mirror of
https://github.com/immich-app/ml-models.git
synced 2026-09-30 13:22:55 +08:00
feat: add ocr to exporter (#61)
* feat: add ppocr to exporter * ocr: unpack scrfd heads * ocr: affine fold Co-authored-by: todorangrg <todorangrg@gmail.com> * rknn dynamic inputs * fp16 outputs * tiled transpose * refactor * target multiple aspect ratios * update cli * add 16:9 * better ci fixture integration * ci bug fixes * check cancellation * chore: bless ci fixtures * tweak runners * add metadata to rknn binaries * canvas->dim * fix fixture trigger * update onnxscript locals * chore: bless ci fixtures * download unconditionally * simplify fix-fixtures * use huge runner for server model * run compilation in subprocess * try/catch recv * remove 16/9 * fix detection mac utilization * chore: bless ci fixtures * conditional rknn compile * add rknn config to render --------- Co-authored-by: todorangrg <todorangrg@gmail.com> Co-authored-by: github-actions <41898282+github-actions[bot]@users.noreply.github.com>
This commit is contained in:
Mert
co-authored by
todorangrg
github-actions
todorangrg
github-actions
parent
c553f6fb08
commit
60e028dee6
@@ -0,0 +1,90 @@
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name: Commit fixtures
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# Takes the renderings a run blessed and commits them to the PR. Called twice: by the export run itself
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# once the matrix settles, and by the label when that run has already finished.
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on:
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workflow_call:
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inputs:
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run-id:
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required: true
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type: string
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branch:
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required: true
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type: string
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head-sha:
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required: true
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type: string
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pull-number:
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required: true
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type: number
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secrets:
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client-id:
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required: true
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private-key:
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required: true
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jobs:
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commit:
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runs-on: ubuntu-latest
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# both entry points can reach the same branch at once; queue them rather than race the push
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concurrency:
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group: commit-fixtures-${{ inputs.branch }}
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cancel-in-progress: false
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permissions:
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actions: read
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steps:
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- id: token
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uses: immich-app/devtools/actions/create-workflow-token@1af396ae134e4bc3b63d947e672bc68bf4ff9dc5 # create-workflow-token-action-v3.0.0
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with:
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client-id: ${{ secrets.client-id }}
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private-key: ${{ secrets.private-key }}
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permission-contents: write
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permission-pull-requests: write
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# nothing in the tree is executed here, so checking out the PR's own code carries no risk
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- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
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with:
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ref: ${{ inputs.branch }}
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persist-credentials: true
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token: ${{ steps.token.outputs.token }}
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# a push between resolving the run and checking out would put these renderings on a commit that
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# never produced them, and the branch checkout above would follow it silently
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- env:
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EXPECTED: ${{ inputs.head-sha }}
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run: |
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actual=$(git rev-parse HEAD)
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if [ "$actual" != "$EXPECTED" ]; then
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echo "head is $actual, not the $EXPECTED these renderings describe; label again" >&2
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exit 1
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fi
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- uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
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with:
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pattern: renderings-*
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# every artifact is rooted at `ci`, so the models merge back into one tree
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merge-multiple: true
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path: ci
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run-id: ${{ inputs.run-id }}
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# the job's own `actions: read`, not the app token, which is scoped to contents and pull requests
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github-token: ${{ github.token }}
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- uses: EndBug/add-and-commit@290ea2c423ad77ca9c62ae0f5b224379612c0321 # v10.0.0
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with:
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default_author: github_actions
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message: 'chore: bless ci fixtures'
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add: ci
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- if: always()
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uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
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env:
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PULL_NUMBER: ${{ inputs.pull-number }}
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with:
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github-token: ${{ steps.token.outputs.token }}
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script: |
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github.rest.issues.removeLabel({
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issue_number: Number(process.env.PULL_NUMBER),
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owner: context.repo.owner,
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repo: context.repo.repo,
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name: 'fix:fixtures',
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})
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@@ -19,6 +19,12 @@ on:
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upload:
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type: boolean
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default: false
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compile-all:
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type: boolean
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default: true
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previous-ref:
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type: string
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default: ''
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jobs:
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export:
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@@ -26,6 +32,8 @@ jobs:
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steps:
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- name: Checkout
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uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
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with:
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fetch-depth: 0 # the compile scope below diffs this model's renderings against the previous ref
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- uses: astral-sh/setup-uv@c771a70e6277c0a99b617c7a806ffedaca235ff9 # v9.0.0
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with:
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@@ -39,15 +47,15 @@ jobs:
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HF_MODEL_NAME: ${{ inputs.hf-name || inputs.model-name }}
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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# Here rather than in its own job because this is where an exported model exists
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# Here rather than in its own job because this is where an exported model exists.
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- id: check
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run: uv run --frozen --extra export immich-model check --models models
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run: uv run --frozen --extra export immich-model check model models
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# An exporter change stales every rendering at once; hand back this run's rather than making the
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# author re-export the catalog
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- if: ${{ failure() && steps.check.outcome == 'failure' }}
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run: uv run --frozen --extra export immich-model check --models models --bless
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run: uv run --frozen --extra export immich-model check model models --bless
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- if: ${{ failure() && steps.check.outcome == 'failure' }}
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uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
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with:
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@@ -56,8 +64,22 @@ jobs:
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ci/graphs/${{ inputs.model-name }}
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ci/rewrites/${{ inputs.model-name }}
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# Skip compilation if the renderings are the same, being what the binary is built from
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- id: needed
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env:
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MODEL_NAME: ${{ inputs.model-name }}
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COMPILE_ALL: ${{ inputs.compile-all }}
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PREVIOUS_REF: ${{ inputs.previous-ref }}
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run: |
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git add -N ci # a model exported for the first time renders to a path git is not yet tracking
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if [ "$COMPILE_ALL" = 'true' ] || ! git diff --quiet "$PREVIOUS_REF" -- ci/plans.txt \
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"ci/graphs/$MODEL_NAME" "ci/rewrites/$MODEL_NAME"; then
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echo "compile=yes" >> "$GITHUB_OUTPUT"
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fi
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# RKNN binaries are built from the same fused ONNX every other backend uses
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- run: uv run --frozen --extra rknn immich-model rknn compile "$MODEL_NAME"
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- if: ${{ steps.needed.outputs.compile }}
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run: uv run --frozen --extra rknn immich-model rknn compile "$MODEL_NAME"
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env:
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MODEL_NAME: ${{ inputs.model-name }}
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@@ -0,0 +1,60 @@
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name: Fix fixtures
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# The label applied AFTER a run finished; applied before or during, that run's own `commit-fixtures` job
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# takes it instead, so nothing here ever waits.
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on:
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pull_request:
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types: ['labeled']
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permissions: {}
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jobs:
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find:
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if: ${{ github.event.label.name == 'fix:fixtures' }}
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runs-on: ubuntu-latest
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permissions:
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actions: read
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outputs:
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run-id: ${{ steps.source.outputs.run-id }}
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steps:
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# which run to take the renderings from; whether it blessed any is `commit-fixtures`' problem, an
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# empty download and a clean tree both being no-ops there
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- id: source
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uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
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env:
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HEAD_SHA: ${{ github.event.pull_request.head.sha }}
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with:
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script: |
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const { owner, repo } = context.repo
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const head = process.env.HEAD_SHA
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const runs = await github.paginate(github.rest.actions.listWorkflowRuns, {
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owner, repo, workflow_id: 'push.yaml', head_sha: head, per_page: 100,
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})
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// an in-flight run reads the label in its own `labelled` job, and committing under it would
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// move the head that run's `commit-fixtures` verifies. Leaving the label set is the retry.
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const pending = runs.find((run) => run.status !== 'completed')
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if (pending) {
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return core.info(`run ${pending.id} is ${pending.status} and will commit these itself`)
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}
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// a superseded run holds whichever renderings it reached before it died, which is not the set
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const source = runs.find((run) => run.conclusion !== 'cancelled')
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if (!source) {
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return core.info(`no completed run for ${head.slice(0, 7)} to take renderings from`)
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}
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core.info(`taking renderings from run ${source.id}`)
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core.setOutput('run-id', source.id)
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commit:
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needs: find
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if: ${{ needs.find.outputs.run-id }}
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permissions:
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actions: read
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uses: ./.github/workflows/commit-fixtures.yaml
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secrets:
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client-id: ${{ secrets.PUSH_O_MATIC_APP_CLIENT_ID }}
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private-key: ${{ secrets.PUSH_O_MATIC_APP_KEY }}
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with:
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run-id: ${{ needs.find.outputs.run-id }}
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branch: ${{ github.event.pull_request.head.ref }}
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head-sha: ${{ github.event.pull_request.head.sha }}
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pull-number: ${{ github.event.pull_request.number }}
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@@ -3,6 +3,7 @@ on:
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push:
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branches: ['main']
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pull_request:
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types: ['opened', 'synchronize', 'reopened']
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release:
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types: ['published']
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workflow_dispatch:
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@@ -28,16 +29,26 @@ jobs:
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persist-credentials: false
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- uses: astral-sh/setup-uv@c771a70e6277c0a99b617c7a806ffedaca235ff9 # v9.0.0
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with:
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# this job produces no artifact for a poisoned cache to reach
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# the rendering it hands back is of this PR's own source and is committed to this PR's own head,
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# and a PR-scoped cache is readable by no other PR, so a poisoned one reaches nothing new
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enable-cache: true # zizmor: ignore[cache-poisoning]
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cache-dependency-glob: uv.lock
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- run: uv run --frozen --extra export immich-model check
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- id: check
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run: uv run --frozen --extra export immich-model check plan
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- if: ${{ failure() && steps.check.outcome == 'failure' }}
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run: uv run --frozen --extra export immich-model check plan --bless
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- if: ${{ failure() && steps.check.outcome == 'failure' }}
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uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
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with:
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name: renderings-plans
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path: ci/plans.txt
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configure:
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runs-on: ubuntu-latest
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outputs:
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to_export: ${{ steps.scope.outputs.to_export }}
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unchanged: ${{ steps.scope.outputs.unchanged }}
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previous-ref: ${{ steps.ref.outputs.previous-ref }}
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steps:
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- name: Checkout new ref
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uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
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@@ -85,8 +96,8 @@ jobs:
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script({core})
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# TODO: Explicitly skip this if nothing to do
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export:
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if: ${{ needs.configure.outputs.to_export != '[]' }}
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uses: ./.github/workflows/export.yaml
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needs: configure
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secrets: inherit
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@@ -102,3 +113,42 @@ jobs:
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hf-name: ${{ matrix.hf-name }}
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runner: ${{ matrix.runner || 'ubuntu-latest'}}
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upload: ${{ inputs.force || github.event_name == 'release'}}
|
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previous-ref: ${{ needs.configure.outputs.previous-ref }}
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compile-all: ${{ inputs.force || github.event_name == 'release' }}
|
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|
||||
# Read at the end rather than off the event payload, so labelling while the matrix runs still counts.
|
||||
labelled:
|
||||
if: ${{ !cancelled() && github.event_name == 'pull_request' }}
|
||||
needs: [plans, export]
|
||||
runs-on: ubuntu-latest
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||||
permissions:
|
||||
pull-requests: read
|
||||
outputs:
|
||||
wanted: ${{ steps.label.outputs.wanted }}
|
||||
steps:
|
||||
- id: label
|
||||
uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
|
||||
with:
|
||||
script: |
|
||||
const { data: pull } = await github.rest.pulls.get({
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo,
|
||||
pull_number: context.payload.pull_request.number,
|
||||
})
|
||||
const wanted = pull.labels.some((applied) => applied.name === 'fix:fixtures')
|
||||
core.info(wanted ? 'labelled fix:fixtures' : 'not labelled, leaving the fixtures alone')
|
||||
core.setOutput('wanted', wanted ? 'yes' : '')
|
||||
|
||||
commit-fixtures:
|
||||
needs: labelled
|
||||
if: ${{ !cancelled() && needs.labelled.outputs.wanted }}
|
||||
uses: ./.github/workflows/commit-fixtures.yaml
|
||||
secrets:
|
||||
client-id: ${{ secrets.PUSH_O_MATIC_APP_CLIENT_ID }}
|
||||
private-key: ${{ secrets.PUSH_O_MATIC_APP_KEY }}
|
||||
with:
|
||||
run-id: ${{ github.run_id }}
|
||||
branch: ${{ github.event.pull_request.head.ref }}
|
||||
head-sha: ${{ github.event.pull_request.head.sha }}
|
||||
pull-number: ${{ github.event.pull_request.number }}
|
||||
|
||||
|
||||
@@ -0,0 +1,468 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,192,unk__22,unk__23] "Add.105"
|
||||
float[batch,192,unk__22,unk__23] "Add.111"
|
||||
float[batch,192,unk__42,unk__43] "Add.117"
|
||||
float[batch,48,1,1] "Add.119"
|
||||
float[batch,192,1,1] "Add.121"
|
||||
float[batch,384,unk__42,unk__43] "Add.125"
|
||||
float[batch,384,unk__42,unk__43] "Add.131"
|
||||
float[batch,384,unk__42,unk__43] "Add.133"
|
||||
float[batch,96,1,1] "Add.135"
|
||||
float[batch,384,1,1] "Add.137"
|
||||
float[batch,384,unk__42,unk__43] "Add.141"
|
||||
float[batch,384,unk__42,unk__43] "Add.147"
|
||||
float[batch,32,unk__6,unk__7] "Add.15"
|
||||
float[batch,384,unk__42,unk__43] "Add.153"
|
||||
float[batch,384,unk__42,unk__43] "Add.159"
|
||||
float[batch,384,unk__42,unk__43] "Add.165"
|
||||
float[batch,96,unk__42,unk__43] "Add.181"
|
||||
float[batch,96,unk__22,unk__23] "Add.187"
|
||||
float[batch,48,unk__6,unk__7] "Add.19"
|
||||
float[batch,96,unk__14,unk__15] "Add.193"
|
||||
float[batch,96,unk__6,unk__7] "Add.199"
|
||||
float[batch,96,unk__22,unk__23] "Add.201"
|
||||
float[batch,96,unk__14,unk__15] "Add.203"
|
||||
float[batch,96,unk__6,unk__7] "Add.205"
|
||||
float[batch,24,unk__42,unk__43] "Add.211"
|
||||
float[batch,24,unk__22,unk__23] "Add.217"
|
||||
float[batch,24,unk__14,unk__15] "Add.223"
|
||||
float[batch,24,unk__6,unk__7] "Add.229"
|
||||
float[batch,1,height,width] "Add.233"
|
||||
float[batch,48,unk__6,unk__7] "Add.25"
|
||||
float[batch,16,unk__0,unk__1] "Add.3"
|
||||
float[batch,48,unk__6,unk__7] "Add.31"
|
||||
float[batch,48,unk__14,unk__15] "Add.37"
|
||||
float[batch,96,unk__14,unk__15] "Add.41"
|
||||
float[batch,96,unk__14,unk__15] "Add.47"
|
||||
float[batch,96,unk__14,unk__15] "Add.53"
|
||||
float[batch,96,unk__22,unk__23] "Add.59"
|
||||
float[batch,192,unk__22,unk__23] "Add.63"
|
||||
float[batch,192,unk__22,unk__23] "Add.69"
|
||||
float[batch,192,unk__22,unk__23] "Add.75"
|
||||
float[batch,192,unk__22,unk__23] "Add.81"
|
||||
float[batch,192,unk__22,unk__23] "Add.87"
|
||||
float[batch,32,unk__0,unk__1] "Add.9"
|
||||
float[batch,192,unk__22,unk__23] "Add.93"
|
||||
float[batch,192,unk__22,unk__23] "Add.99"
|
||||
float[batch,96,unk__6,unk__7] "Concat.1"
|
||||
float[batch,192,unk__42,unk__43] "Mul.77"
|
||||
float[batch,384,unk__42,unk__43] "Mul.85"
|
||||
float[batch,384,unk__42,unk__43] "Mul.87"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,96,unk__42,unk__43] "p2o.pd_op.conv2d.23.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.conv2d.26.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.conv2d.29.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.conv2d.32.0"
|
||||
float[batch,24,unk__42,unk__43] "p2o.pd_op.conv2d.35.0"
|
||||
float[batch,24,unk__22,unk__23] "p2o.pd_op.conv2d.38.0"
|
||||
float[batch,24,unk__14,unk__15] "p2o.pd_op.conv2d.41.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.conv2d.44.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.hardswish.0.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.hardswish.1.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.10.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.11.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.12.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.13.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.14.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.15.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.16.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.17.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.18.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.19.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.2.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.20.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.21.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.22.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.23.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.3.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.4.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.5.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.6.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.7.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.8.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.9.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.pool2d.1.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.2.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.3.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.4.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.5.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.6.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.7.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.8.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.9.0"
|
||||
float[batch,48,1,1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.relu.10.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.relu.11.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.2.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.3.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.4.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.5.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.6.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.7.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.8.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.9.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,96,1,1] se_group0_down
|
||||
float[batch,384,1,1] se_group0_gates
|
||||
float[batch,384,1,1] se_group0_pooled
|
||||
float[batch,96,1,1] se_group0_relu
|
||||
float[batch,384,1,1] se_group0_up
|
||||
float[batch,24,1,1] se_group1_down
|
||||
float[batch,96,1,1] se_group1_gates
|
||||
float[batch,96,1,1] se_group1_pooled
|
||||
float[batch,24,1,1] se_group1_relu
|
||||
float[batch,96,1,1] se_group1_up
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,16,unk__0,unk__1] val_0
|
||||
float[batch,32,unk__0,unk__1] val_1
|
||||
float[batch,96,unk__14,unk__15] val_10
|
||||
float[batch,96,unk__14,unk__15] val_11
|
||||
float[batch,96,unk__14,unk__15] val_12
|
||||
float[batch,192,unk__22,unk__23] val_13
|
||||
float[batch,192,unk__22,unk__23] val_14
|
||||
float[batch,192,unk__22,unk__23] val_15
|
||||
float[batch,192,unk__22,unk__23] val_16
|
||||
float[batch,192,unk__22,unk__23] val_17
|
||||
float[batch,192,unk__22,unk__23] val_18
|
||||
float[batch,192,unk__22,unk__23] val_19
|
||||
float[batch,32,unk__0,unk__1] val_2
|
||||
float[batch,192,unk__22,unk__23] val_20
|
||||
float[batch,192,unk__22,unk__23] val_21
|
||||
float[batch,192,unk__22,unk__23] val_22
|
||||
float[batch,192,unk__22,unk__23] val_23
|
||||
float[batch,192,unk__22,unk__23] val_24
|
||||
float[batch,192,unk__22,unk__23] val_25
|
||||
float[batch,192,unk__22,unk__23] val_26
|
||||
float[batch,384,unk__42,unk__43] val_27
|
||||
float[batch,384,unk__42,unk__43] val_28
|
||||
float[batch,384,unk__42,unk__43] val_29
|
||||
float[batch,48,unk__6,unk__7] val_3
|
||||
float[batch,384,unk__42,unk__43] val_30
|
||||
float[batch,384,unk__42,unk__43] val_31
|
||||
float[batch,384,unk__42,unk__43] val_32
|
||||
float[batch,384,unk__42,unk__43] val_33
|
||||
float[batch,384,unk__42,unk__43] val_34
|
||||
float[batch,384,unk__42,unk__43] val_35
|
||||
float[batch,384,unk__42,unk__43] val_36
|
||||
float[batch,96,1,1] val_37
|
||||
float[batch,96,1,1] val_38
|
||||
float[batch,96,1,1] val_39
|
||||
float[batch,48,unk__6,unk__7] val_4
|
||||
float[batch,96,1,1] val_40
|
||||
float[batch,24,1,1] val_41
|
||||
float[batch,24,1,1] val_42
|
||||
float[batch,24,1,1] val_43
|
||||
float[batch,24,1,1] val_44
|
||||
float[batch,48,unk__6,unk__7] val_5
|
||||
float[batch,48,unk__6,unk__7] val_6
|
||||
float[batch,48,unk__6,unk__7] val_7
|
||||
float[batch,96,unk__14,unk__15] val_8
|
||||
float[batch,96,unk__14,unk__15] val_9
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_0.w_0", "conv2d_0.w_0_bias")
|
||||
"Add.3" = Conv <dilations: ints = [1, 1], group: int = 16, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.0.0", "conv2d_161.w_0_lab", "p2o.pd_op.depthwise_conv2d.0.0_bias_lab")
|
||||
val_0 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.3")
|
||||
"p2o.pd_op.hardswish.0.0" = Mul ("Add.3", val_0)
|
||||
"Add.9" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.0.0", "conv2d_162.w_0_lab_lab", "p2o.pd_op.conv2d.1.0_bias_lab_lab")
|
||||
val_1 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.9")
|
||||
"p2o.pd_op.hardswish.1.0" = Mul ("Add.9", val_1)
|
||||
val_2 = Add ("p2o.pd_op.hardswish.1.0", "conv2d_163.w_0_lab_laboffset")
|
||||
"Add.15" = Conv <dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_2, "conv2d_163.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.1.0_bias_lab")
|
||||
"Add.19" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.15", "conv2d_164.w_0_lab", "p2o.pd_op.conv2d.2.0_bias_lab")
|
||||
val_3 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.19")
|
||||
"p2o.pd_op.hardswish.2.0" = Mul ("Add.19", val_3)
|
||||
val_4 = Add ("p2o.pd_op.hardswish.2.0", "conv2d_165.w_0_lab_laboffset")
|
||||
"Add.25" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_4, "conv2d_165.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.2.0_bias_lab")
|
||||
val_5 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.25")
|
||||
"p2o.pd_op.hardswish.3.0" = Mul ("Add.25", val_5)
|
||||
"Add.31" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.3.0", "conv2d_166.w_0_lab_lab", "p2o.pd_op.conv2d.3.0_bias_lab_lab")
|
||||
val_6 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.31")
|
||||
"p2o.pd_op.hardswish.4.0" = Mul ("Add.31", val_6)
|
||||
val_7 = Add ("p2o.pd_op.hardswish.4.0", "conv2d_167.w_0_lab_laboffset")
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_7, "conv2d_167.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.3.0_bias_lab")
|
||||
"Add.41" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.37", "conv2d_168.w_0_lab", "p2o.pd_op.conv2d.4.0_bias_lab")
|
||||
val_8 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.41")
|
||||
"p2o.pd_op.hardswish.5.0" = Mul ("Add.41", val_8)
|
||||
val_9 = Add ("p2o.pd_op.hardswish.5.0", "conv2d_169.w_0_lab_laboffset")
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_9, "conv2d_169.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.4.0_bias_lab")
|
||||
val_10 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.47")
|
||||
"p2o.pd_op.hardswish.6.0" = Mul ("Add.47", val_10)
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.6.0", "conv2d_170.w_0_lab_lab", "p2o.pd_op.conv2d.5.0_bias_lab_lab")
|
||||
val_11 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.53")
|
||||
"p2o.pd_op.hardswish.7.0" = Mul ("Add.53", val_11)
|
||||
val_12 = Add ("p2o.pd_op.hardswish.7.0", "conv2d_171.w_0_lab_laboffset")
|
||||
"Add.59" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_12, "conv2d_171.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.5.0_bias_lab")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.59", "conv2d_172.w_0_lab", "p2o.pd_op.conv2d.6.0_bias_lab")
|
||||
val_13 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.63")
|
||||
"p2o.pd_op.hardswish.8.0" = Mul ("Add.63", val_13)
|
||||
val_14 = Add ("p2o.pd_op.hardswish.8.0", "conv2d_173.w_0_lab_laboffset")
|
||||
"Add.69" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_14, "conv2d_173.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.6.0_bias_lab")
|
||||
val_15 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.69")
|
||||
"p2o.pd_op.hardswish.9.0" = Mul ("Add.69", val_15)
|
||||
"Add.75" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.9.0", "conv2d_174.w_0_lab_lab", "p2o.pd_op.conv2d.7.0_bias_lab_lab")
|
||||
val_16 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.75")
|
||||
"p2o.pd_op.hardswish.10.0" = Mul ("Add.75", val_16)
|
||||
val_17 = Add ("p2o.pd_op.hardswish.10.0", "conv2d_175.w_0_lab_laboffset")
|
||||
"Add.81" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_17, "conv2d_175.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.7.0_bias_lab")
|
||||
val_18 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.81")
|
||||
"p2o.pd_op.hardswish.11.0" = Mul ("Add.81", val_18)
|
||||
"Add.87" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.11.0", "conv2d_176.w_0_lab_lab", "p2o.pd_op.conv2d.8.0_bias_lab_lab")
|
||||
val_19 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.87")
|
||||
"p2o.pd_op.hardswish.12.0" = Mul ("Add.87", val_19)
|
||||
val_20 = Add ("p2o.pd_op.hardswish.12.0", "conv2d_177.w_0_lab_laboffset")
|
||||
"Add.93" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_20, "conv2d_177.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.8.0_bias_lab")
|
||||
val_21 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.93")
|
||||
"p2o.pd_op.hardswish.13.0" = Mul ("Add.93", val_21)
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.13.0", "conv2d_178.w_0_lab_lab", "p2o.pd_op.conv2d.9.0_bias_lab_lab")
|
||||
val_22 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.99")
|
||||
"p2o.pd_op.hardswish.14.0" = Mul ("Add.99", val_22)
|
||||
val_23 = Add ("p2o.pd_op.hardswish.14.0", "conv2d_179.w_0_lab_laboffset")
|
||||
"Add.105" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_23, "conv2d_179.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.9.0_bias_lab")
|
||||
val_24 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.105")
|
||||
"p2o.pd_op.hardswish.15.0" = Mul ("Add.105", val_24)
|
||||
"Add.111" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.15.0", "conv2d_180.w_0_lab_lab", "p2o.pd_op.conv2d.10.0_bias_lab_lab")
|
||||
val_25 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.111")
|
||||
"p2o.pd_op.hardswish.16.0" = Mul ("Add.111", val_25)
|
||||
val_26 = Add ("p2o.pd_op.hardswish.16.0", "conv2d_181.w_0_lab_laboffset")
|
||||
"Add.117" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [2, 2]> (val_26, "conv2d_181.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.10.0_bias_lab")
|
||||
["GlobalAveragePool.0"] "p2o.pd_op.pool2d.0.0" = GlobalAveragePool ("Add.117")
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.0.0", "conv2d_96.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.119")
|
||||
"Add.121" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_97.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.121")
|
||||
["Mul.76"] "Mul.77" = Mul ("Add.117", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.77", "conv2d_182.w_0_lab", "p2o.pd_op.conv2d.13.0_bias_lab")
|
||||
val_27 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.125")
|
||||
"p2o.pd_op.hardswish.17.0" = Mul ("Add.125", val_27)
|
||||
val_28 = Add ("p2o.pd_op.hardswish.17.0", "conv2d_183.w_0_lab_laboffset")
|
||||
"Add.131" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_28, "conv2d_183.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.11.0_bias_lab")
|
||||
val_29 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.131")
|
||||
"p2o.pd_op.hardswish.18.0" = Mul ("Add.131", val_29)
|
||||
["Mul.84"] "Mul.85" = Mul ("learnable_affine_block_45.w_0", "p2o.pd_op.hardswish.18.0")
|
||||
["Add.132"] "Add.133" = Add ("Mul.85", "learnable_affine_block_45.w_1")
|
||||
["GlobalAveragePool.1"] "p2o.pd_op.pool2d.1.0" = GlobalAveragePool ("Add.133")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.1.0", "conv2d_107.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.135")
|
||||
"Add.137" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_108.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.137")
|
||||
["Mul.86"] "Mul.87" = Mul ("Add.133", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.141" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.87", "conv2d_184.w_0_lab", "p2o.pd_op.conv2d.16.0_bias_lab")
|
||||
val_30 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.141")
|
||||
"p2o.pd_op.hardswish.19.0" = Mul ("Add.141", val_30)
|
||||
val_31 = Add ("p2o.pd_op.hardswish.19.0", "conv2d_185.w_0_lab_laboffset")
|
||||
"Add.147" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_31, "conv2d_185.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.12.0_bias_lab")
|
||||
val_32 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.147")
|
||||
"p2o.pd_op.hardswish.20.0" = Mul ("Add.147", val_32)
|
||||
"Add.153" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.20.0", "conv2d_186.w_0_lab_lab", "p2o.pd_op.conv2d.17.0_bias_lab_lab")
|
||||
val_33 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.153")
|
||||
"p2o.pd_op.hardswish.21.0" = Mul ("Add.153", val_33)
|
||||
val_34 = Add ("p2o.pd_op.hardswish.21.0", "conv2d_187.w_0_lab_laboffset")
|
||||
"Add.159" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_34, "conv2d_187.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.13.0_bias_lab")
|
||||
val_35 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.159")
|
||||
"p2o.pd_op.hardswish.22.0" = Mul ("Add.159", val_35)
|
||||
"Add.165" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.22.0", "conv2d_188.w_0_lab_lab", "p2o.pd_op.conv2d.18.0_bias_lab_lab")
|
||||
val_36 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.165")
|
||||
"p2o.pd_op.hardswish.23.0" = Mul ("Add.165", val_36)
|
||||
"p2o.pd_op.conv2d.23.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.23.0", "Conv.37_folded_w_lab", "Conv.37_folded_b_lab")
|
||||
["GlobalAveragePool.2"] "p2o.pd_op.pool2d.2.0" = GlobalAveragePool ("p2o.pd_op.conv2d.23.0")
|
||||
"p2o.pd_op.conv2d.26.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_26, "Conv.40_folded_w_labscale", "Conv.40_folded_b")
|
||||
["GlobalAveragePool.3"] "p2o.pd_op.pool2d.3.0" = GlobalAveragePool ("p2o.pd_op.conv2d.26.0")
|
||||
"p2o.pd_op.conv2d.29.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_12, "Conv.43_folded_w_labscale", "Conv.43_folded_b")
|
||||
["GlobalAveragePool.4"] "p2o.pd_op.pool2d.4.0" = GlobalAveragePool ("p2o.pd_op.conv2d.29.0")
|
||||
"p2o.pd_op.conv2d.32.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_7, "Conv.46_folded_w_labscale", "Conv.46_folded_b")
|
||||
["GlobalAveragePool.5"] "p2o.pd_op.pool2d.5.0" = GlobalAveragePool ("p2o.pd_op.conv2d.32.0")
|
||||
se_group0_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.2.0", "p2o.pd_op.pool2d.3.0", "p2o.pd_op.pool2d.4.0", "p2o.pd_op.pool2d.5.0")
|
||||
se_group0_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_pooled, se_group0_down1, se_group0_down2)
|
||||
se_group0_relu = Relu (se_group0_down)
|
||||
se_group0_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_relu, se_group0_up1, se_group0_up2)
|
||||
se_group0_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group0_up)
|
||||
"se_group0_p2o.pd_op.hardsigmoid.2.0", "se_group0_p2o.pd_op.hardsigmoid.3.0", "se_group0_p2o.pd_op.hardsigmoid.4.0", "se_group0_p2o.pd_op.hardsigmoid.5.0" = Split <axis: int = 1> (se_group0_gates, se_group0_sizes)
|
||||
val_37 = Add ("se_group0_p2o.pd_op.hardsigmoid.2.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.181" = Mul ("p2o.pd_op.conv2d.23.0", val_37)
|
||||
val_38 = Add ("se_group0_p2o.pd_op.hardsigmoid.3.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.187" = Mul ("p2o.pd_op.conv2d.26.0", val_38)
|
||||
val_39 = Add ("se_group0_p2o.pd_op.hardsigmoid.4.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.193" = Mul ("p2o.pd_op.conv2d.29.0", val_39)
|
||||
val_40 = Add ("se_group0_p2o.pd_op.hardsigmoid.5.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.199" = Mul ("p2o.pd_op.conv2d.32.0", val_40)
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.181", "helper.constant.1", "helper.constant.0")
|
||||
["Add.200"] "Add.201" = Add ("Add.187", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.201", "helper.constant.1", "helper.constant.0")
|
||||
["Add.202"] "Add.203" = Add ("Add.193", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.203", "helper.constant.1", "helper.constant.0")
|
||||
["Add.204"] "Add.205" = Add ("Add.199", "p2o.pd_op.nearest_interp.2.0")
|
||||
["Conv.49"] "p2o.pd_op.conv2d.35.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.181", "conv2d_156.w_0")
|
||||
["GlobalAveragePool.6"] "p2o.pd_op.pool2d.6.0" = GlobalAveragePool ("p2o.pd_op.conv2d.35.0")
|
||||
["Conv.52"] "p2o.pd_op.conv2d.38.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.201", "conv2d_150.w_0")
|
||||
["GlobalAveragePool.7"] "p2o.pd_op.pool2d.7.0" = GlobalAveragePool ("p2o.pd_op.conv2d.38.0")
|
||||
["Conv.55"] "p2o.pd_op.conv2d.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.203", "conv2d_144.w_0")
|
||||
["GlobalAveragePool.8"] "p2o.pd_op.pool2d.8.0" = GlobalAveragePool ("p2o.pd_op.conv2d.41.0")
|
||||
["Conv.58"] "p2o.pd_op.conv2d.44.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.205", "conv2d_138.w_0")
|
||||
["GlobalAveragePool.9"] "p2o.pd_op.pool2d.9.0" = GlobalAveragePool ("p2o.pd_op.conv2d.44.0")
|
||||
se_group1_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.6.0", "p2o.pd_op.pool2d.7.0", "p2o.pd_op.pool2d.8.0", "p2o.pd_op.pool2d.9.0")
|
||||
se_group1_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_pooled, se_group1_down1, se_group1_down2)
|
||||
se_group1_relu = Relu (se_group1_down)
|
||||
se_group1_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_relu, se_group1_up1, se_group1_up2)
|
||||
se_group1_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group1_up)
|
||||
"se_group1_p2o.pd_op.hardsigmoid.6.0", "se_group1_p2o.pd_op.hardsigmoid.7.0", "se_group1_p2o.pd_op.hardsigmoid.8.0", "se_group1_p2o.pd_op.hardsigmoid.9.0" = Split <axis: int = 1> (se_group1_gates, se_group1_sizes)
|
||||
val_41 = Add ("se_group1_p2o.pd_op.hardsigmoid.6.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.211" = Mul ("p2o.pd_op.conv2d.35.0", val_41)
|
||||
val_42 = Add ("se_group1_p2o.pd_op.hardsigmoid.7.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.217" = Mul ("p2o.pd_op.conv2d.38.0", val_42)
|
||||
val_43 = Add ("se_group1_p2o.pd_op.hardsigmoid.8.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.223" = Mul ("p2o.pd_op.conv2d.41.0", val_43)
|
||||
val_44 = Add ("se_group1_p2o.pd_op.hardsigmoid.9.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.229" = Mul ("p2o.pd_op.conv2d.44.0", val_44)
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.211", "helper.constant.1", "helper.constant.6")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.217", "helper.constant.1", "helper.constant.8")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.223", "helper.constant.1", "helper.constant.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.229")
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.1", "conv2d_159.w_0", "conv2d_159.w_0_bias")
|
||||
["Relu.10"] "p2o.pd_op.relu.10.0" = Relu ("p2o.pd_op.batch_norm_.1.0")
|
||||
"p2o.pd_op.batch_norm_.2.0" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.10.0", "auto.cast.57", "ConvTranspose.1_bias")
|
||||
["Relu.11"] "p2o.pd_op.relu.11.0" = Relu ("p2o.pd_op.batch_norm_.2.0")
|
||||
"Add.233" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.11.0", "auto.cast.60", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] fetch_name_0 = Sigmoid ("Add.233")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
Conv.37_folded_b_lab FLOAT[96] 0d571951a1e0
|
||||
Conv.37_folded_w_lab FLOAT[96,384,1,1] 1d0305563ea7
|
||||
Conv.40_folded_b FLOAT[96] dcfdd514912d
|
||||
Conv.40_folded_w_labscale FLOAT[96,192,1,1] bacc8274202e
|
||||
Conv.43_folded_b FLOAT[96] ee902cf71aad
|
||||
Conv.43_folded_w_labscale FLOAT[96,96,1,1] b17e08485dc5
|
||||
Conv.46_folded_b FLOAT[96] 6541e510a35d
|
||||
Conv.46_folded_w_labscale FLOAT[96,48,1,1] 9423b2c0951a
|
||||
ConvTranspose.1_bias FLOAT[24] 64cabf62980d
|
||||
ConvTranspose.3_bias FLOAT[1] 55c86fee1edb
|
||||
auto.cast.57 FLOAT[24,24,2,2] 1dc864bec64f
|
||||
auto.cast.60 FLOAT[24,1,2,2] c9862b3a19bc
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_0.w_0 FLOAT[16,3,3,3] 7841f2f3efae
|
||||
conv2d_0.w_0_bias FLOAT[16] 2713bf453fd1
|
||||
conv2d_107.w_0 FLOAT[96,384,1,1] 2fc401aa1ec6
|
||||
conv2d_108.w_0 FLOAT[384,96,1,1] f2a9a9261c07
|
||||
conv2d_138.w_0 FLOAT[24,96,3,3] 47aa8ba1db50
|
||||
conv2d_144.w_0 FLOAT[24,96,3,3] cd85b03c436c
|
||||
conv2d_150.w_0 FLOAT[24,96,3,3] 591f14004ce0
|
||||
conv2d_156.w_0 FLOAT[24,96,3,3] 5e0bc4bf821e
|
||||
conv2d_159.w_0 FLOAT[24,96,3,3] 43b6b1b17bef
|
||||
conv2d_159.w_0_bias FLOAT[24] c98267f8273d
|
||||
conv2d_161.w_0_lab FLOAT[16,1,3,3] 22528d709d37
|
||||
conv2d_162.w_0_lab_lab FLOAT[32,16,1,1] 051645505e21
|
||||
conv2d_163.w_0_lab_laboffset FLOAT[] 92a142f7dc41
|
||||
conv2d_163.w_0_lab_labscale FLOAT[32,1,3,3] 8694842bd3fb
|
||||
conv2d_164.w_0_lab FLOAT[48,32,1,1] 0c937f040d0e
|
||||
conv2d_165.w_0_lab_laboffset FLOAT[] 012179917694
|
||||
conv2d_165.w_0_lab_labscale FLOAT[48,1,3,3] 7d779e5616fa
|
||||
conv2d_166.w_0_lab_lab FLOAT[48,48,1,1] d70c86b2d1ec
|
||||
conv2d_167.w_0_lab_laboffset FLOAT[] 9741b37d98e3
|
||||
conv2d_167.w_0_lab_labscale FLOAT[48,1,3,3] fa2e1db2eb62
|
||||
conv2d_168.w_0_lab FLOAT[96,48,1,1] 81e13e0bd382
|
||||
conv2d_169.w_0_lab_laboffset FLOAT[] f3e015d53e9a
|
||||
conv2d_169.w_0_lab_labscale FLOAT[96,1,3,3] 75bbb69deb68
|
||||
conv2d_170.w_0_lab_lab FLOAT[96,96,1,1] 59b22a69e345
|
||||
conv2d_171.w_0_lab_laboffset FLOAT[] f42328163f40
|
||||
conv2d_171.w_0_lab_labscale FLOAT[96,1,3,3] 65cbca6287a2
|
||||
conv2d_172.w_0_lab FLOAT[192,96,1,1] ff93ca701d2f
|
||||
conv2d_173.w_0_lab_laboffset FLOAT[] b76450d3656f
|
||||
conv2d_173.w_0_lab_labscale FLOAT[192,1,5,5] 28d7de00679c
|
||||
conv2d_174.w_0_lab_lab FLOAT[192,192,1,1] 53cf6f343ec2
|
||||
conv2d_175.w_0_lab_laboffset FLOAT[] e665434a5d2d
|
||||
conv2d_175.w_0_lab_labscale FLOAT[192,1,5,5] 3c0aa815839d
|
||||
conv2d_176.w_0_lab_lab FLOAT[192,192,1,1] cb45f031f07b
|
||||
conv2d_177.w_0_lab_laboffset FLOAT[] e095ffc76247
|
||||
conv2d_177.w_0_lab_labscale FLOAT[192,1,5,5] 22fe03b75591
|
||||
conv2d_178.w_0_lab_lab FLOAT[192,192,1,1] c259022f5c3d
|
||||
conv2d_179.w_0_lab_laboffset FLOAT[] 5842420f0e64
|
||||
conv2d_179.w_0_lab_labscale FLOAT[192,1,5,5] 408bbab0d507
|
||||
conv2d_180.w_0_lab_lab FLOAT[192,192,1,1] 85871ea30bf1
|
||||
conv2d_181.w_0_lab_laboffset FLOAT[] 9e0407355f14
|
||||
conv2d_181.w_0_lab_labscale FLOAT[192,1,5,5] 75764b0f5265
|
||||
conv2d_182.w_0_lab FLOAT[384,192,1,1] 81235d1a972f
|
||||
conv2d_183.w_0_lab_laboffset FLOAT[] e648d792317a
|
||||
conv2d_183.w_0_lab_labscale FLOAT[384,1,5,5] f5341adaad28
|
||||
conv2d_184.w_0_lab FLOAT[384,384,1,1] c37a7cec640b
|
||||
conv2d_185.w_0_lab_laboffset FLOAT[] 768fa13da14b
|
||||
conv2d_185.w_0_lab_labscale FLOAT[384,1,5,5] 6bacb713155c
|
||||
conv2d_186.w_0_lab_lab FLOAT[384,384,1,1] 2fa80ae1b18f
|
||||
conv2d_187.w_0_lab_laboffset FLOAT[] ad505dafbd90
|
||||
conv2d_187.w_0_lab_labscale FLOAT[384,1,5,5] a221bd8406f2
|
||||
conv2d_188.w_0_lab_lab FLOAT[384,384,1,1] 9ea062b2f1b4
|
||||
conv2d_96.w_0 FLOAT[48,192,1,1] 6d73ce1fb738
|
||||
conv2d_97.w_0 FLOAT[192,48,1,1] 8098a00a81f0
|
||||
helper.constant.0 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.1 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.6 FLOAT[4] cf5451a623be
|
||||
helper.constant.8 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
learnable_affine_block_45.w_0 FLOAT[1] 65444e550b77
|
||||
learnable_affine_block_45.w_1 FLOAT[1] f2ee18a061af
|
||||
p2o.pd_op.conv2d.1.0_bias_lab_lab FLOAT[32] 3f4be24e33b8
|
||||
p2o.pd_op.conv2d.10.0_bias_lab_lab FLOAT[192] e32536500417
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[48] 961ec85108cb
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[192] c348751cbed0
|
||||
p2o.pd_op.conv2d.13.0_bias_lab FLOAT[384] 1b6d0aa0e977
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[96] 7876208c6fb1
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[384] 871907fff11d
|
||||
p2o.pd_op.conv2d.16.0_bias_lab FLOAT[384] fd15d67f1e85
|
||||
p2o.pd_op.conv2d.17.0_bias_lab_lab FLOAT[384] 097f0d068f05
|
||||
p2o.pd_op.conv2d.18.0_bias_lab_lab FLOAT[384] b8e228cae698
|
||||
p2o.pd_op.conv2d.2.0_bias_lab FLOAT[48] 8138a593f8f2
|
||||
p2o.pd_op.conv2d.3.0_bias_lab_lab FLOAT[48] 57128b896e31
|
||||
p2o.pd_op.conv2d.4.0_bias_lab FLOAT[96] d2230ff7a27e
|
||||
p2o.pd_op.conv2d.5.0_bias_lab_lab FLOAT[96] 05b9a5f236b6
|
||||
p2o.pd_op.conv2d.6.0_bias_lab FLOAT[192] a990b3fed4dd
|
||||
p2o.pd_op.conv2d.7.0_bias_lab_lab FLOAT[192] 74df3e4f22b6
|
||||
p2o.pd_op.conv2d.8.0_bias_lab_lab FLOAT[192] 9c072f4b4032
|
||||
p2o.pd_op.conv2d.9.0_bias_lab_lab FLOAT[192] 8f6e7021fe63
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias_lab FLOAT[16] 5b3de9e3f7c2
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias_lab FLOAT[32] bb4239a962eb
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias_lab FLOAT[192] 81ac3c08eae1
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias_lab FLOAT[384] 2236a6b52e38
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias_lab FLOAT[384] 14c22d416e3b
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias_lab FLOAT[384] 4eebd04fbeb4
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias_lab FLOAT[48] aaee6f6db9c1
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias_lab FLOAT[48] dcc78f972645
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias_lab FLOAT[96] dbd763cef105
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias_lab FLOAT[96] 5849d6801824
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias_lab FLOAT[192] 01e9219938aa
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias_lab FLOAT[192] e35d55fdac89
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias_lab FLOAT[192] fd7c6cc0a8fb
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias_lab FLOAT[192] aedc2ab77e2b
|
||||
p2o.pd_op.hardsigmoid.2.0_one FLOAT[] e00e5eb94441
|
||||
se_group0_down1 FLOAT[96,96,1,1] 4c8c888b01f2
|
||||
se_group0_down2 FLOAT[96] b99146f86442
|
||||
se_group0_sizes INT64[4] 4bb249469bee
|
||||
se_group0_up1 FLOAT[384,24,1,1] 1446892243f3
|
||||
se_group0_up2 FLOAT[384] 8538540d9317
|
||||
se_group1_down1 FLOAT[24,24,1,1] 01a670ee8021
|
||||
se_group1_down2 FLOAT[24] 7f8067be0db7
|
||||
se_group1_sizes INT64[4] 5c995dc6a0ef
|
||||
se_group1_up1 FLOAT[96,6,1,1] 3e47b305535b
|
||||
se_group1_up2 FLOAT[96] ed3a93d396c3
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,676 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,1024,unk__46,unk__47] "Add.1"
|
||||
float[batch,32,unk__28,unk__29] "Add.109"
|
||||
float[batch,64,unk__28,unk__29] "Add.11"
|
||||
float[batch,32,unk__28,unk__29] "Add.119"
|
||||
float[batch,64,unk__28,unk__29] "Add.123"
|
||||
float[batch,32,unk__8,unk__9] "Add.125"
|
||||
float[batch,64,unk__46,unk__47] "Add.13"
|
||||
float[batch,32,unk__8,unk__9] "Add.135"
|
||||
float[batch,32,unk__8,unk__9] "Add.145"
|
||||
float[batch,64,unk__136,unk__137] "Add.15"
|
||||
float[batch,32,unk__8,unk__9] "Add.155"
|
||||
float[batch,64,unk__8,unk__9] "Add.159"
|
||||
float[batch,1,height,width] "Add.163"
|
||||
float[batch,1,height,width] "Add.165"
|
||||
float[batch,1,height,width] "Add.167"
|
||||
float[batch,32,unk__136,unk__137] "Add.17"
|
||||
float[batch,32,unk__136,unk__137] "Add.27"
|
||||
float[batch,1024,unk__46,unk__47] "Add.3"
|
||||
float[batch,32,unk__136,unk__137] "Add.37"
|
||||
float[batch,32,unk__136,unk__137] "Add.47"
|
||||
float[batch,256,unk__46,unk__47] "Add.5"
|
||||
float[batch,64,unk__136,unk__137] "Add.51"
|
||||
float[batch,32,unk__46,unk__47] "Add.53"
|
||||
float[batch,32,unk__46,unk__47] "Add.63"
|
||||
float[batch,256,unk__28,unk__29] "Add.7"
|
||||
float[batch,32,unk__46,unk__47] "Add.73"
|
||||
float[batch,32,unk__46,unk__47] "Add.83"
|
||||
float[batch,64,unk__46,unk__47] "Add.87"
|
||||
float[batch,32,unk__28,unk__29] "Add.89"
|
||||
float[batch,256,unk__8,unk__9] "Add.9"
|
||||
float[batch,32,unk__28,unk__29] "Add.99"
|
||||
float[batch,64,unk__0,unk__1] "Concat.1"
|
||||
float[batch,2176,unk__46,unk__47] "Concat.11"
|
||||
float[batch,3328,unk__136,unk__137] "Concat.13"
|
||||
float[batch,256,unk__8,unk__9] "Concat.15"
|
||||
float[batch,65,height,width] "Concat.17"
|
||||
float[batch,336,unk__8,unk__9] "Concat.3"
|
||||
float[batch,704,unk__28,unk__29] "Concat.5"
|
||||
float[batch,1664,unk__46,unk__47] "Concat.7"
|
||||
float[batch,2176,unk__46,unk__47] "Concat.9"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.10.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.batch_norm_.11.0"
|
||||
float[batch,128,unk__8,unk__9] "p2o.pd_op.batch_norm_.12.0"
|
||||
float[batch,128,unk__28,unk__29] "p2o.pd_op.batch_norm_.13.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.batch_norm_.14.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.batch_norm_.15.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.batch_norm_.16.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.batch_norm_.17.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.batch_norm_.18.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.batch_norm_.19.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,256,unk__28,unk__29] "p2o.pd_op.batch_norm_.20.0"
|
||||
float[batch,512,unk__28,unk__29] "p2o.pd_op.batch_norm_.21.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.batch_norm_.22.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.23.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.24.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.25.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.26.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.27.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.28.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.29.0"
|
||||
float[batch,32,unk__8,unk__9] "p2o.pd_op.batch_norm_.3.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.30.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.31.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.32.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.33.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.34.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.batch_norm_.35.0"
|
||||
float[batch,1024,unk__46,unk__47] "p2o.pd_op.batch_norm_.36.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.37.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.38.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.39.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.4.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.40.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.41.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.42.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.43.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.44.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.45.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.46.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.47.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.48.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.batch_norm_.49.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.5.0"
|
||||
float[batch,1024,unk__46,unk__47] "p2o.pd_op.batch_norm_.50.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.51.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.52.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.53.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.54.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.55.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.56.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.57.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.58.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.59.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.6.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.60.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.61.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.62.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.batch_norm_.63.0"
|
||||
float[batch,1024,unk__46,unk__47] "p2o.pd_op.batch_norm_.64.0"
|
||||
float[batch,1024,unk__136,unk__137] "p2o.pd_op.batch_norm_.65.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.66.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.67.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.68.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.69.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.7.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.70.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.71.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.72.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.73.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.74.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.75.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.76.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.77.0"
|
||||
float[batch,1024,unk__136,unk__137] "p2o.pd_op.batch_norm_.78.0"
|
||||
float[batch,2048,unk__136,unk__137] "p2o.pd_op.batch_norm_.79.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.8.0"
|
||||
float[batch,64,unk__136,unk__137] "p2o.pd_op.batch_norm_.80.0"
|
||||
float[batch,64,unk__46,unk__47] "p2o.pd_op.batch_norm_.81.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.batch_norm_.82.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.batch_norm_.83.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.batch_norm_.84.0"
|
||||
float[batch,64,unk__0,unk__1] "p2o.pd_op.batch_norm_.85.0"
|
||||
float[batch,64,height,width] "p2o.pd_op.batch_norm_.86.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.9.0"
|
||||
float[batch,256,unk__136,unk__137] "p2o.pd_op.conv2d.53.0"
|
||||
float[batch,256,unk__46,unk__47] "p2o.pd_op.conv2d.54.0"
|
||||
float[batch,256,unk__28,unk__29] "p2o.pd_op.conv2d.55.0"
|
||||
float[batch,256,unk__8,unk__9] "p2o.pd_op.conv2d.56.0"
|
||||
float[batch,64,unk__136,unk__137] "p2o.pd_op.conv2d.57.0"
|
||||
float[batch,64,unk__46,unk__47] "p2o.pd_op.conv2d.58.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.conv2d.59.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.conv2d.60.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.conv2d.61.0"
|
||||
float[batch,64,unk__46,unk__47] "p2o.pd_op.conv2d.62.0"
|
||||
float[batch,64,unk__136,unk__137] "p2o.pd_op.conv2d.63.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.conv2d.64.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.conv2d.65.0"
|
||||
float[batch,64,unk__46,unk__47] "p2o.pd_op.conv2d.66.0"
|
||||
float[batch,64,unk__136,unk__137] "p2o.pd_op.conv2d.67.0"
|
||||
float[batch,256,unk__46,unk__47] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,256,unk__28,unk__29] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,256,unk__8,unk__9] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,64,height,width] "p2o.pd_op.nearest_interp.6.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.10.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.relu.11.0"
|
||||
float[batch,128,unk__8,unk__9] "p2o.pd_op.relu.12.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.relu.13.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.relu.14.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.relu.15.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.relu.16.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.relu.17.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.relu.18.0"
|
||||
float[batch,256,unk__28,unk__29] "p2o.pd_op.relu.19.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.relu.2.0"
|
||||
float[batch,512,unk__28,unk__29] "p2o.pd_op.relu.20.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.21.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.22.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.23.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.24.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.25.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.26.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.relu.27.0"
|
||||
float[batch,1024,unk__46,unk__47] "p2o.pd_op.relu.28.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.29.0"
|
||||
float[batch,32,unk__8,unk__9] "p2o.pd_op.relu.3.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.30.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.31.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.32.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.33.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.34.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.relu.35.0"
|
||||
float[batch,1024,unk__46,unk__47] "p2o.pd_op.relu.36.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.37.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.38.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.39.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.4.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.40.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.41.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.42.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.relu.43.0"
|
||||
float[batch,1024,unk__46,unk__47] "p2o.pd_op.relu.44.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.relu.45.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.relu.46.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.relu.47.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.relu.48.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.relu.49.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.5.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.relu.50.0"
|
||||
float[batch,1024,unk__136,unk__137] "p2o.pd_op.relu.51.0"
|
||||
float[batch,2048,unk__136,unk__137] "p2o.pd_op.relu.52.0"
|
||||
float[batch,64,unk__136,unk__137] "p2o.pd_op.relu.53.0"
|
||||
float[batch,64,unk__46,unk__47] "p2o.pd_op.relu.54.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.relu.55.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.relu.56.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.relu.57.0"
|
||||
float[batch,64,unk__0,unk__1] "p2o.pd_op.relu.58.0"
|
||||
float[batch,64,height,width] "p2o.pd_op.relu.59.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.6.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.7.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.8.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.9.0"
|
||||
float[batch,1,height,width] "p2o.pd_op.sigmoid.0.0"
|
||||
float[batch,1,height,width] "p2o.pd_op.sigmoid.1.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_0.w_0", "conv2d_0.w_0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("p2o.pd_op.batch_norm_.0.0")
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <auto_pad: string = "SAME_UPPER", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_1.w_0", "conv2d_1.w_0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("p2o.pd_op.batch_norm_.1.0")
|
||||
"p2o.pd_op.batch_norm_.2.0" = Conv <auto_pad: string = "SAME_UPPER", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_2.w_0", "conv2d_2.w_0_bias")
|
||||
["Relu.2"] "p2o.pd_op.relu.2.0" = Relu ("p2o.pd_op.batch_norm_.2.0")
|
||||
["MaxPool.0"] "p2o.pd_op.pool2d.0.0" = MaxPool <auto_pad: string = "SAME_UPPER", ceil_mode: int = 0, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.pool2d.0.0", "p2o.pd_op.relu.2.0")
|
||||
"p2o.pd_op.batch_norm_.3.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Concat.1", "conv2d_3.w_0", "conv2d_3.w_0_bias")
|
||||
["Relu.3"] "p2o.pd_op.relu.3.0" = Relu ("p2o.pd_op.batch_norm_.3.0")
|
||||
"p2o.pd_op.batch_norm_.4.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.3.0", "conv2d_4.w_0", "conv2d_4.w_0_bias")
|
||||
["Relu.4"] "p2o.pd_op.relu.4.0" = Relu ("p2o.pd_op.batch_norm_.4.0")
|
||||
"p2o.pd_op.batch_norm_.5.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.4.0", "conv2d_5.w_0", "conv2d_5.w_0_bias")
|
||||
["Relu.5"] "p2o.pd_op.relu.5.0" = Relu ("p2o.pd_op.batch_norm_.5.0")
|
||||
"p2o.pd_op.batch_norm_.6.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.5.0", "conv2d_6.w_0", "conv2d_6.w_0_bias")
|
||||
["Relu.6"] "p2o.pd_op.relu.6.0" = Relu ("p2o.pd_op.batch_norm_.6.0")
|
||||
"p2o.pd_op.batch_norm_.7.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.6.0", "conv2d_7.w_0", "conv2d_7.w_0_bias")
|
||||
["Relu.7"] "p2o.pd_op.relu.7.0" = Relu ("p2o.pd_op.batch_norm_.7.0")
|
||||
"p2o.pd_op.batch_norm_.8.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.7.0", "conv2d_8.w_0", "conv2d_8.w_0_bias")
|
||||
["Relu.8"] "p2o.pd_op.relu.8.0" = Relu ("p2o.pd_op.batch_norm_.8.0")
|
||||
"p2o.pd_op.batch_norm_.9.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.8.0", "conv2d_9.w_0", "conv2d_9.w_0_bias")
|
||||
["Relu.9"] "p2o.pd_op.relu.9.0" = Relu ("p2o.pd_op.batch_norm_.9.0")
|
||||
"p2o.pd_op.batch_norm_.10.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.9.0", "conv2d_10.w_0", "conv2d_10.w_0_bias")
|
||||
["Relu.10"] "p2o.pd_op.relu.10.0" = Relu ("p2o.pd_op.batch_norm_.10.0")
|
||||
["Concat.2"] "Concat.3" = Concat <axis: int = 1> ("p2o.pd_op.relu.4.0", "p2o.pd_op.relu.5.0", "p2o.pd_op.relu.6.0", "p2o.pd_op.relu.7.0", "p2o.pd_op.relu.8.0", "p2o.pd_op.relu.9.0", "p2o.pd_op.relu.10.0")
|
||||
"p2o.pd_op.batch_norm_.11.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Concat.3", "conv2d_11.w_0", "conv2d_11.w_0_bias")
|
||||
["Relu.11"] "p2o.pd_op.relu.11.0" = Relu ("p2o.pd_op.batch_norm_.11.0")
|
||||
"p2o.pd_op.batch_norm_.12.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.11.0", "conv2d_12.w_0", "conv2d_12.w_0_bias")
|
||||
["Relu.12"] "p2o.pd_op.relu.12.0" = Relu ("p2o.pd_op.batch_norm_.12.0")
|
||||
"p2o.pd_op.batch_norm_.13.0" = Conv <dilations: ints = [1, 1], group: int = 128, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("p2o.pd_op.relu.12.0", "conv2d_13.w_0", "conv2d_13.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.14.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.13.0", "conv2d_14.w_0", "conv2d_14.w_0_bias")
|
||||
["Relu.13"] "p2o.pd_op.relu.13.0" = Relu ("p2o.pd_op.batch_norm_.14.0")
|
||||
"p2o.pd_op.batch_norm_.15.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.13.0", "conv2d_15.w_0", "conv2d_15.w_0_bias")
|
||||
["Relu.14"] "p2o.pd_op.relu.14.0" = Relu ("p2o.pd_op.batch_norm_.15.0")
|
||||
"p2o.pd_op.batch_norm_.16.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.14.0", "conv2d_16.w_0", "conv2d_16.w_0_bias")
|
||||
["Relu.15"] "p2o.pd_op.relu.15.0" = Relu ("p2o.pd_op.batch_norm_.16.0")
|
||||
"p2o.pd_op.batch_norm_.17.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.15.0", "conv2d_17.w_0", "conv2d_17.w_0_bias")
|
||||
["Relu.16"] "p2o.pd_op.relu.16.0" = Relu ("p2o.pd_op.batch_norm_.17.0")
|
||||
"p2o.pd_op.batch_norm_.18.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.16.0", "conv2d_18.w_0", "conv2d_18.w_0_bias")
|
||||
["Relu.17"] "p2o.pd_op.relu.17.0" = Relu ("p2o.pd_op.batch_norm_.18.0")
|
||||
"p2o.pd_op.batch_norm_.19.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.17.0", "conv2d_19.w_0", "conv2d_19.w_0_bias")
|
||||
["Relu.18"] "p2o.pd_op.relu.18.0" = Relu ("p2o.pd_op.batch_norm_.19.0")
|
||||
["Concat.4"] "Concat.5" = Concat <axis: int = 1> ("p2o.pd_op.batch_norm_.13.0", "p2o.pd_op.relu.13.0", "p2o.pd_op.relu.14.0", "p2o.pd_op.relu.15.0", "p2o.pd_op.relu.16.0", "p2o.pd_op.relu.17.0", "p2o.pd_op.relu.18.0")
|
||||
"p2o.pd_op.batch_norm_.20.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Concat.5", "conv2d_20.w_0", "conv2d_20.w_0_bias")
|
||||
["Relu.19"] "p2o.pd_op.relu.19.0" = Relu ("p2o.pd_op.batch_norm_.20.0")
|
||||
"p2o.pd_op.batch_norm_.21.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.19.0", "conv2d_21.w_0", "conv2d_21.w_0_bias")
|
||||
["Relu.20"] "p2o.pd_op.relu.20.0" = Relu ("p2o.pd_op.batch_norm_.21.0")
|
||||
"p2o.pd_op.batch_norm_.22.0" = Conv <dilations: ints = [1, 1], group: int = 512, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("p2o.pd_op.relu.20.0", "conv2d_22.w_0", "conv2d_22.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.23.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.22.0", "conv2d_23.w_0", "conv2d_23.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.24.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.23.0", "conv2d_24.w_0", "conv2d_24.w_0_bias")
|
||||
["Relu.21"] "p2o.pd_op.relu.21.0" = Relu ("p2o.pd_op.batch_norm_.24.0")
|
||||
"p2o.pd_op.batch_norm_.25.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.21.0", "conv2d_25.w_0", "conv2d_25.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.26.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.25.0", "conv2d_26.w_0", "conv2d_26.w_0_bias")
|
||||
["Relu.22"] "p2o.pd_op.relu.22.0" = Relu ("p2o.pd_op.batch_norm_.26.0")
|
||||
"p2o.pd_op.batch_norm_.27.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.22.0", "conv2d_27.w_0", "conv2d_27.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.28.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.27.0", "conv2d_28.w_0", "conv2d_28.w_0_bias")
|
||||
["Relu.23"] "p2o.pd_op.relu.23.0" = Relu ("p2o.pd_op.batch_norm_.28.0")
|
||||
"p2o.pd_op.batch_norm_.29.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.23.0", "conv2d_29.w_0", "conv2d_29.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.30.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.29.0", "conv2d_30.w_0", "conv2d_30.w_0_bias")
|
||||
["Relu.24"] "p2o.pd_op.relu.24.0" = Relu ("p2o.pd_op.batch_norm_.30.0")
|
||||
"p2o.pd_op.batch_norm_.31.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.24.0", "conv2d_31.w_0", "conv2d_31.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.32.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.31.0", "conv2d_32.w_0", "conv2d_32.w_0_bias")
|
||||
["Relu.25"] "p2o.pd_op.relu.25.0" = Relu ("p2o.pd_op.batch_norm_.32.0")
|
||||
"p2o.pd_op.batch_norm_.33.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.25.0", "conv2d_33.w_0", "conv2d_33.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.34.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.33.0", "conv2d_34.w_0", "conv2d_34.w_0_bias")
|
||||
["Relu.26"] "p2o.pd_op.relu.26.0" = Relu ("p2o.pd_op.batch_norm_.34.0")
|
||||
["Concat.6"] "Concat.7" = Concat <axis: int = 1> ("p2o.pd_op.batch_norm_.22.0", "p2o.pd_op.relu.21.0", "p2o.pd_op.relu.22.0", "p2o.pd_op.relu.23.0", "p2o.pd_op.relu.24.0", "p2o.pd_op.relu.25.0", "p2o.pd_op.relu.26.0")
|
||||
"p2o.pd_op.batch_norm_.35.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Concat.7", "conv2d_35.w_0", "conv2d_35.w_0_bias")
|
||||
["Relu.27"] "p2o.pd_op.relu.27.0" = Relu ("p2o.pd_op.batch_norm_.35.0")
|
||||
"p2o.pd_op.batch_norm_.36.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.27.0", "conv2d_36.w_0", "conv2d_36.w_0_bias")
|
||||
["Relu.28"] "p2o.pd_op.relu.28.0" = Relu ("p2o.pd_op.batch_norm_.36.0")
|
||||
"p2o.pd_op.batch_norm_.37.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.28.0", "conv2d_37.w_0", "conv2d_37.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.38.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.37.0", "conv2d_38.w_0", "conv2d_38.w_0_bias")
|
||||
["Relu.29"] "p2o.pd_op.relu.29.0" = Relu ("p2o.pd_op.batch_norm_.38.0")
|
||||
"p2o.pd_op.batch_norm_.39.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.29.0", "conv2d_39.w_0", "conv2d_39.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.40.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.39.0", "conv2d_40.w_0", "conv2d_40.w_0_bias")
|
||||
["Relu.30"] "p2o.pd_op.relu.30.0" = Relu ("p2o.pd_op.batch_norm_.40.0")
|
||||
"p2o.pd_op.batch_norm_.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.30.0", "conv2d_41.w_0", "conv2d_41.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.42.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.41.0", "conv2d_42.w_0", "conv2d_42.w_0_bias")
|
||||
["Relu.31"] "p2o.pd_op.relu.31.0" = Relu ("p2o.pd_op.batch_norm_.42.0")
|
||||
"p2o.pd_op.batch_norm_.43.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.31.0", "conv2d_43.w_0", "conv2d_43.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.44.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.43.0", "conv2d_44.w_0", "conv2d_44.w_0_bias")
|
||||
["Relu.32"] "p2o.pd_op.relu.32.0" = Relu ("p2o.pd_op.batch_norm_.44.0")
|
||||
"p2o.pd_op.batch_norm_.45.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.32.0", "conv2d_45.w_0", "conv2d_45.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.46.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.45.0", "conv2d_46.w_0", "conv2d_46.w_0_bias")
|
||||
["Relu.33"] "p2o.pd_op.relu.33.0" = Relu ("p2o.pd_op.batch_norm_.46.0")
|
||||
"p2o.pd_op.batch_norm_.47.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.33.0", "conv2d_47.w_0", "conv2d_47.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.48.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.47.0", "conv2d_48.w_0", "conv2d_48.w_0_bias")
|
||||
["Relu.34"] "p2o.pd_op.relu.34.0" = Relu ("p2o.pd_op.batch_norm_.48.0")
|
||||
["Concat.8"] "Concat.9" = Concat <axis: int = 1> ("p2o.pd_op.relu.28.0", "p2o.pd_op.relu.29.0", "p2o.pd_op.relu.30.0", "p2o.pd_op.relu.31.0", "p2o.pd_op.relu.32.0", "p2o.pd_op.relu.33.0", "p2o.pd_op.relu.34.0")
|
||||
"p2o.pd_op.batch_norm_.49.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Concat.9", "conv2d_49.w_0", "conv2d_49.w_0_bias")
|
||||
["Relu.35"] "p2o.pd_op.relu.35.0" = Relu ("p2o.pd_op.batch_norm_.49.0")
|
||||
"p2o.pd_op.batch_norm_.50.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.35.0", "conv2d_50.w_0", "conv2d_50.w_0_bias")
|
||||
["Relu.36"] "p2o.pd_op.relu.36.0" = Relu ("p2o.pd_op.batch_norm_.50.0")
|
||||
["Add.0"] "Add.1" = Add ("p2o.pd_op.relu.36.0", "p2o.pd_op.relu.28.0")
|
||||
"p2o.pd_op.batch_norm_.51.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.1", "conv2d_51.w_0", "conv2d_51.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.52.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.51.0", "conv2d_52.w_0", "conv2d_52.w_0_bias")
|
||||
["Relu.37"] "p2o.pd_op.relu.37.0" = Relu ("p2o.pd_op.batch_norm_.52.0")
|
||||
"p2o.pd_op.batch_norm_.53.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.37.0", "conv2d_53.w_0", "conv2d_53.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.54.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.53.0", "conv2d_54.w_0", "conv2d_54.w_0_bias")
|
||||
["Relu.38"] "p2o.pd_op.relu.38.0" = Relu ("p2o.pd_op.batch_norm_.54.0")
|
||||
"p2o.pd_op.batch_norm_.55.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.38.0", "conv2d_55.w_0", "conv2d_55.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.56.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.55.0", "conv2d_56.w_0", "conv2d_56.w_0_bias")
|
||||
["Relu.39"] "p2o.pd_op.relu.39.0" = Relu ("p2o.pd_op.batch_norm_.56.0")
|
||||
"p2o.pd_op.batch_norm_.57.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.39.0", "conv2d_57.w_0", "conv2d_57.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.58.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.57.0", "conv2d_58.w_0", "conv2d_58.w_0_bias")
|
||||
["Relu.40"] "p2o.pd_op.relu.40.0" = Relu ("p2o.pd_op.batch_norm_.58.0")
|
||||
"p2o.pd_op.batch_norm_.59.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.40.0", "conv2d_59.w_0", "conv2d_59.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.60.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.59.0", "conv2d_60.w_0", "conv2d_60.w_0_bias")
|
||||
["Relu.41"] "p2o.pd_op.relu.41.0" = Relu ("p2o.pd_op.batch_norm_.60.0")
|
||||
"p2o.pd_op.batch_norm_.61.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.41.0", "conv2d_61.w_0", "conv2d_61.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.62.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.61.0", "conv2d_62.w_0", "conv2d_62.w_0_bias")
|
||||
["Relu.42"] "p2o.pd_op.relu.42.0" = Relu ("p2o.pd_op.batch_norm_.62.0")
|
||||
["Concat.10"] "Concat.11" = Concat <axis: int = 1> ("Add.1", "p2o.pd_op.relu.37.0", "p2o.pd_op.relu.38.0", "p2o.pd_op.relu.39.0", "p2o.pd_op.relu.40.0", "p2o.pd_op.relu.41.0", "p2o.pd_op.relu.42.0")
|
||||
"p2o.pd_op.batch_norm_.63.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Concat.11", "conv2d_63.w_0", "conv2d_63.w_0_bias")
|
||||
["Relu.43"] "p2o.pd_op.relu.43.0" = Relu ("p2o.pd_op.batch_norm_.63.0")
|
||||
"p2o.pd_op.batch_norm_.64.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.43.0", "conv2d_64.w_0", "conv2d_64.w_0_bias")
|
||||
["Relu.44"] "p2o.pd_op.relu.44.0" = Relu ("p2o.pd_op.batch_norm_.64.0")
|
||||
["Add.2"] "Add.3" = Add ("p2o.pd_op.relu.44.0", "Add.1")
|
||||
"p2o.pd_op.batch_norm_.65.0" = Conv <dilations: ints = [1, 1], group: int = 1024, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.3", "conv2d_65.w_0", "conv2d_65.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.66.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.65.0", "conv2d_66.w_0", "conv2d_66.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.67.0" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.66.0", "conv2d_67.w_0", "conv2d_67.w_0_bias")
|
||||
["Relu.45"] "p2o.pd_op.relu.45.0" = Relu ("p2o.pd_op.batch_norm_.67.0")
|
||||
"p2o.pd_op.batch_norm_.68.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.45.0", "conv2d_68.w_0", "conv2d_68.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.69.0" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.68.0", "conv2d_69.w_0", "conv2d_69.w_0_bias")
|
||||
["Relu.46"] "p2o.pd_op.relu.46.0" = Relu ("p2o.pd_op.batch_norm_.69.0")
|
||||
"p2o.pd_op.batch_norm_.70.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.46.0", "conv2d_70.w_0", "conv2d_70.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.71.0" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.70.0", "conv2d_71.w_0", "conv2d_71.w_0_bias")
|
||||
["Relu.47"] "p2o.pd_op.relu.47.0" = Relu ("p2o.pd_op.batch_norm_.71.0")
|
||||
"p2o.pd_op.batch_norm_.72.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.47.0", "conv2d_72.w_0", "conv2d_72.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.73.0" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.72.0", "conv2d_73.w_0", "conv2d_73.w_0_bias")
|
||||
["Relu.48"] "p2o.pd_op.relu.48.0" = Relu ("p2o.pd_op.batch_norm_.73.0")
|
||||
"p2o.pd_op.batch_norm_.74.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.48.0", "conv2d_74.w_0", "conv2d_74.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.75.0" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.74.0", "conv2d_75.w_0", "conv2d_75.w_0_bias")
|
||||
["Relu.49"] "p2o.pd_op.relu.49.0" = Relu ("p2o.pd_op.batch_norm_.75.0")
|
||||
"p2o.pd_op.batch_norm_.76.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.49.0", "conv2d_76.w_0", "conv2d_76.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.77.0" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.76.0", "conv2d_77.w_0", "conv2d_77.w_0_bias")
|
||||
["Relu.50"] "p2o.pd_op.relu.50.0" = Relu ("p2o.pd_op.batch_norm_.77.0")
|
||||
["Concat.12"] "Concat.13" = Concat <axis: int = 1> ("p2o.pd_op.batch_norm_.65.0", "p2o.pd_op.relu.45.0", "p2o.pd_op.relu.46.0", "p2o.pd_op.relu.47.0", "p2o.pd_op.relu.48.0", "p2o.pd_op.relu.49.0", "p2o.pd_op.relu.50.0")
|
||||
"p2o.pd_op.batch_norm_.78.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Concat.13", "conv2d_78.w_0", "conv2d_78.w_0_bias")
|
||||
["Relu.51"] "p2o.pd_op.relu.51.0" = Relu ("p2o.pd_op.batch_norm_.78.0")
|
||||
"p2o.pd_op.batch_norm_.79.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.51.0", "conv2d_79.w_0", "conv2d_79.w_0_bias")
|
||||
["Relu.52"] "p2o.pd_op.relu.52.0" = Relu ("p2o.pd_op.batch_norm_.79.0")
|
||||
["Conv.80"] "p2o.pd_op.conv2d.53.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.52.0", "conv2d_92.w_0")
|
||||
["Conv.81"] "p2o.pd_op.conv2d.54.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.3", "conv2d_88.w_0")
|
||||
["Conv.82"] "p2o.pd_op.conv2d.55.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.20.0", "conv2d_84.w_0")
|
||||
["Conv.83"] "p2o.pd_op.conv2d.56.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.12.0", "conv2d_81.w_0")
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("p2o.pd_op.conv2d.53.0", "helper.constant.1", "helper.constant.0")
|
||||
["Add.4"] "Add.5" = Add ("p2o.pd_op.conv2d.54.0", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.5", "helper.constant.1", "helper.constant.0")
|
||||
["Add.6"] "Add.7" = Add ("p2o.pd_op.conv2d.55.0", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.7", "helper.constant.1", "helper.constant.0")
|
||||
["Add.8"] "Add.9" = Add ("p2o.pd_op.conv2d.56.0", "p2o.pd_op.nearest_interp.2.0")
|
||||
["Conv.84"] "p2o.pd_op.conv2d.57.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.53.0", "conv2d_93.w_0")
|
||||
["Conv.85"] "p2o.pd_op.conv2d.58.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.5", "conv2d_89.w_0")
|
||||
["Conv.86"] "p2o.pd_op.conv2d.59.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.7", "conv2d_85.w_0")
|
||||
["Conv.87"] "p2o.pd_op.conv2d.60.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.9", "conv2d_82.w_0")
|
||||
["Conv.88"] "p2o.pd_op.conv2d.61.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("p2o.pd_op.conv2d.60.0", "conv2d_86.w_0")
|
||||
["Add.10"] "Add.11" = Add ("p2o.pd_op.conv2d.59.0", "p2o.pd_op.conv2d.61.0")
|
||||
["Conv.89"] "p2o.pd_op.conv2d.62.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.11", "conv2d_90.w_0")
|
||||
["Add.12"] "Add.13" = Add ("p2o.pd_op.conv2d.58.0", "p2o.pd_op.conv2d.62.0")
|
||||
["Conv.90"] "p2o.pd_op.conv2d.63.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.13", "conv2d_94.w_0")
|
||||
["Add.14"] "Add.15" = Add ("p2o.pd_op.conv2d.57.0", "p2o.pd_op.conv2d.63.0")
|
||||
["Conv.91"] "p2o.pd_op.conv2d.64.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.60.0", "conv2d_83.w_0")
|
||||
["Conv.92"] "p2o.pd_op.conv2d.65.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.11", "conv2d_87.w_0")
|
||||
["Conv.93"] "p2o.pd_op.conv2d.66.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.13", "conv2d_91.w_0")
|
||||
["Conv.94"] "p2o.pd_op.conv2d.67.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.15", "conv2d_95.w_0")
|
||||
"Add.17" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.67.0", "conv2d_129.w_0", "p2o.pd_op.conv2d.68.0_bias")
|
||||
"Add.27" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.17", node_Conv_84_asym_w, node_Conv_84_asym_b)
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.27", node_Conv_87_asym_w, node_Conv_87_asym_b)
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.37", node_Conv_90_asym_w, node_Conv_90_asym_b)
|
||||
"p2o.pd_op.batch_norm_.80.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.47", "conv2d_130.w_0", "p2o.pd_op.conv2d.78.0_bias")
|
||||
["Relu.53"] "p2o.pd_op.relu.53.0" = Relu ("p2o.pd_op.batch_norm_.80.0")
|
||||
["Add.50"] "Add.51" = Add ("p2o.pd_op.conv2d.67.0", "p2o.pd_op.relu.53.0")
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.66.0", "conv2d_118.w_0", "p2o.pd_op.conv2d.79.0_bias")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.53", node_Conv_95_asym_w, node_Conv_95_asym_b)
|
||||
"Add.73" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.63", node_Conv_98_asym_w, node_Conv_98_asym_b)
|
||||
"Add.83" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.73", node_Conv_101_asym_w, node_Conv_101_asym_b)
|
||||
"p2o.pd_op.batch_norm_.81.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.83", "conv2d_119.w_0", "p2o.pd_op.conv2d.89.0_bias")
|
||||
["Relu.54"] "p2o.pd_op.relu.54.0" = Relu ("p2o.pd_op.batch_norm_.81.0")
|
||||
["Add.86"] "Add.87" = Add ("p2o.pd_op.conv2d.66.0", "p2o.pd_op.relu.54.0")
|
||||
"Add.89" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.65.0", "conv2d_107.w_0", "p2o.pd_op.conv2d.90.0_bias")
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.89", node_Conv_106_asym_w, node_Conv_106_asym_b)
|
||||
"Add.109" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.99", node_Conv_109_asym_w, node_Conv_109_asym_b)
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.109", node_Conv_112_asym_w, node_Conv_112_asym_b)
|
||||
"p2o.pd_op.batch_norm_.82.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.119", "conv2d_108.w_0", "p2o.pd_op.conv2d.100.0_bias")
|
||||
["Relu.55"] "p2o.pd_op.relu.55.0" = Relu ("p2o.pd_op.batch_norm_.82.0")
|
||||
["Add.122"] "Add.123" = Add ("p2o.pd_op.conv2d.65.0", "p2o.pd_op.relu.55.0")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.64.0", "conv2d_96.w_0", "p2o.pd_op.conv2d.101.0_bias")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.125", node_Conv_117_asym_w, node_Conv_117_asym_b)
|
||||
"Add.145" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.135", node_Conv_120_asym_w, node_Conv_120_asym_b)
|
||||
"Add.155" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.145", node_Conv_123_asym_w, node_Conv_123_asym_b)
|
||||
"p2o.pd_op.batch_norm_.83.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.155", "conv2d_97.w_0", "p2o.pd_op.conv2d.111.0_bias")
|
||||
["Relu.56"] "p2o.pd_op.relu.56.0" = Relu ("p2o.pd_op.batch_norm_.83.0")
|
||||
["Add.158"] "Add.159" = Add ("p2o.pd_op.conv2d.64.0", "p2o.pd_op.relu.56.0")
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.51", "helper.constant.1", "helper.constant.6")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.87", "helper.constant.1", "helper.constant.8")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.123", "helper.constant.1", "helper.constant.0")
|
||||
["Concat.14"] "Concat.15" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.159")
|
||||
"p2o.pd_op.batch_norm_.84.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.15", "conv2d_140.w_0", "conv2d_140.w_0_bias")
|
||||
["Relu.57"] "p2o.pd_op.relu.57.0" = Relu ("p2o.pd_op.batch_norm_.84.0")
|
||||
"p2o.pd_op.batch_norm_.85.0" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.57.0", "auto.cast.93", "ConvTranspose.1_bias")
|
||||
["Relu.58"] "p2o.pd_op.relu.58.0" = Relu ("p2o.pd_op.batch_norm_.85.0")
|
||||
"Add.163" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.58.0", "auto.cast.96", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] "p2o.pd_op.sigmoid.0.0" = Sigmoid ("Add.163")
|
||||
["Resize.6"] "p2o.pd_op.nearest_interp.6.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("p2o.pd_op.relu.58.0", "helper.constant.1", "helper.constant.0")
|
||||
["Concat.16"] "Concat.17" = Concat <axis: int = 1> ("p2o.pd_op.sigmoid.0.0", "p2o.pd_op.nearest_interp.6.0")
|
||||
"p2o.pd_op.batch_norm_.86.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.17", "conv2d_142.w_0", "conv2d_142.w_0_bias")
|
||||
["Relu.59"] "p2o.pd_op.relu.59.0" = Relu ("p2o.pd_op.batch_norm_.86.0")
|
||||
"Add.165" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.59.0", "conv2d_143.w_0", "p2o.pd_op.conv2d.114.0_bias")
|
||||
["Sigmoid.1"] "p2o.pd_op.sigmoid.1.0" = Sigmoid ("Add.165")
|
||||
["Add.166"] "Add.167" = Add ("p2o.pd_op.sigmoid.0.0", "p2o.pd_op.sigmoid.1.0")
|
||||
["Mul.0"] fetch_name_0 = Mul ("Add.167", "auto.cast.102")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
ConvTranspose.1_bias FLOAT[64] 4d9e09811298
|
||||
ConvTranspose.3_bias FLOAT[1] d7cf0756b564
|
||||
auto.cast.102 FLOAT[1] d99e58435243
|
||||
auto.cast.93 FLOAT[64,64,2,2] 446499e40216
|
||||
auto.cast.96 FLOAT[64,1,2,2] 6fa61becf97c
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_0.w_0 FLOAT[32,3,3,3] aed5723444c4
|
||||
conv2d_0.w_0_bias FLOAT[32] a404004a3f2d
|
||||
conv2d_1.w_0 FLOAT[16,32,2,2] 6355973c9252
|
||||
conv2d_1.w_0_bias FLOAT[16] db00ab5bf862
|
||||
conv2d_10.w_0 FLOAT[48,48,3,3] 51411ab738f8
|
||||
conv2d_10.w_0_bias FLOAT[48] 5b2cfae3b29a
|
||||
conv2d_107.w_0 FLOAT[32,64,1,1] 9f1dcbc35c35
|
||||
conv2d_108.w_0 FLOAT[64,32,1,1] f35808fcbd70
|
||||
conv2d_11.w_0 FLOAT[64,336,1,1] 83fde16b8fa0
|
||||
conv2d_11.w_0_bias FLOAT[64] c6174a10a753
|
||||
conv2d_118.w_0 FLOAT[32,64,1,1] 9f1dcbc35c35
|
||||
conv2d_119.w_0 FLOAT[64,32,1,1] eb87e44872d1
|
||||
conv2d_12.w_0 FLOAT[128,64,1,1] 5143914c85dc
|
||||
conv2d_12.w_0_bias FLOAT[128] 1a81f1411319
|
||||
conv2d_129.w_0 FLOAT[32,64,1,1] 9f1dcbc35c35
|
||||
conv2d_13.w_0 FLOAT[128,1,3,3] ae6f9b4b68af
|
||||
conv2d_13.w_0_bias FLOAT[128] 4e95a650212e
|
||||
conv2d_130.w_0 FLOAT[64,32,1,1] 1920115e5065
|
||||
conv2d_14.w_0 FLOAT[96,128,3,3] 1bbba7c1ce63
|
||||
conv2d_14.w_0_bias FLOAT[96] 51a8b2bbfe5f
|
||||
conv2d_140.w_0 FLOAT[64,256,3,3] a7695f15be7f
|
||||
conv2d_140.w_0_bias FLOAT[64] b2af6f525940
|
||||
conv2d_142.w_0 FLOAT[64,65,3,3] a31b42b48097
|
||||
conv2d_142.w_0_bias FLOAT[64] bdd4b593bf14
|
||||
conv2d_143.w_0 FLOAT[1,64,1,1] 84eabc2d820d
|
||||
conv2d_15.w_0 FLOAT[96,96,3,3] 69fd2f6e6a93
|
||||
conv2d_15.w_0_bias FLOAT[96] 2f717b0fd722
|
||||
conv2d_16.w_0 FLOAT[96,96,3,3] f732bcd2e98a
|
||||
conv2d_16.w_0_bias FLOAT[96] c6d310e2c8c4
|
||||
conv2d_17.w_0 FLOAT[96,96,3,3] 29b1c22f58f5
|
||||
conv2d_17.w_0_bias FLOAT[96] 97fe21a0d6e5
|
||||
conv2d_18.w_0 FLOAT[96,96,3,3] dd647ff9da4e
|
||||
conv2d_18.w_0_bias FLOAT[96] 6da0f2396ba0
|
||||
conv2d_19.w_0 FLOAT[96,96,3,3] 2a226b6562ff
|
||||
conv2d_19.w_0_bias FLOAT[96] afe239509ede
|
||||
conv2d_2.w_0 FLOAT[32,16,2,2] 903f80a9fc40
|
||||
conv2d_2.w_0_bias FLOAT[32] 402ab8f2e445
|
||||
conv2d_20.w_0 FLOAT[256,704,1,1] 8a6115c40624
|
||||
conv2d_20.w_0_bias FLOAT[256] 329ac342b86c
|
||||
conv2d_21.w_0 FLOAT[512,256,1,1] 895e6ce805d0
|
||||
conv2d_21.w_0_bias FLOAT[512] f014d6e30f9f
|
||||
conv2d_22.w_0 FLOAT[512,1,3,3] 122dd5643a79
|
||||
conv2d_22.w_0_bias FLOAT[512] 65118505cbb5
|
||||
conv2d_23.w_0 FLOAT[192,512,1,1] a786e504252f
|
||||
conv2d_23.w_0_bias FLOAT[192] 43bb2d7f6ea2
|
||||
conv2d_24.w_0 FLOAT[192,1,5,5] 48edfb95d59e
|
||||
conv2d_24.w_0_bias FLOAT[192] 16563dcb5fe5
|
||||
conv2d_25.w_0 FLOAT[192,192,1,1] d142c7c70596
|
||||
conv2d_25.w_0_bias FLOAT[192] 69debf8dfe33
|
||||
conv2d_26.w_0 FLOAT[192,1,5,5] 36dd82de8800
|
||||
conv2d_26.w_0_bias FLOAT[192] e5d093b7afb1
|
||||
conv2d_27.w_0 FLOAT[192,192,1,1] b137a4bcaab2
|
||||
conv2d_27.w_0_bias FLOAT[192] b585dc971a34
|
||||
conv2d_28.w_0 FLOAT[192,1,5,5] 14c15b82cb29
|
||||
conv2d_28.w_0_bias FLOAT[192] 4f74bd26f9f3
|
||||
conv2d_29.w_0 FLOAT[192,192,1,1] e25f2419665e
|
||||
conv2d_29.w_0_bias FLOAT[192] 3119aa8fd66c
|
||||
conv2d_3.w_0 FLOAT[32,64,3,3] 4933a30975d2
|
||||
conv2d_3.w_0_bias FLOAT[32] 73657ab565e9
|
||||
conv2d_30.w_0 FLOAT[192,1,5,5] 69a422cfaeb1
|
||||
conv2d_30.w_0_bias FLOAT[192] a1e447196d01
|
||||
conv2d_31.w_0 FLOAT[192,192,1,1] b144357846d3
|
||||
conv2d_31.w_0_bias FLOAT[192] f4aa4639f652
|
||||
conv2d_32.w_0 FLOAT[192,1,5,5] 1debb74f8bac
|
||||
conv2d_32.w_0_bias FLOAT[192] 83d9e916e680
|
||||
conv2d_33.w_0 FLOAT[192,192,1,1] ccdace993034
|
||||
conv2d_33.w_0_bias FLOAT[192] 641de90dc092
|
||||
conv2d_34.w_0 FLOAT[192,1,5,5] 4dc84372652b
|
||||
conv2d_34.w_0_bias FLOAT[192] e83e1469ee5b
|
||||
conv2d_35.w_0 FLOAT[512,1664,1,1] 2e1301c127b8
|
||||
conv2d_35.w_0_bias FLOAT[512] 2ee5703de97b
|
||||
conv2d_36.w_0 FLOAT[1024,512,1,1] 8f1b0de9a3b4
|
||||
conv2d_36.w_0_bias FLOAT[1024] 7a55a55e87da
|
||||
conv2d_37.w_0 FLOAT[192,1024,1,1] 00412b9131e0
|
||||
conv2d_37.w_0_bias FLOAT[192] 9689e7947a56
|
||||
conv2d_38.w_0 FLOAT[192,1,5,5] 19f1b11f6b8c
|
||||
conv2d_38.w_0_bias FLOAT[192] 0deeb692417d
|
||||
conv2d_39.w_0 FLOAT[192,192,1,1] 92026b573cfb
|
||||
conv2d_39.w_0_bias FLOAT[192] 590a0207459f
|
||||
conv2d_4.w_0 FLOAT[48,32,1,1] 3e8a7a325a2e
|
||||
conv2d_4.w_0_bias FLOAT[48] dd13b9696a60
|
||||
conv2d_40.w_0 FLOAT[192,1,5,5] cea2f56ef92e
|
||||
conv2d_40.w_0_bias FLOAT[192] 394efd933dbe
|
||||
conv2d_41.w_0 FLOAT[192,192,1,1] 083661a0266b
|
||||
conv2d_41.w_0_bias FLOAT[192] 082b3c2f5aca
|
||||
conv2d_42.w_0 FLOAT[192,1,5,5] 1915f99f1753
|
||||
conv2d_42.w_0_bias FLOAT[192] f02edaf2fa20
|
||||
conv2d_43.w_0 FLOAT[192,192,1,1] 2f561e64f6e8
|
||||
conv2d_43.w_0_bias FLOAT[192] e658c6a83708
|
||||
conv2d_44.w_0 FLOAT[192,1,5,5] 49d58ef2e1cb
|
||||
conv2d_44.w_0_bias FLOAT[192] 20b51dfab43e
|
||||
conv2d_45.w_0 FLOAT[192,192,1,1] e9f080846f2f
|
||||
conv2d_45.w_0_bias FLOAT[192] 5536be8a931c
|
||||
conv2d_46.w_0 FLOAT[192,1,5,5] 493918a100cd
|
||||
conv2d_46.w_0_bias FLOAT[192] 9950b66a4d4e
|
||||
conv2d_47.w_0 FLOAT[192,192,1,1] 701d098688e2
|
||||
conv2d_47.w_0_bias FLOAT[192] 76c58042b727
|
||||
conv2d_48.w_0 FLOAT[192,1,5,5] a48e880bce28
|
||||
conv2d_48.w_0_bias FLOAT[192] e3cfecc74be6
|
||||
conv2d_49.w_0 FLOAT[512,2176,1,1] 76108a3c4cf9
|
||||
conv2d_49.w_0_bias FLOAT[512] 3b55275475c3
|
||||
conv2d_5.w_0 FLOAT[48,48,3,3] 09008d53042f
|
||||
conv2d_5.w_0_bias FLOAT[48] 73192bdb6f5c
|
||||
conv2d_50.w_0 FLOAT[1024,512,1,1] 9ad2544c0e16
|
||||
conv2d_50.w_0_bias FLOAT[1024] 21eef1b61ac5
|
||||
conv2d_51.w_0 FLOAT[192,1024,1,1] a97e80d30eaf
|
||||
conv2d_51.w_0_bias FLOAT[192] 3402dbc6bd14
|
||||
conv2d_52.w_0 FLOAT[192,1,5,5] e9f3b5d3046b
|
||||
conv2d_52.w_0_bias FLOAT[192] 277e2bd5f1ed
|
||||
conv2d_53.w_0 FLOAT[192,192,1,1] 37629bb1cc32
|
||||
conv2d_53.w_0_bias FLOAT[192] a38560394397
|
||||
conv2d_54.w_0 FLOAT[192,1,5,5] 05fb4d6b334c
|
||||
conv2d_54.w_0_bias FLOAT[192] f3e5bf9d19e7
|
||||
conv2d_55.w_0 FLOAT[192,192,1,1] d6bf8a539a0b
|
||||
conv2d_55.w_0_bias FLOAT[192] a7f5411d539d
|
||||
conv2d_56.w_0 FLOAT[192,1,5,5] facfc96767e7
|
||||
conv2d_56.w_0_bias FLOAT[192] a04889ef0afd
|
||||
conv2d_57.w_0 FLOAT[192,192,1,1] 894777b46366
|
||||
conv2d_57.w_0_bias FLOAT[192] f0c285f1eae6
|
||||
conv2d_58.w_0 FLOAT[192,1,5,5] d5e48fbf3ee2
|
||||
conv2d_58.w_0_bias FLOAT[192] 9be347e95bb9
|
||||
conv2d_59.w_0 FLOAT[192,192,1,1] 700d4c63ea85
|
||||
conv2d_59.w_0_bias FLOAT[192] d72df89f574f
|
||||
conv2d_6.w_0 FLOAT[48,48,3,3] 308c19bfcf5e
|
||||
conv2d_6.w_0_bias FLOAT[48] 635143bd4452
|
||||
conv2d_60.w_0 FLOAT[192,1,5,5] a741705e9788
|
||||
conv2d_60.w_0_bias FLOAT[192] 7ebde9240317
|
||||
conv2d_61.w_0 FLOAT[192,192,1,1] 6b46473b3149
|
||||
conv2d_61.w_0_bias FLOAT[192] 736f11c9d244
|
||||
conv2d_62.w_0 FLOAT[192,1,5,5] c5b6bc42b776
|
||||
conv2d_62.w_0_bias FLOAT[192] 4cc54272c636
|
||||
conv2d_63.w_0 FLOAT[512,2176,1,1] 5608efb9c257
|
||||
conv2d_63.w_0_bias FLOAT[512] 47cbb56a497a
|
||||
conv2d_64.w_0 FLOAT[1024,512,1,1] 6beb7705f174
|
||||
conv2d_64.w_0_bias FLOAT[1024] 952f3e5be0c1
|
||||
conv2d_65.w_0 FLOAT[1024,1,3,3] 543854fbe506
|
||||
conv2d_65.w_0_bias FLOAT[1024] da89e73edd61
|
||||
conv2d_66.w_0 FLOAT[384,1024,1,1] ab336657501a
|
||||
conv2d_66.w_0_bias FLOAT[384] 80a676c7aab9
|
||||
conv2d_67.w_0 FLOAT[384,1,5,5] 3474a1022fdd
|
||||
conv2d_67.w_0_bias FLOAT[384] 7ee0f9d35974
|
||||
conv2d_68.w_0 FLOAT[384,384,1,1] e58fce181f95
|
||||
conv2d_68.w_0_bias FLOAT[384] 362bbfa580cd
|
||||
conv2d_69.w_0 FLOAT[384,1,5,5] 27dda3b3d0d7
|
||||
conv2d_69.w_0_bias FLOAT[384] f6a00eaaf5e8
|
||||
conv2d_7.w_0 FLOAT[48,48,3,3] adc1b4529bcc
|
||||
conv2d_7.w_0_bias FLOAT[48] a307c3d1cb1f
|
||||
conv2d_70.w_0 FLOAT[384,384,1,1] df4e87969670
|
||||
conv2d_70.w_0_bias FLOAT[384] 1bd79ee4c9e6
|
||||
conv2d_71.w_0 FLOAT[384,1,5,5] 1a44da8e03a7
|
||||
conv2d_71.w_0_bias FLOAT[384] 361d8bca6885
|
||||
conv2d_72.w_0 FLOAT[384,384,1,1] a6af4880b6db
|
||||
conv2d_72.w_0_bias FLOAT[384] 9ef132ad1dd0
|
||||
conv2d_73.w_0 FLOAT[384,1,5,5] 0feedf067bd6
|
||||
conv2d_73.w_0_bias FLOAT[384] ff0cdd3fe0b2
|
||||
conv2d_74.w_0 FLOAT[384,384,1,1] 6c644edd904d
|
||||
conv2d_74.w_0_bias FLOAT[384] 1f54b47144f7
|
||||
conv2d_75.w_0 FLOAT[384,1,5,5] 55c105e10e08
|
||||
conv2d_75.w_0_bias FLOAT[384] 1d631fb327b4
|
||||
conv2d_76.w_0 FLOAT[384,384,1,1] 1a1fc3ccdd2c
|
||||
conv2d_76.w_0_bias FLOAT[384] 90bc957eee42
|
||||
conv2d_77.w_0 FLOAT[384,1,5,5] 84e9bd430b83
|
||||
conv2d_77.w_0_bias FLOAT[384] 440d8a3dcecd
|
||||
conv2d_78.w_0 FLOAT[1024,3328,1,1] 113ea9eda44a
|
||||
conv2d_78.w_0_bias FLOAT[1024] 8c39729cf00c
|
||||
conv2d_79.w_0 FLOAT[2048,1024,1,1] 78b6983c4973
|
||||
conv2d_79.w_0_bias FLOAT[2048] dfd4aff6cd80
|
||||
conv2d_8.w_0 FLOAT[48,48,3,3] 6fcce5235f78
|
||||
conv2d_8.w_0_bias FLOAT[48] b8b149cb92e1
|
||||
conv2d_81.w_0 FLOAT[256,128,1,1] 5294b218dde6
|
||||
conv2d_82.w_0 FLOAT[64,256,9,9] 860a2c2f44ed
|
||||
conv2d_83.w_0 FLOAT[64,64,9,9] 073941384d9c
|
||||
conv2d_84.w_0 FLOAT[256,512,1,1] 355cf6d6aaf2
|
||||
conv2d_85.w_0 FLOAT[64,256,9,9] 6ab5aa7a3aaa
|
||||
conv2d_86.w_0 FLOAT[64,64,3,3] 7ec046584c86
|
||||
conv2d_87.w_0 FLOAT[64,64,9,9] 0e915f8b2a44
|
||||
conv2d_88.w_0 FLOAT[256,1024,1,1] 922be789a59b
|
||||
conv2d_89.w_0 FLOAT[64,256,9,9] 41cdf13c5867
|
||||
conv2d_9.w_0 FLOAT[48,48,3,3] ba744539217a
|
||||
conv2d_9.w_0_bias FLOAT[48] 5e225c1cd595
|
||||
conv2d_90.w_0 FLOAT[64,64,3,3] 8db0d95502bb
|
||||
conv2d_91.w_0 FLOAT[64,64,9,9] 6d6102e52c48
|
||||
conv2d_92.w_0 FLOAT[256,2048,1,1] fd9fe5ec3288
|
||||
conv2d_93.w_0 FLOAT[64,256,9,9] d6c8040de5a2
|
||||
conv2d_94.w_0 FLOAT[64,64,3,3] 7c6b6a1a0bca
|
||||
conv2d_95.w_0 FLOAT[64,64,9,9] 6db06f7cf7c6
|
||||
conv2d_96.w_0 FLOAT[32,64,1,1] 9f1dcbc35c35
|
||||
conv2d_97.w_0 FLOAT[64,32,1,1] b64d8ab1f062
|
||||
helper.constant.0 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.1 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.6 FLOAT[4] cf5451a623be
|
||||
helper.constant.8 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
node_Conv_101_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_101_asym_w FLOAT[32,32,3,3] 1c0273095382
|
||||
node_Conv_106_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_106_asym_w FLOAT[32,32,7,7] ba0ee4b797b9
|
||||
node_Conv_109_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_109_asym_w FLOAT[32,32,5,5] f627ca4c2c32
|
||||
node_Conv_112_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_112_asym_w FLOAT[32,32,3,3] 1c0273095382
|
||||
node_Conv_117_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_117_asym_w FLOAT[32,32,7,7] a5e56dbbfbc8
|
||||
node_Conv_120_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_120_asym_w FLOAT[32,32,5,5] f627ca4c2c32
|
||||
node_Conv_123_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_123_asym_w FLOAT[32,32,3,3] 1c0273095382
|
||||
node_Conv_84_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_84_asym_w FLOAT[32,32,7,7] ba0ee4b797b9
|
||||
node_Conv_87_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_87_asym_w FLOAT[32,32,5,5] f627ca4c2c32
|
||||
node_Conv_90_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_90_asym_w FLOAT[32,32,3,3] 1c0273095382
|
||||
node_Conv_95_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_95_asym_w FLOAT[32,32,7,7] ba0ee4b797b9
|
||||
node_Conv_98_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_98_asym_w FLOAT[32,32,5,5] f627ca4c2c32
|
||||
p2o.pd_op.conv2d.100.0_bias FLOAT[64] 936316c173ad
|
||||
p2o.pd_op.conv2d.101.0_bias FLOAT[32] 38723a2e5e8a
|
||||
p2o.pd_op.conv2d.111.0_bias FLOAT[64] f0eba8610837
|
||||
p2o.pd_op.conv2d.114.0_bias FLOAT[1] d894932b695a
|
||||
p2o.pd_op.conv2d.68.0_bias FLOAT[32] 38723a2e5e8a
|
||||
p2o.pd_op.conv2d.78.0_bias FLOAT[64] 78bb18b3d82f
|
||||
p2o.pd_op.conv2d.79.0_bias FLOAT[32] 38723a2e5e8a
|
||||
p2o.pd_op.conv2d.89.0_bias FLOAT[64] 4761b58748c8
|
||||
p2o.pd_op.conv2d.90.0_bias FLOAT[32] 38723a2e5e8a
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,468 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,192,unk__22,unk__23] "Add.105"
|
||||
float[batch,192,unk__22,unk__23] "Add.111"
|
||||
float[batch,192,unk__42,unk__43] "Add.117"
|
||||
float[batch,48,1,1] "Add.119"
|
||||
float[batch,192,1,1] "Add.121"
|
||||
float[batch,384,unk__42,unk__43] "Add.125"
|
||||
float[batch,384,unk__42,unk__43] "Add.131"
|
||||
float[batch,384,unk__42,unk__43] "Add.133"
|
||||
float[batch,96,1,1] "Add.135"
|
||||
float[batch,384,1,1] "Add.137"
|
||||
float[batch,384,unk__42,unk__43] "Add.141"
|
||||
float[batch,384,unk__42,unk__43] "Add.147"
|
||||
float[batch,32,unk__6,unk__7] "Add.15"
|
||||
float[batch,384,unk__42,unk__43] "Add.153"
|
||||
float[batch,384,unk__42,unk__43] "Add.159"
|
||||
float[batch,384,unk__42,unk__43] "Add.165"
|
||||
float[batch,96,unk__42,unk__43] "Add.181"
|
||||
float[batch,96,unk__22,unk__23] "Add.187"
|
||||
float[batch,48,unk__6,unk__7] "Add.19"
|
||||
float[batch,96,unk__14,unk__15] "Add.193"
|
||||
float[batch,96,unk__6,unk__7] "Add.199"
|
||||
float[batch,96,unk__22,unk__23] "Add.201"
|
||||
float[batch,96,unk__14,unk__15] "Add.203"
|
||||
float[batch,96,unk__6,unk__7] "Add.205"
|
||||
float[batch,24,unk__42,unk__43] "Add.211"
|
||||
float[batch,24,unk__22,unk__23] "Add.217"
|
||||
float[batch,24,unk__14,unk__15] "Add.223"
|
||||
float[batch,24,unk__6,unk__7] "Add.229"
|
||||
float[batch,1,height,width] "Add.233"
|
||||
float[batch,48,unk__6,unk__7] "Add.25"
|
||||
float[batch,16,unk__0,unk__1] "Add.3"
|
||||
float[batch,48,unk__6,unk__7] "Add.31"
|
||||
float[batch,48,unk__14,unk__15] "Add.37"
|
||||
float[batch,96,unk__14,unk__15] "Add.41"
|
||||
float[batch,96,unk__14,unk__15] "Add.47"
|
||||
float[batch,96,unk__14,unk__15] "Add.53"
|
||||
float[batch,96,unk__22,unk__23] "Add.59"
|
||||
float[batch,192,unk__22,unk__23] "Add.63"
|
||||
float[batch,192,unk__22,unk__23] "Add.69"
|
||||
float[batch,192,unk__22,unk__23] "Add.75"
|
||||
float[batch,192,unk__22,unk__23] "Add.81"
|
||||
float[batch,192,unk__22,unk__23] "Add.87"
|
||||
float[batch,32,unk__0,unk__1] "Add.9"
|
||||
float[batch,192,unk__22,unk__23] "Add.93"
|
||||
float[batch,192,unk__22,unk__23] "Add.99"
|
||||
float[batch,96,unk__6,unk__7] "Concat.1"
|
||||
float[batch,192,unk__42,unk__43] "Mul.77"
|
||||
float[batch,384,unk__42,unk__43] "Mul.85"
|
||||
float[batch,384,unk__42,unk__43] "Mul.87"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,96,unk__42,unk__43] "p2o.pd_op.conv2d.23.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.conv2d.26.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.conv2d.29.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.conv2d.32.0"
|
||||
float[batch,24,unk__42,unk__43] "p2o.pd_op.conv2d.35.0"
|
||||
float[batch,24,unk__22,unk__23] "p2o.pd_op.conv2d.38.0"
|
||||
float[batch,24,unk__14,unk__15] "p2o.pd_op.conv2d.41.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.conv2d.44.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.hardswish.0.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.hardswish.1.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.10.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.11.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.12.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.13.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.14.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.15.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.16.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.17.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.18.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.19.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.2.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.20.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.21.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.22.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.23.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.3.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.4.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.5.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.6.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.7.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.8.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.9.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.pool2d.1.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.2.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.3.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.4.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.5.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.6.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.7.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.8.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.9.0"
|
||||
float[batch,48,1,1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.relu.10.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.relu.11.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.2.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.3.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.4.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.5.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.6.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.7.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.8.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.9.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,96,1,1] se_group0_down
|
||||
float[batch,384,1,1] se_group0_gates
|
||||
float[batch,384,1,1] se_group0_pooled
|
||||
float[batch,96,1,1] se_group0_relu
|
||||
float[batch,384,1,1] se_group0_up
|
||||
float[batch,24,1,1] se_group1_down
|
||||
float[batch,96,1,1] se_group1_gates
|
||||
float[batch,96,1,1] se_group1_pooled
|
||||
float[batch,24,1,1] se_group1_relu
|
||||
float[batch,96,1,1] se_group1_up
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,16,unk__0,unk__1] val_0
|
||||
float[batch,32,unk__0,unk__1] val_1
|
||||
float[batch,96,unk__14,unk__15] val_10
|
||||
float[batch,96,unk__14,unk__15] val_11
|
||||
float[batch,96,unk__14,unk__15] val_12
|
||||
float[batch,192,unk__22,unk__23] val_13
|
||||
float[batch,192,unk__22,unk__23] val_14
|
||||
float[batch,192,unk__22,unk__23] val_15
|
||||
float[batch,192,unk__22,unk__23] val_16
|
||||
float[batch,192,unk__22,unk__23] val_17
|
||||
float[batch,192,unk__22,unk__23] val_18
|
||||
float[batch,192,unk__22,unk__23] val_19
|
||||
float[batch,32,unk__0,unk__1] val_2
|
||||
float[batch,192,unk__22,unk__23] val_20
|
||||
float[batch,192,unk__22,unk__23] val_21
|
||||
float[batch,192,unk__22,unk__23] val_22
|
||||
float[batch,192,unk__22,unk__23] val_23
|
||||
float[batch,192,unk__22,unk__23] val_24
|
||||
float[batch,192,unk__22,unk__23] val_25
|
||||
float[batch,192,unk__22,unk__23] val_26
|
||||
float[batch,384,unk__42,unk__43] val_27
|
||||
float[batch,384,unk__42,unk__43] val_28
|
||||
float[batch,384,unk__42,unk__43] val_29
|
||||
float[batch,48,unk__6,unk__7] val_3
|
||||
float[batch,384,unk__42,unk__43] val_30
|
||||
float[batch,384,unk__42,unk__43] val_31
|
||||
float[batch,384,unk__42,unk__43] val_32
|
||||
float[batch,384,unk__42,unk__43] val_33
|
||||
float[batch,384,unk__42,unk__43] val_34
|
||||
float[batch,384,unk__42,unk__43] val_35
|
||||
float[batch,384,unk__42,unk__43] val_36
|
||||
float[batch,96,1,1] val_37
|
||||
float[batch,96,1,1] val_38
|
||||
float[batch,96,1,1] val_39
|
||||
float[batch,48,unk__6,unk__7] val_4
|
||||
float[batch,96,1,1] val_40
|
||||
float[batch,24,1,1] val_41
|
||||
float[batch,24,1,1] val_42
|
||||
float[batch,24,1,1] val_43
|
||||
float[batch,24,1,1] val_44
|
||||
float[batch,48,unk__6,unk__7] val_5
|
||||
float[batch,48,unk__6,unk__7] val_6
|
||||
float[batch,48,unk__6,unk__7] val_7
|
||||
float[batch,96,unk__14,unk__15] val_8
|
||||
float[batch,96,unk__14,unk__15] val_9
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_0.w_0", "conv2d_0.w_0_bias")
|
||||
"Add.3" = Conv <dilations: ints = [1, 1], group: int = 16, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.0.0", "conv2d_161.w_0_lab", "p2o.pd_op.depthwise_conv2d.0.0_bias_lab")
|
||||
val_0 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.3")
|
||||
"p2o.pd_op.hardswish.0.0" = Mul ("Add.3", val_0)
|
||||
"Add.9" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.0.0", "conv2d_162.w_0_lab_lab", "p2o.pd_op.conv2d.1.0_bias_lab_lab")
|
||||
val_1 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.9")
|
||||
"p2o.pd_op.hardswish.1.0" = Mul ("Add.9", val_1)
|
||||
val_2 = Add ("p2o.pd_op.hardswish.1.0", "conv2d_163.w_0_lab_laboffset")
|
||||
"Add.15" = Conv <dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_2, "conv2d_163.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.1.0_bias_lab")
|
||||
"Add.19" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.15", "conv2d_164.w_0_lab", "p2o.pd_op.conv2d.2.0_bias_lab")
|
||||
val_3 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.19")
|
||||
"p2o.pd_op.hardswish.2.0" = Mul ("Add.19", val_3)
|
||||
val_4 = Add ("p2o.pd_op.hardswish.2.0", "conv2d_165.w_0_lab_laboffset")
|
||||
"Add.25" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_4, "conv2d_165.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.2.0_bias_lab")
|
||||
val_5 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.25")
|
||||
"p2o.pd_op.hardswish.3.0" = Mul ("Add.25", val_5)
|
||||
"Add.31" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.3.0", "conv2d_166.w_0_lab_lab", "p2o.pd_op.conv2d.3.0_bias_lab_lab")
|
||||
val_6 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.31")
|
||||
"p2o.pd_op.hardswish.4.0" = Mul ("Add.31", val_6)
|
||||
val_7 = Add ("p2o.pd_op.hardswish.4.0", "conv2d_167.w_0_lab_laboffset")
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_7, "conv2d_167.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.3.0_bias_lab")
|
||||
"Add.41" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.37", "conv2d_168.w_0_lab", "p2o.pd_op.conv2d.4.0_bias_lab")
|
||||
val_8 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.41")
|
||||
"p2o.pd_op.hardswish.5.0" = Mul ("Add.41", val_8)
|
||||
val_9 = Add ("p2o.pd_op.hardswish.5.0", "conv2d_169.w_0_lab_laboffset")
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_9, "conv2d_169.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.4.0_bias_lab")
|
||||
val_10 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.47")
|
||||
"p2o.pd_op.hardswish.6.0" = Mul ("Add.47", val_10)
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.6.0", "conv2d_170.w_0_lab_lab", "p2o.pd_op.conv2d.5.0_bias_lab_lab")
|
||||
val_11 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.53")
|
||||
"p2o.pd_op.hardswish.7.0" = Mul ("Add.53", val_11)
|
||||
val_12 = Add ("p2o.pd_op.hardswish.7.0", "conv2d_171.w_0_lab_laboffset")
|
||||
"Add.59" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_12, "conv2d_171.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.5.0_bias_lab")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.59", "conv2d_172.w_0_lab", "p2o.pd_op.conv2d.6.0_bias_lab")
|
||||
val_13 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.63")
|
||||
"p2o.pd_op.hardswish.8.0" = Mul ("Add.63", val_13)
|
||||
val_14 = Add ("p2o.pd_op.hardswish.8.0", "conv2d_173.w_0_lab_laboffset")
|
||||
"Add.69" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_14, "conv2d_173.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.6.0_bias_lab")
|
||||
val_15 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.69")
|
||||
"p2o.pd_op.hardswish.9.0" = Mul ("Add.69", val_15)
|
||||
"Add.75" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.9.0", "conv2d_174.w_0_lab_lab", "p2o.pd_op.conv2d.7.0_bias_lab_lab")
|
||||
val_16 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.75")
|
||||
"p2o.pd_op.hardswish.10.0" = Mul ("Add.75", val_16)
|
||||
val_17 = Add ("p2o.pd_op.hardswish.10.0", "conv2d_175.w_0_lab_laboffset")
|
||||
"Add.81" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_17, "conv2d_175.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.7.0_bias_lab")
|
||||
val_18 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.81")
|
||||
"p2o.pd_op.hardswish.11.0" = Mul ("Add.81", val_18)
|
||||
"Add.87" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.11.0", "conv2d_176.w_0_lab_lab", "p2o.pd_op.conv2d.8.0_bias_lab_lab")
|
||||
val_19 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.87")
|
||||
"p2o.pd_op.hardswish.12.0" = Mul ("Add.87", val_19)
|
||||
val_20 = Add ("p2o.pd_op.hardswish.12.0", "conv2d_177.w_0_lab_laboffset")
|
||||
"Add.93" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_20, "conv2d_177.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.8.0_bias_lab")
|
||||
val_21 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.93")
|
||||
"p2o.pd_op.hardswish.13.0" = Mul ("Add.93", val_21)
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.13.0", "conv2d_178.w_0_lab_lab", "p2o.pd_op.conv2d.9.0_bias_lab_lab")
|
||||
val_22 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.99")
|
||||
"p2o.pd_op.hardswish.14.0" = Mul ("Add.99", val_22)
|
||||
val_23 = Add ("p2o.pd_op.hardswish.14.0", "conv2d_179.w_0_lab_laboffset")
|
||||
"Add.105" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_23, "conv2d_179.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.9.0_bias_lab")
|
||||
val_24 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.105")
|
||||
"p2o.pd_op.hardswish.15.0" = Mul ("Add.105", val_24)
|
||||
"Add.111" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.15.0", "conv2d_180.w_0_lab_lab", "p2o.pd_op.conv2d.10.0_bias_lab_lab")
|
||||
val_25 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.111")
|
||||
"p2o.pd_op.hardswish.16.0" = Mul ("Add.111", val_25)
|
||||
val_26 = Add ("p2o.pd_op.hardswish.16.0", "conv2d_181.w_0_lab_laboffset")
|
||||
"Add.117" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [2, 2]> (val_26, "conv2d_181.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.10.0_bias_lab")
|
||||
["GlobalAveragePool.0"] "p2o.pd_op.pool2d.0.0" = GlobalAveragePool ("Add.117")
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.0.0", "conv2d_96.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.119")
|
||||
"Add.121" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_97.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.121")
|
||||
["Mul.76"] "Mul.77" = Mul ("Add.117", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.77", "conv2d_182.w_0_lab", "p2o.pd_op.conv2d.13.0_bias_lab")
|
||||
val_27 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.125")
|
||||
"p2o.pd_op.hardswish.17.0" = Mul ("Add.125", val_27)
|
||||
val_28 = Add ("p2o.pd_op.hardswish.17.0", "conv2d_183.w_0_lab_laboffset")
|
||||
"Add.131" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_28, "conv2d_183.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.11.0_bias_lab")
|
||||
val_29 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.131")
|
||||
"p2o.pd_op.hardswish.18.0" = Mul ("Add.131", val_29)
|
||||
["Mul.84"] "Mul.85" = Mul ("learnable_affine_block_45.w_0", "p2o.pd_op.hardswish.18.0")
|
||||
["Add.132"] "Add.133" = Add ("Mul.85", "learnable_affine_block_45.w_1")
|
||||
["GlobalAveragePool.1"] "p2o.pd_op.pool2d.1.0" = GlobalAveragePool ("Add.133")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.1.0", "conv2d_107.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.135")
|
||||
"Add.137" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_108.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.137")
|
||||
["Mul.86"] "Mul.87" = Mul ("Add.133", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.141" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.87", "conv2d_184.w_0_lab", "p2o.pd_op.conv2d.16.0_bias_lab")
|
||||
val_30 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.141")
|
||||
"p2o.pd_op.hardswish.19.0" = Mul ("Add.141", val_30)
|
||||
val_31 = Add ("p2o.pd_op.hardswish.19.0", "conv2d_185.w_0_lab_laboffset")
|
||||
"Add.147" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_31, "conv2d_185.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.12.0_bias_lab")
|
||||
val_32 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.147")
|
||||
"p2o.pd_op.hardswish.20.0" = Mul ("Add.147", val_32)
|
||||
"Add.153" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.20.0", "conv2d_186.w_0_lab_lab", "p2o.pd_op.conv2d.17.0_bias_lab_lab")
|
||||
val_33 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.153")
|
||||
"p2o.pd_op.hardswish.21.0" = Mul ("Add.153", val_33)
|
||||
val_34 = Add ("p2o.pd_op.hardswish.21.0", "conv2d_187.w_0_lab_laboffset")
|
||||
"Add.159" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_34, "conv2d_187.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.13.0_bias_lab")
|
||||
val_35 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.159")
|
||||
"p2o.pd_op.hardswish.22.0" = Mul ("Add.159", val_35)
|
||||
"Add.165" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.22.0", "conv2d_188.w_0_lab_lab", "p2o.pd_op.conv2d.18.0_bias_lab_lab")
|
||||
val_36 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.165")
|
||||
"p2o.pd_op.hardswish.23.0" = Mul ("Add.165", val_36)
|
||||
"p2o.pd_op.conv2d.23.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.23.0", "Conv.37_folded_w_lab", "Conv.37_folded_b_lab")
|
||||
["GlobalAveragePool.2"] "p2o.pd_op.pool2d.2.0" = GlobalAveragePool ("p2o.pd_op.conv2d.23.0")
|
||||
"p2o.pd_op.conv2d.26.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_26, "Conv.40_folded_w_labscale", "Conv.40_folded_b")
|
||||
["GlobalAveragePool.3"] "p2o.pd_op.pool2d.3.0" = GlobalAveragePool ("p2o.pd_op.conv2d.26.0")
|
||||
"p2o.pd_op.conv2d.29.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_12, "Conv.43_folded_w_labscale", "Conv.43_folded_b")
|
||||
["GlobalAveragePool.4"] "p2o.pd_op.pool2d.4.0" = GlobalAveragePool ("p2o.pd_op.conv2d.29.0")
|
||||
"p2o.pd_op.conv2d.32.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_7, "Conv.46_folded_w_labscale", "Conv.46_folded_b")
|
||||
["GlobalAveragePool.5"] "p2o.pd_op.pool2d.5.0" = GlobalAveragePool ("p2o.pd_op.conv2d.32.0")
|
||||
se_group0_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.2.0", "p2o.pd_op.pool2d.3.0", "p2o.pd_op.pool2d.4.0", "p2o.pd_op.pool2d.5.0")
|
||||
se_group0_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_pooled, se_group0_down1, se_group0_down2)
|
||||
se_group0_relu = Relu (se_group0_down)
|
||||
se_group0_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_relu, se_group0_up1, se_group0_up2)
|
||||
se_group0_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group0_up)
|
||||
"se_group0_p2o.pd_op.hardsigmoid.2.0", "se_group0_p2o.pd_op.hardsigmoid.3.0", "se_group0_p2o.pd_op.hardsigmoid.4.0", "se_group0_p2o.pd_op.hardsigmoid.5.0" = Split <axis: int = 1> (se_group0_gates, se_group0_sizes)
|
||||
val_37 = Add ("se_group0_p2o.pd_op.hardsigmoid.2.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.181" = Mul ("p2o.pd_op.conv2d.23.0", val_37)
|
||||
val_38 = Add ("se_group0_p2o.pd_op.hardsigmoid.3.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.187" = Mul ("p2o.pd_op.conv2d.26.0", val_38)
|
||||
val_39 = Add ("se_group0_p2o.pd_op.hardsigmoid.4.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.193" = Mul ("p2o.pd_op.conv2d.29.0", val_39)
|
||||
val_40 = Add ("se_group0_p2o.pd_op.hardsigmoid.5.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.199" = Mul ("p2o.pd_op.conv2d.32.0", val_40)
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.181", "helper.constant.1", "helper.constant.0")
|
||||
["Add.200"] "Add.201" = Add ("Add.187", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.201", "helper.constant.1", "helper.constant.0")
|
||||
["Add.202"] "Add.203" = Add ("Add.193", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.203", "helper.constant.1", "helper.constant.0")
|
||||
["Add.204"] "Add.205" = Add ("Add.199", "p2o.pd_op.nearest_interp.2.0")
|
||||
["Conv.49"] "p2o.pd_op.conv2d.35.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.181", "conv2d_156.w_0")
|
||||
["GlobalAveragePool.6"] "p2o.pd_op.pool2d.6.0" = GlobalAveragePool ("p2o.pd_op.conv2d.35.0")
|
||||
["Conv.52"] "p2o.pd_op.conv2d.38.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.201", "conv2d_150.w_0")
|
||||
["GlobalAveragePool.7"] "p2o.pd_op.pool2d.7.0" = GlobalAveragePool ("p2o.pd_op.conv2d.38.0")
|
||||
["Conv.55"] "p2o.pd_op.conv2d.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.203", "conv2d_144.w_0")
|
||||
["GlobalAveragePool.8"] "p2o.pd_op.pool2d.8.0" = GlobalAveragePool ("p2o.pd_op.conv2d.41.0")
|
||||
["Conv.58"] "p2o.pd_op.conv2d.44.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.205", "conv2d_138.w_0")
|
||||
["GlobalAveragePool.9"] "p2o.pd_op.pool2d.9.0" = GlobalAveragePool ("p2o.pd_op.conv2d.44.0")
|
||||
se_group1_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.6.0", "p2o.pd_op.pool2d.7.0", "p2o.pd_op.pool2d.8.0", "p2o.pd_op.pool2d.9.0")
|
||||
se_group1_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_pooled, se_group1_down1, se_group1_down2)
|
||||
se_group1_relu = Relu (se_group1_down)
|
||||
se_group1_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_relu, se_group1_up1, se_group1_up2)
|
||||
se_group1_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group1_up)
|
||||
"se_group1_p2o.pd_op.hardsigmoid.6.0", "se_group1_p2o.pd_op.hardsigmoid.7.0", "se_group1_p2o.pd_op.hardsigmoid.8.0", "se_group1_p2o.pd_op.hardsigmoid.9.0" = Split <axis: int = 1> (se_group1_gates, se_group1_sizes)
|
||||
val_41 = Add ("se_group1_p2o.pd_op.hardsigmoid.6.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.211" = Mul ("p2o.pd_op.conv2d.35.0", val_41)
|
||||
val_42 = Add ("se_group1_p2o.pd_op.hardsigmoid.7.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.217" = Mul ("p2o.pd_op.conv2d.38.0", val_42)
|
||||
val_43 = Add ("se_group1_p2o.pd_op.hardsigmoid.8.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.223" = Mul ("p2o.pd_op.conv2d.41.0", val_43)
|
||||
val_44 = Add ("se_group1_p2o.pd_op.hardsigmoid.9.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.229" = Mul ("p2o.pd_op.conv2d.44.0", val_44)
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.211", "helper.constant.1", "helper.constant.6")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.217", "helper.constant.1", "helper.constant.8")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.223", "helper.constant.1", "helper.constant.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.229")
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.1", "conv2d_159.w_0", "conv2d_159.w_0_bias")
|
||||
["Relu.10"] "p2o.pd_op.relu.10.0" = Relu ("p2o.pd_op.batch_norm_.1.0")
|
||||
"p2o.pd_op.batch_norm_.2.0" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.10.0", "auto.cast.57", "ConvTranspose.1_bias")
|
||||
["Relu.11"] "p2o.pd_op.relu.11.0" = Relu ("p2o.pd_op.batch_norm_.2.0")
|
||||
"Add.233" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.11.0", "auto.cast.60", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] fetch_name_0 = Sigmoid ("Add.233")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
Conv.37_folded_b_lab FLOAT[96] 0d571951a1e0
|
||||
Conv.37_folded_w_lab FLOAT[96,384,1,1] 1d0305563ea7
|
||||
Conv.40_folded_b FLOAT[96] dcfdd514912d
|
||||
Conv.40_folded_w_labscale FLOAT[96,192,1,1] bacc8274202e
|
||||
Conv.43_folded_b FLOAT[96] ee902cf71aad
|
||||
Conv.43_folded_w_labscale FLOAT[96,96,1,1] b17e08485dc5
|
||||
Conv.46_folded_b FLOAT[96] 6541e510a35d
|
||||
Conv.46_folded_w_labscale FLOAT[96,48,1,1] 9423b2c0951a
|
||||
ConvTranspose.1_bias FLOAT[24] 64cabf62980d
|
||||
ConvTranspose.3_bias FLOAT[1] 55c86fee1edb
|
||||
auto.cast.57 FLOAT[24,24,2,2] 1dc864bec64f
|
||||
auto.cast.60 FLOAT[24,1,2,2] c9862b3a19bc
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_0.w_0 FLOAT[16,3,3,3] 7841f2f3efae
|
||||
conv2d_0.w_0_bias FLOAT[16] 2713bf453fd1
|
||||
conv2d_107.w_0 FLOAT[96,384,1,1] 2fc401aa1ec6
|
||||
conv2d_108.w_0 FLOAT[384,96,1,1] f2a9a9261c07
|
||||
conv2d_138.w_0 FLOAT[24,96,3,3] 47aa8ba1db50
|
||||
conv2d_144.w_0 FLOAT[24,96,3,3] cd85b03c436c
|
||||
conv2d_150.w_0 FLOAT[24,96,3,3] 591f14004ce0
|
||||
conv2d_156.w_0 FLOAT[24,96,3,3] 5e0bc4bf821e
|
||||
conv2d_159.w_0 FLOAT[24,96,3,3] 43b6b1b17bef
|
||||
conv2d_159.w_0_bias FLOAT[24] c98267f8273d
|
||||
conv2d_161.w_0_lab FLOAT[16,1,3,3] 22528d709d37
|
||||
conv2d_162.w_0_lab_lab FLOAT[32,16,1,1] 051645505e21
|
||||
conv2d_163.w_0_lab_laboffset FLOAT[] 92a142f7dc41
|
||||
conv2d_163.w_0_lab_labscale FLOAT[32,1,3,3] 8694842bd3fb
|
||||
conv2d_164.w_0_lab FLOAT[48,32,1,1] 0c937f040d0e
|
||||
conv2d_165.w_0_lab_laboffset FLOAT[] 012179917694
|
||||
conv2d_165.w_0_lab_labscale FLOAT[48,1,3,3] 7d779e5616fa
|
||||
conv2d_166.w_0_lab_lab FLOAT[48,48,1,1] d70c86b2d1ec
|
||||
conv2d_167.w_0_lab_laboffset FLOAT[] 9741b37d98e3
|
||||
conv2d_167.w_0_lab_labscale FLOAT[48,1,3,3] fa2e1db2eb62
|
||||
conv2d_168.w_0_lab FLOAT[96,48,1,1] 81e13e0bd382
|
||||
conv2d_169.w_0_lab_laboffset FLOAT[] f3e015d53e9a
|
||||
conv2d_169.w_0_lab_labscale FLOAT[96,1,3,3] 75bbb69deb68
|
||||
conv2d_170.w_0_lab_lab FLOAT[96,96,1,1] 59b22a69e345
|
||||
conv2d_171.w_0_lab_laboffset FLOAT[] f42328163f40
|
||||
conv2d_171.w_0_lab_labscale FLOAT[96,1,3,3] 65cbca6287a2
|
||||
conv2d_172.w_0_lab FLOAT[192,96,1,1] ff93ca701d2f
|
||||
conv2d_173.w_0_lab_laboffset FLOAT[] b76450d3656f
|
||||
conv2d_173.w_0_lab_labscale FLOAT[192,1,5,5] 28d7de00679c
|
||||
conv2d_174.w_0_lab_lab FLOAT[192,192,1,1] 53cf6f343ec2
|
||||
conv2d_175.w_0_lab_laboffset FLOAT[] e665434a5d2d
|
||||
conv2d_175.w_0_lab_labscale FLOAT[192,1,5,5] 3c0aa815839d
|
||||
conv2d_176.w_0_lab_lab FLOAT[192,192,1,1] cb45f031f07b
|
||||
conv2d_177.w_0_lab_laboffset FLOAT[] e095ffc76247
|
||||
conv2d_177.w_0_lab_labscale FLOAT[192,1,5,5] 22fe03b75591
|
||||
conv2d_178.w_0_lab_lab FLOAT[192,192,1,1] c259022f5c3d
|
||||
conv2d_179.w_0_lab_laboffset FLOAT[] 5842420f0e64
|
||||
conv2d_179.w_0_lab_labscale FLOAT[192,1,5,5] 408bbab0d507
|
||||
conv2d_180.w_0_lab_lab FLOAT[192,192,1,1] 85871ea30bf1
|
||||
conv2d_181.w_0_lab_laboffset FLOAT[] 9e0407355f14
|
||||
conv2d_181.w_0_lab_labscale FLOAT[192,1,5,5] 75764b0f5265
|
||||
conv2d_182.w_0_lab FLOAT[384,192,1,1] 81235d1a972f
|
||||
conv2d_183.w_0_lab_laboffset FLOAT[] e648d792317a
|
||||
conv2d_183.w_0_lab_labscale FLOAT[384,1,5,5] f5341adaad28
|
||||
conv2d_184.w_0_lab FLOAT[384,384,1,1] c37a7cec640b
|
||||
conv2d_185.w_0_lab_laboffset FLOAT[] 768fa13da14b
|
||||
conv2d_185.w_0_lab_labscale FLOAT[384,1,5,5] 6bacb713155c
|
||||
conv2d_186.w_0_lab_lab FLOAT[384,384,1,1] 2fa80ae1b18f
|
||||
conv2d_187.w_0_lab_laboffset FLOAT[] ad505dafbd90
|
||||
conv2d_187.w_0_lab_labscale FLOAT[384,1,5,5] a221bd8406f2
|
||||
conv2d_188.w_0_lab_lab FLOAT[384,384,1,1] 9ea062b2f1b4
|
||||
conv2d_96.w_0 FLOAT[48,192,1,1] 6d73ce1fb738
|
||||
conv2d_97.w_0 FLOAT[192,48,1,1] 8098a00a81f0
|
||||
helper.constant.0 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.1 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.6 FLOAT[4] cf5451a623be
|
||||
helper.constant.8 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
learnable_affine_block_45.w_0 FLOAT[1] 65444e550b77
|
||||
learnable_affine_block_45.w_1 FLOAT[1] f2ee18a061af
|
||||
p2o.pd_op.conv2d.1.0_bias_lab_lab FLOAT[32] 3f4be24e33b8
|
||||
p2o.pd_op.conv2d.10.0_bias_lab_lab FLOAT[192] e32536500417
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[48] 961ec85108cb
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[192] c348751cbed0
|
||||
p2o.pd_op.conv2d.13.0_bias_lab FLOAT[384] 1b6d0aa0e977
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[96] 7876208c6fb1
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[384] 871907fff11d
|
||||
p2o.pd_op.conv2d.16.0_bias_lab FLOAT[384] fd15d67f1e85
|
||||
p2o.pd_op.conv2d.17.0_bias_lab_lab FLOAT[384] 097f0d068f05
|
||||
p2o.pd_op.conv2d.18.0_bias_lab_lab FLOAT[384] b8e228cae698
|
||||
p2o.pd_op.conv2d.2.0_bias_lab FLOAT[48] 8138a593f8f2
|
||||
p2o.pd_op.conv2d.3.0_bias_lab_lab FLOAT[48] 57128b896e31
|
||||
p2o.pd_op.conv2d.4.0_bias_lab FLOAT[96] d2230ff7a27e
|
||||
p2o.pd_op.conv2d.5.0_bias_lab_lab FLOAT[96] 05b9a5f236b6
|
||||
p2o.pd_op.conv2d.6.0_bias_lab FLOAT[192] a990b3fed4dd
|
||||
p2o.pd_op.conv2d.7.0_bias_lab_lab FLOAT[192] 74df3e4f22b6
|
||||
p2o.pd_op.conv2d.8.0_bias_lab_lab FLOAT[192] 9c072f4b4032
|
||||
p2o.pd_op.conv2d.9.0_bias_lab_lab FLOAT[192] 8f6e7021fe63
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias_lab FLOAT[16] 5b3de9e3f7c2
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias_lab FLOAT[32] bb4239a962eb
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias_lab FLOAT[192] 81ac3c08eae1
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias_lab FLOAT[384] 2236a6b52e38
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias_lab FLOAT[384] 14c22d416e3b
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias_lab FLOAT[384] 4eebd04fbeb4
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias_lab FLOAT[48] aaee6f6db9c1
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias_lab FLOAT[48] dcc78f972645
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias_lab FLOAT[96] dbd763cef105
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias_lab FLOAT[96] 5849d6801824
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias_lab FLOAT[192] 01e9219938aa
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias_lab FLOAT[192] e35d55fdac89
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias_lab FLOAT[192] fd7c6cc0a8fb
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias_lab FLOAT[192] aedc2ab77e2b
|
||||
p2o.pd_op.hardsigmoid.2.0_one FLOAT[] e00e5eb94441
|
||||
se_group0_down1 FLOAT[96,96,1,1] 4c8c888b01f2
|
||||
se_group0_down2 FLOAT[96] b99146f86442
|
||||
se_group0_sizes INT64[4] 4bb249469bee
|
||||
se_group0_up1 FLOAT[384,24,1,1] 1446892243f3
|
||||
se_group0_up2 FLOAT[384] 8538540d9317
|
||||
se_group1_down1 FLOAT[24,24,1,1] 01a670ee8021
|
||||
se_group1_down2 FLOAT[24] 7f8067be0db7
|
||||
se_group1_sizes INT64[4] 5c995dc6a0ef
|
||||
se_group1_up1 FLOAT[96,6,1,1] 3e47b305535b
|
||||
se_group1_up2 FLOAT[96] ed3a93d396c3
|
||||
@@ -0,0 +1,893 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20],
|
||||
metadata_props: ["character": "!
|
||||
\"
|
||||
#
|
||||
$
|
||||
%
|
||||
&
|
||||
'
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
||||
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|
||||
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|
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
||||
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
A
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
||||
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|
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
e
|
||||
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
v
|
||||
w
|
||||
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|
||||
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|
||||
z
|
||||
Α
|
||||
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|
||||
Γ
|
||||
Δ
|
||||
Ε
|
||||
Ζ
|
||||
Η
|
||||
Θ
|
||||
Ι
|
||||
Κ
|
||||
Λ
|
||||
Μ
|
||||
Ν
|
||||
Ξ
|
||||
Ο
|
||||
Π
|
||||
Ρ
|
||||
Σ
|
||||
Τ
|
||||
Υ
|
||||
Φ
|
||||
Χ
|
||||
Ψ
|
||||
Ω
|
||||
ά
|
||||
έ
|
||||
ή
|
||||
ί
|
||||
ό
|
||||
ύ
|
||||
ώ
|
||||
Ϊ
|
||||
Ϋ
|
||||
Ά
|
||||
Έ
|
||||
Ή
|
||||
Ί
|
||||
Ό
|
||||
Ύ
|
||||
Ώ
|
||||
ϊ
|
||||
ΐ
|
||||
ϋ
|
||||
ΰ
|
||||
α
|
||||
β
|
||||
γ
|
||||
δ
|
||||
ε
|
||||
ζ
|
||||
η
|
||||
θ
|
||||
ι
|
||||
κ
|
||||
λ
|
||||
μ
|
||||
ν
|
||||
ξ
|
||||
ο
|
||||
π
|
||||
ρ
|
||||
ς
|
||||
σ
|
||||
τ
|
||||
υ
|
||||
φ
|
||||
χ
|
||||
ψ
|
||||
ω
|
||||
ϐ
|
||||
ϑ
|
||||
ϒ
|
||||
ϓ
|
||||
ϔ
|
||||
ϕ
|
||||
ϖ
|
||||
Ϛ
|
||||
ϛ
|
||||
Ϝ
|
||||
ϝ
|
||||
Ϟ
|
||||
ϟ
|
||||
Ϡ
|
||||
ϡ
|
||||
Ϣ
|
||||
ϣ
|
||||
Ϥ
|
||||
ϥ
|
||||
Ϧ
|
||||
ϧ
|
||||
Ϩ
|
||||
ϩ
|
||||
Ϫ
|
||||
ϫ
|
||||
Ϭ
|
||||
ϭ
|
||||
Ϯ
|
||||
ϯ
|
||||
ϰ
|
||||
ϱ
|
||||
ϲ
|
||||
ϳ
|
||||
ϴ
|
||||
ϵ
|
||||
϶
|
||||
Ϸ
|
||||
ϸ
|
||||
Ϲ
|
||||
Ϻ
|
||||
ϻ
|
||||
"]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,48,width,3] image) => (int32[batch,seq] ctc_indices, float[batch,seq] ctc_confidence)
|
||||
<
|
||||
float[batch,240,12,unk__11] "Add.105"
|
||||
float[batch,240,12,unk__11] "Add.111"
|
||||
float[batch,240,12,unk__11] "Add.117"
|
||||
float[batch,240,6,unk__11] "Add.123"
|
||||
float[batch,240,6,unk__11] "Add.125"
|
||||
float[batch,60,1,1] "Add.127"
|
||||
float[batch,240,1,1] "Add.129"
|
||||
float[batch,480,6,unk__11] "Add.133"
|
||||
float[batch,480,6,unk__11] "Add.139"
|
||||
float[batch,480,6,unk__11] "Add.141"
|
||||
float[batch,120,1,1] "Add.143"
|
||||
float[batch,480,1,1] "Add.145"
|
||||
float[batch,480,6,unk__11] "Add.149"
|
||||
float[batch,32,24,unk__0] "Add.15"
|
||||
float[batch,480,3,unk__11] "Add.155"
|
||||
float[batch,480,3,unk__11] "Add.161"
|
||||
float[batch,480,3,unk__11] "Add.167"
|
||||
float[batch,480,3,unk__11] "Add.173"
|
||||
float[batch,seq,120] "Add.181"
|
||||
float[batch,seq,360] "Add.183"
|
||||
float[batch,8,seq,15] "Add.183_k"
|
||||
float[batch,8,seq,15] "Add.183_q"
|
||||
float[batch,seq,24,15] "Add.183_qkv"
|
||||
float[batch,24,seq,15] "Add.183_qkv_heads"
|
||||
float[batch,8,seq,15] "Add.183_v"
|
||||
float[batch,seq,120] "Add.185"
|
||||
float[batch,seq,120] "Add.187"
|
||||
float[batch,seq,120] "Add.191"
|
||||
float[batch,seq,240] "Add.193"
|
||||
float[batch,seq,120] "Add.195"
|
||||
float[batch,seq,120] "Add.197"
|
||||
float[batch,seq,120] "Add.201"
|
||||
float[batch,seq,360] "Add.203"
|
||||
float[batch,8,seq,15] "Add.203_k"
|
||||
float[batch,8,seq,15] "Add.203_q"
|
||||
float[batch,seq,24,15] "Add.203_qkv"
|
||||
float[batch,24,seq,15] "Add.203_qkv_heads"
|
||||
float[batch,8,seq,15] "Add.203_v"
|
||||
float[batch,seq,120] "Add.205"
|
||||
float[batch,seq,120] "Add.207"
|
||||
float[batch,64,24,unk__0] "Add.21"
|
||||
float[batch,seq,120] "Add.211"
|
||||
float[batch,seq,240] "Add.213"
|
||||
float[batch,seq,120] "Add.215"
|
||||
float[batch,seq,120] "Add.217"
|
||||
float[batch,seq,120] "Add.221"
|
||||
float[batch,seq,356] "Add.223"
|
||||
float[batch,64,24,unk__0] "Add.27"
|
||||
float[batch,16,24,unk__0] "Add.3"
|
||||
float[batch,64,24,unk__0] "Add.33"
|
||||
float[batch,64,12,unk__0] "Add.39"
|
||||
float[batch,128,12,unk__0] "Add.45"
|
||||
float[batch,128,12,unk__0] "Add.51"
|
||||
float[batch,128,12,unk__0] "Add.57"
|
||||
float[batch,128,12,unk__11] "Add.63"
|
||||
float[batch,240,12,unk__11] "Add.69"
|
||||
float[batch,240,12,unk__11] "Add.75"
|
||||
float[batch,240,12,unk__11] "Add.81"
|
||||
float[batch,240,12,unk__11] "Add.87"
|
||||
float[batch,32,24,unk__0] "Add.9"
|
||||
float[batch,240,12,unk__11] "Add.93"
|
||||
float[batch,240,12,unk__11] "Add.99"
|
||||
float[batch,960,1,seq] "Concat.4"
|
||||
float[batch,240,6,unk__11] "Mul.83"
|
||||
float[batch,240,6,unk__11] "Mul.85"
|
||||
float[batch,480,6,unk__11] "Mul.93"
|
||||
float[batch,480,6,unk__11] "Mul.95"
|
||||
float[batch,60,1,seq] "Sigmoid.1"
|
||||
float[batch,60,1,seq] "Sigmoid.11"
|
||||
float[batch,120,1,seq] "Sigmoid.13"
|
||||
float[batch,120,1,seq] "Sigmoid.3"
|
||||
float[batch,seq,240] "Sigmoid.5"
|
||||
float[batch,seq,240] "Sigmoid.7"
|
||||
float[batch,480,1,seq] "Sigmoid.9"
|
||||
float[batch,16,24,unk__0] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,60,1,seq] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,120,1,seq] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,480,1,seq] "p2o.pd_op.batch_norm_.3.0"
|
||||
float[batch,60,1,seq] "p2o.pd_op.batch_norm_.4.0"
|
||||
float[batch,120,1,seq] "p2o.pd_op.batch_norm_.5.0"
|
||||
float[batch,120,seq] "p2o.pd_op.flatten.0.0"
|
||||
float[batch,240,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,480,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,16,24,unk__0] "p2o.pd_op.hardswish.0.0"
|
||||
float[batch,32,24,unk__0] "p2o.pd_op.hardswish.1.0"
|
||||
float[batch,128,12,unk__11] "p2o.pd_op.hardswish.10.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.11.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.12.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.13.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.14.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.15.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.16.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.17.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.18.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.19.0"
|
||||
float[batch,32,24,unk__0] "p2o.pd_op.hardswish.2.0"
|
||||
float[batch,240,6,unk__11] "p2o.pd_op.hardswish.20.0"
|
||||
float[batch,480,6,unk__11] "p2o.pd_op.hardswish.21.0"
|
||||
float[batch,480,6,unk__11] "p2o.pd_op.hardswish.22.0"
|
||||
float[batch,480,6,unk__11] "p2o.pd_op.hardswish.23.0"
|
||||
float[batch,480,3,unk__11] "p2o.pd_op.hardswish.24.0"
|
||||
float[batch,480,3,unk__11] "p2o.pd_op.hardswish.25.0"
|
||||
float[batch,480,3,unk__11] "p2o.pd_op.hardswish.26.0"
|
||||
float[batch,480,3,unk__11] "p2o.pd_op.hardswish.27.0"
|
||||
float[batch,64,24,unk__0] "p2o.pd_op.hardswish.3.0"
|
||||
float[batch,64,24,unk__0] "p2o.pd_op.hardswish.4.0"
|
||||
float[batch,64,24,unk__0] "p2o.pd_op.hardswish.5.0"
|
||||
float[batch,64,12,unk__0] "p2o.pd_op.hardswish.6.0"
|
||||
float[batch,128,12,unk__0] "p2o.pd_op.hardswish.7.0"
|
||||
float[batch,128,12,unk__0] "p2o.pd_op.hardswish.8.0"
|
||||
float[batch,128,12,unk__0] "p2o.pd_op.hardswish.9.0"
|
||||
float[batch,seq,360] "p2o.pd_op.matmul.0.0"
|
||||
float[batch,8,seq,seq] "p2o.pd_op.matmul.1.0"
|
||||
float[batch,seq,240] "p2o.pd_op.matmul.10.0"
|
||||
float[batch,seq,120] "p2o.pd_op.matmul.11.0"
|
||||
float[batch,seq,356] "p2o.pd_op.matmul.12.0"
|
||||
float[batch,8,seq,15] "p2o.pd_op.matmul.2.0"
|
||||
float[batch,seq,120] "p2o.pd_op.matmul.3.0"
|
||||
float[batch,seq,240] "p2o.pd_op.matmul.4.0"
|
||||
float[batch,seq,120] "p2o.pd_op.matmul.5.0"
|
||||
float[batch,seq,360] "p2o.pd_op.matmul.6.0"
|
||||
float[batch,8,seq,seq] "p2o.pd_op.matmul.7.0"
|
||||
float[batch,8,seq,15] "p2o.pd_op.matmul.8.0"
|
||||
float[batch,seq,120] "p2o.pd_op.matmul.9.0"
|
||||
float[batch,240,1,1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,480,1,1] "p2o.pd_op.pool2d.1.0"
|
||||
float[batch,480,1,seq] "p2o.pd_op.pool2d.2.0"
|
||||
float[batch,60,1,1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,120,1,1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,seq,120] "p2o.pd_op.reshape.33.0"
|
||||
float[batch,seq,120] "p2o.pd_op.reshape.35.0"
|
||||
float[batch,1,seq,120] "p2o.pd_op.reshape.36.0"
|
||||
float[batch,8,seq,seq] "p2o.pd_op.softmax.0.0"
|
||||
float[batch,8,seq,seq] "p2o.pd_op.softmax.1.0"
|
||||
float[batch,120,seq] "p2o.pd_op.squeeze.0.0"
|
||||
float[batch,60,1,seq] "p2o.pd_op.swish.0.0"
|
||||
float[batch,120,1,seq] "p2o.pd_op.swish.1.0"
|
||||
float[batch,seq,240] "p2o.pd_op.swish.2.0"
|
||||
float[batch,seq,240] "p2o.pd_op.swish.3.0"
|
||||
float[batch,480,1,seq] "p2o.pd_op.swish.4.0"
|
||||
float[batch,60,1,seq] "p2o.pd_op.swish.5.0"
|
||||
float[batch,120,1,seq] "p2o.pd_op.swish.6.0"
|
||||
float[batch,seq,120] "p2o.pd_op.transpose.0.0"
|
||||
float[batch,8,15,seq] "p2o.pd_op.transpose.2.0"
|
||||
float[batch,seq,8,15] "p2o.pd_op.transpose.3.0"
|
||||
float[batch,8,15,seq] "p2o.pd_op.transpose.5.0"
|
||||
float[batch,seq,8,15] "p2o.pd_op.transpose.6.0"
|
||||
float[batch,120,1,seq] "p2o.pd_op.transpose.7.0"
|
||||
float[batch,seq,120] "p2o.pd_op.transpose.8.0"
|
||||
float[batch,seq,1] max_logits
|
||||
float[batch,48,width,3] tmp
|
||||
float[batch,3,48,width] tmp_0
|
||||
float[batch,seq,356] tmp_0_2
|
||||
float[batch,seq,356] tmp_1
|
||||
int64[batch,seq] tmp_2
|
||||
float[batch,seq] tmp_3
|
||||
float[batch,16,24,unk__0] val_0
|
||||
float[batch,32,24,unk__0] val_1
|
||||
float[batch,128,12,unk__0] val_10
|
||||
float[batch,128,12,unk__0] val_11
|
||||
float[batch,128,12,unk__0] val_12
|
||||
float[batch,128,12,unk__0] val_13
|
||||
float[batch,128,12,unk__0] val_14
|
||||
float[batch,128,12,unk__11] val_15
|
||||
float[batch,240,12,unk__11] val_16
|
||||
float[batch,240,12,unk__11] val_17
|
||||
float[batch,240,12,unk__11] val_18
|
||||
float[batch,240,12,unk__11] val_19
|
||||
float[batch,32,24,unk__0] val_2
|
||||
float[batch,240,12,unk__11] val_20
|
||||
float[batch,240,12,unk__11] val_21
|
||||
float[batch,240,12,unk__11] val_22
|
||||
float[batch,240,12,unk__11] val_23
|
||||
float[batch,240,12,unk__11] val_24
|
||||
float[batch,240,12,unk__11] val_25
|
||||
float[batch,240,12,unk__11] val_26
|
||||
float[batch,240,12,unk__11] val_27
|
||||
float[batch,240,12,unk__11] val_28
|
||||
float[batch,240,12,unk__11] val_29
|
||||
float[batch,32,24,unk__0] val_3
|
||||
float[batch,240,6,unk__11] val_30
|
||||
float[batch,480,6,unk__11] val_31
|
||||
float[batch,480,6,unk__11] val_32
|
||||
float[batch,480,6,unk__11] val_33
|
||||
float[batch,480,6,unk__11] val_34
|
||||
float[batch,480,6,unk__11] val_35
|
||||
float[batch,480,3,unk__11] val_36
|
||||
float[batch,480,3,unk__11] val_37
|
||||
float[batch,480,3,unk__11] val_38
|
||||
float[batch,480,3,unk__11] val_39
|
||||
float[batch,64,24,unk__0] val_4
|
||||
float[batch,480,3,unk__11] val_40
|
||||
float[batch,480,1,seq] val_41
|
||||
float[batch,480,1,seq] val_42
|
||||
float[batch,64,24,unk__0] val_5
|
||||
float[batch,64,24,unk__0] val_6
|
||||
float[batch,64,24,unk__0] val_7
|
||||
float[batch,64,24,unk__0] val_8
|
||||
float[batch,64,12,unk__0] val_9
|
||||
float[batch,3,48,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_0.w_0", "conv2d_0.w_0_bias")
|
||||
"Add.3" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 16, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.0.0", "conv2d_136.w_0_lab", "p2o.pd_op.depthwise_conv2d.0.0_bias_lab")
|
||||
val_0 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.3")
|
||||
"p2o.pd_op.hardswish.0.0" = Mul ("Add.3", val_0)
|
||||
"Add.9" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.0.0", "conv2d_137.w_0_lab_lab", "p2o.pd_op.conv2d.1.0_bias_lab_lab")
|
||||
val_1 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.9")
|
||||
"p2o.pd_op.hardswish.1.0" = Mul ("Add.9", val_1)
|
||||
val_2 = Add ("p2o.pd_op.hardswish.1.0", "conv2d_138.w_0_lab_laboffset")
|
||||
"Add.15" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_2, "conv2d_138.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.1.0_bias_lab")
|
||||
val_3 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.15")
|
||||
"p2o.pd_op.hardswish.2.0" = Mul ("Add.15", val_3)
|
||||
"Add.21" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.2.0", "conv2d_139.w_0_lab_lab", "p2o.pd_op.conv2d.2.0_bias_lab_lab")
|
||||
val_4 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.21")
|
||||
"p2o.pd_op.hardswish.3.0" = Mul ("Add.21", val_4)
|
||||
val_5 = Add ("p2o.pd_op.hardswish.3.0", "conv2d_140.w_0_lab_laboffset")
|
||||
"Add.27" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_5, "conv2d_140.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.2.0_bias_lab")
|
||||
val_6 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.27")
|
||||
"p2o.pd_op.hardswish.4.0" = Mul ("Add.27", val_6)
|
||||
"Add.33" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.4.0", "conv2d_141.w_0_lab_lab", "p2o.pd_op.conv2d.3.0_bias_lab_lab")
|
||||
val_7 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.33")
|
||||
"p2o.pd_op.hardswish.5.0" = Mul ("Add.33", val_7)
|
||||
val_8 = Add ("p2o.pd_op.hardswish.5.0", "conv2d_142.w_0_lab_laboffset")
|
||||
"Add.39" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 1]> (val_8, "conv2d_142.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.3.0_bias_lab")
|
||||
val_9 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.39")
|
||||
"p2o.pd_op.hardswish.6.0" = Mul ("Add.39", val_9)
|
||||
"Add.45" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.6.0", "conv2d_143.w_0_lab_lab", "p2o.pd_op.conv2d.4.0_bias_lab_lab")
|
||||
val_10 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.45")
|
||||
"p2o.pd_op.hardswish.7.0" = Mul ("Add.45", val_10)
|
||||
val_11 = Add ("p2o.pd_op.hardswish.7.0", "conv2d_144.w_0_lab_laboffset")
|
||||
"Add.51" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 128, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_11, "conv2d_144.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.4.0_bias_lab")
|
||||
val_12 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.51")
|
||||
"p2o.pd_op.hardswish.8.0" = Mul ("Add.51", val_12)
|
||||
"Add.57" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.8.0", "conv2d_145.w_0_lab_lab", "p2o.pd_op.conv2d.5.0_bias_lab_lab")
|
||||
val_13 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.57")
|
||||
"p2o.pd_op.hardswish.9.0" = Mul ("Add.57", val_13)
|
||||
val_14 = Add ("p2o.pd_op.hardswish.9.0", "conv2d_146.w_0_lab_laboffset")
|
||||
"Add.63" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 128, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 2]> (val_14, "conv2d_146.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.5.0_bias_lab")
|
||||
val_15 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.63")
|
||||
"p2o.pd_op.hardswish.10.0" = Mul ("Add.63", val_15)
|
||||
"Add.69" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.10.0", "conv2d_147.w_0_lab_lab", "p2o.pd_op.conv2d.6.0_bias_lab_lab")
|
||||
val_16 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.69")
|
||||
"p2o.pd_op.hardswish.11.0" = Mul ("Add.69", val_16)
|
||||
val_17 = Add ("p2o.pd_op.hardswish.11.0", "conv2d_148.w_0_lab_laboffset")
|
||||
"Add.75" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 240, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_17, "conv2d_148.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.6.0_bias_lab")
|
||||
val_18 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.75")
|
||||
"p2o.pd_op.hardswish.12.0" = Mul ("Add.75", val_18)
|
||||
"Add.81" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.12.0", "conv2d_149.w_0_lab_lab", "p2o.pd_op.conv2d.7.0_bias_lab_lab")
|
||||
val_19 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.81")
|
||||
"p2o.pd_op.hardswish.13.0" = Mul ("Add.81", val_19)
|
||||
val_20 = Add ("p2o.pd_op.hardswish.13.0", "conv2d_150.w_0_lab_laboffset")
|
||||
"Add.87" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 240, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_20, "conv2d_150.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.7.0_bias_lab")
|
||||
val_21 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.87")
|
||||
"p2o.pd_op.hardswish.14.0" = Mul ("Add.87", val_21)
|
||||
"Add.93" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.14.0", "conv2d_151.w_0_lab_lab", "p2o.pd_op.conv2d.8.0_bias_lab_lab")
|
||||
val_22 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.93")
|
||||
"p2o.pd_op.hardswish.15.0" = Mul ("Add.93", val_22)
|
||||
val_23 = Add ("p2o.pd_op.hardswish.15.0", "conv2d_152.w_0_lab_laboffset")
|
||||
"Add.99" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 240, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_23, "conv2d_152.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.8.0_bias_lab")
|
||||
val_24 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.99")
|
||||
"p2o.pd_op.hardswish.16.0" = Mul ("Add.99", val_24)
|
||||
"Add.105" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.16.0", "conv2d_153.w_0_lab_lab", "p2o.pd_op.conv2d.9.0_bias_lab_lab")
|
||||
val_25 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.105")
|
||||
"p2o.pd_op.hardswish.17.0" = Mul ("Add.105", val_25)
|
||||
val_26 = Add ("p2o.pd_op.hardswish.17.0", "conv2d_154.w_0_lab_laboffset")
|
||||
"Add.111" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 240, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_26, "conv2d_154.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.9.0_bias_lab")
|
||||
val_27 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.111")
|
||||
"p2o.pd_op.hardswish.18.0" = Mul ("Add.111", val_27)
|
||||
"Add.117" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.18.0", "conv2d_155.w_0_lab_lab", "p2o.pd_op.conv2d.10.0_bias_lab_lab")
|
||||
val_28 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.117")
|
||||
"p2o.pd_op.hardswish.19.0" = Mul ("Add.117", val_28)
|
||||
val_29 = Add ("p2o.pd_op.hardswish.19.0", "conv2d_156.w_0_lab_laboffset")
|
||||
"Add.123" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 240, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [2, 1]> (val_29, "conv2d_156.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.10.0_bias_lab")
|
||||
val_30 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.123")
|
||||
"p2o.pd_op.hardswish.20.0" = Mul ("Add.123", val_30)
|
||||
["Mul.82"] "Mul.83" = Mul ("learnable_affine_block_41.w_0", "p2o.pd_op.hardswish.20.0")
|
||||
["Add.124"] "Add.125" = Add ("Mul.83", "learnable_affine_block_41.w_1")
|
||||
["GlobalAveragePool.0"] "p2o.pd_op.pool2d.0.0" = GlobalAveragePool ("Add.125")
|
||||
"Add.127" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.0.0", "conv2d_96.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.127")
|
||||
"Add.129" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_97.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.129")
|
||||
["Mul.84"] "Mul.85" = Mul ("Add.125", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.133" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.85", "conv2d_157.w_0_lab", "p2o.pd_op.conv2d.13.0_bias_lab")
|
||||
val_31 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.133")
|
||||
"p2o.pd_op.hardswish.21.0" = Mul ("Add.133", val_31)
|
||||
val_32 = Add ("p2o.pd_op.hardswish.21.0", "conv2d_158.w_0_lab_laboffset")
|
||||
"Add.139" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 480, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_32, "conv2d_158.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.11.0_bias_lab")
|
||||
val_33 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.139")
|
||||
"p2o.pd_op.hardswish.22.0" = Mul ("Add.139", val_33)
|
||||
["Mul.92"] "Mul.93" = Mul ("learnable_affine_block_45.w_0", "p2o.pd_op.hardswish.22.0")
|
||||
["Add.140"] "Add.141" = Add ("Mul.93", "learnable_affine_block_45.w_1")
|
||||
["GlobalAveragePool.1"] "p2o.pd_op.pool2d.1.0" = GlobalAveragePool ("Add.141")
|
||||
"Add.143" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.1.0", "conv2d_107.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.143")
|
||||
"Add.145" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_108.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.145")
|
||||
["Mul.94"] "Mul.95" = Mul ("Add.141", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.149" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.95", "conv2d_159.w_0_lab", "p2o.pd_op.conv2d.16.0_bias_lab")
|
||||
val_34 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.149")
|
||||
"p2o.pd_op.hardswish.23.0" = Mul ("Add.149", val_34)
|
||||
val_35 = Add ("p2o.pd_op.hardswish.23.0", "conv2d_160.w_0_lab_laboffset")
|
||||
"Add.155" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 480, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [2, 1]> (val_35, "conv2d_160.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.12.0_bias_lab")
|
||||
val_36 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.155")
|
||||
"p2o.pd_op.hardswish.24.0" = Mul ("Add.155", val_36)
|
||||
"Add.161" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.24.0", "conv2d_161.w_0_lab_lab", "p2o.pd_op.conv2d.17.0_bias_lab_lab")
|
||||
val_37 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.161")
|
||||
"p2o.pd_op.hardswish.25.0" = Mul ("Add.161", val_37)
|
||||
val_38 = Add ("p2o.pd_op.hardswish.25.0", "conv2d_162.w_0_lab_laboffset")
|
||||
"Add.167" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 480, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_38, "conv2d_162.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.13.0_bias_lab")
|
||||
val_39 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.167")
|
||||
"p2o.pd_op.hardswish.26.0" = Mul ("Add.167", val_39)
|
||||
"Add.173" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.26.0", "conv2d_163.w_0_lab_lab", "p2o.pd_op.conv2d.18.0_bias_lab_lab")
|
||||
val_40 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.173")
|
||||
"p2o.pd_op.hardswish.27.0" = Mul ("Add.173", val_40)
|
||||
val_41 = AveragePool <auto_pad: string = "NOTSET", ceil_mode: int = 0, count_include_pad: int = 0, kernel_shape: ints = [3, 2], pads: ints = [0, 0, 0, 0], strides: ints = [3, 2]> ("p2o.pd_op.hardswish.27.0")
|
||||
val_42 = Mul (val_41, "learnable_affine_block_55.w_0")
|
||||
"p2o.pd_op.pool2d.2.0" = Add (val_42, "learnable_affine_block_55.w_1")
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 3], pads: ints = [0, 1, 0, 1], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.2.0", "conv2d_131.w_0", "conv2d_131.w_0_bias")
|
||||
["Sigmoid.0"] "Sigmoid.1" = Sigmoid ("p2o.pd_op.batch_norm_.1.0")
|
||||
["Mul.116"] "p2o.pd_op.swish.0.0" = Mul ("p2o.pd_op.batch_norm_.1.0", "Sigmoid.1")
|
||||
"p2o.pd_op.batch_norm_.2.0" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.swish.0.0", "conv2d_132.w_0", "conv2d_132.w_0_bias")
|
||||
["Sigmoid.2"] "Sigmoid.3" = Sigmoid ("p2o.pd_op.batch_norm_.2.0")
|
||||
["Mul.117"] "p2o.pd_op.swish.1.0" = Mul ("p2o.pd_op.batch_norm_.2.0", "Sigmoid.3")
|
||||
"p2o.pd_op.flatten.0.0" = Squeeze ("p2o.pd_op.swish.1.0", "helper.constant.9")
|
||||
["Transpose.0"] "p2o.pd_op.transpose.0.0" = Transpose <perm: ints = [0, 2, 1]> ("p2o.pd_op.flatten.0.0")
|
||||
"Add.181" = LayerNormalization <axis: int = -1, epsilon: float = 1e-05, stash_type: int = 1> ("p2o.pd_op.transpose.0.0", "helper.reshape.0", "helper.reshape.1")
|
||||
["MatMul.0"] "p2o.pd_op.matmul.0.0" = MatMul ("Add.181", "linear_0.w_0_qkv_scaled")
|
||||
["Add.182"] "Add.183" = Add ("p2o.pd_op.matmul.0.0", "linear_0.b_0_qkv_scaled")
|
||||
"Add.183_qkv" = Reshape <allowzero: int = 0> ("Add.183", "Add.183_qkv_shape")
|
||||
"Add.183_qkv_heads" = Transpose <perm: ints = [0, 2, 1, 3]> ("Add.183_qkv")
|
||||
"Add.183_q", "Add.183_k", "Add.183_v" = Split <axis: int = 1> ("Add.183_qkv_heads", "Add.183_qkv_sizes")
|
||||
["Transpose.2"] "p2o.pd_op.transpose.2.0" = Transpose <perm: ints = [0, 1, 3, 2]> ("Add.183_k")
|
||||
["MatMul.1"] "p2o.pd_op.matmul.1.0" = MatMul ("Add.183_q", "p2o.pd_op.transpose.2.0")
|
||||
["Softmax.0"] "p2o.pd_op.softmax.0.0" = Softmax <axis: int = -1> ("p2o.pd_op.matmul.1.0")
|
||||
["MatMul.2"] "p2o.pd_op.matmul.2.0" = MatMul ("p2o.pd_op.softmax.0.0", "Add.183_v")
|
||||
["Transpose.3"] "p2o.pd_op.transpose.3.0" = Transpose <perm: ints = [0, 2, 1, 3]> ("p2o.pd_op.matmul.2.0")
|
||||
["Reshape.38"] "p2o.pd_op.reshape.33.0" = Reshape <allowzero: int = 0> ("p2o.pd_op.transpose.3.0", "auto.cast.38")
|
||||
["MatMul.3"] "p2o.pd_op.matmul.3.0" = MatMul ("p2o.pd_op.reshape.33.0", "linear_1.w_0")
|
||||
["Add.184"] "Add.185" = Add ("p2o.pd_op.matmul.3.0", "linear_1.b_0")
|
||||
["Add.186"] "Add.187" = Add ("p2o.pd_op.transpose.0.0", "Add.185")
|
||||
"Add.191" = LayerNormalization <axis: int = -1, epsilon: float = 1e-05, stash_type: int = 1> ("Add.187", "helper.reshape.2", "helper.reshape.3")
|
||||
["MatMul.4"] "p2o.pd_op.matmul.4.0" = MatMul ("Add.191", "linear_2.w_0")
|
||||
["Add.192"] "Add.193" = Add ("p2o.pd_op.matmul.4.0", "linear_2.b_0")
|
||||
["Sigmoid.4"] "Sigmoid.5" = Sigmoid ("Add.193")
|
||||
["Mul.124"] "p2o.pd_op.swish.2.0" = Mul ("Add.193", "Sigmoid.5")
|
||||
["MatMul.5"] "p2o.pd_op.matmul.5.0" = MatMul ("p2o.pd_op.swish.2.0", "linear_3.w_0")
|
||||
["Add.194"] "Add.195" = Add ("p2o.pd_op.matmul.5.0", "linear_3.b_0")
|
||||
["Add.196"] "Add.197" = Add ("Add.187", "Add.195")
|
||||
"Add.201" = LayerNormalization <axis: int = -1, epsilon: float = 1e-05, stash_type: int = 1> ("Add.197", "helper.reshape.4", "helper.reshape.5")
|
||||
["MatMul.6"] "p2o.pd_op.matmul.6.0" = MatMul ("Add.201", "linear_4.w_0_qkv_scaled")
|
||||
["Add.202"] "Add.203" = Add ("p2o.pd_op.matmul.6.0", "linear_4.b_0_qkv_scaled")
|
||||
"Add.203_qkv" = Reshape <allowzero: int = 0> ("Add.203", "Add.183_qkv_shape")
|
||||
"Add.203_qkv_heads" = Transpose <perm: ints = [0, 2, 1, 3]> ("Add.203_qkv")
|
||||
"Add.203_q", "Add.203_k", "Add.203_v" = Split <axis: int = 1> ("Add.203_qkv_heads", "Add.183_qkv_sizes")
|
||||
["Transpose.5"] "p2o.pd_op.transpose.5.0" = Transpose <perm: ints = [0, 1, 3, 2]> ("Add.203_k")
|
||||
["MatMul.7"] "p2o.pd_op.matmul.7.0" = MatMul ("Add.203_q", "p2o.pd_op.transpose.5.0")
|
||||
["Softmax.1"] "p2o.pd_op.softmax.1.0" = Softmax <axis: int = -1> ("p2o.pd_op.matmul.7.0")
|
||||
["MatMul.8"] "p2o.pd_op.matmul.8.0" = MatMul ("p2o.pd_op.softmax.1.0", "Add.203_v")
|
||||
["Transpose.6"] "p2o.pd_op.transpose.6.0" = Transpose <perm: ints = [0, 2, 1, 3]> ("p2o.pd_op.matmul.8.0")
|
||||
["Reshape.46"] "p2o.pd_op.reshape.35.0" = Reshape <allowzero: int = 0> ("p2o.pd_op.transpose.6.0", "auto.cast.38")
|
||||
["MatMul.9"] "p2o.pd_op.matmul.9.0" = MatMul ("p2o.pd_op.reshape.35.0", "linear_5.w_0")
|
||||
["Add.204"] "Add.205" = Add ("p2o.pd_op.matmul.9.0", "linear_5.b_0")
|
||||
["Add.206"] "Add.207" = Add ("Add.197", "Add.205")
|
||||
"Add.211" = LayerNormalization <axis: int = -1, epsilon: float = 1e-05, stash_type: int = 1> ("Add.207", "helper.reshape.6", "helper.reshape.7")
|
||||
["MatMul.10"] "p2o.pd_op.matmul.10.0" = MatMul ("Add.211", "linear_6.w_0")
|
||||
["Add.212"] "Add.213" = Add ("p2o.pd_op.matmul.10.0", "linear_6.b_0")
|
||||
["Sigmoid.6"] "Sigmoid.7" = Sigmoid ("Add.213")
|
||||
["Mul.131"] "p2o.pd_op.swish.3.0" = Mul ("Add.213", "Sigmoid.7")
|
||||
["MatMul.11"] "p2o.pd_op.matmul.11.0" = MatMul ("p2o.pd_op.swish.3.0", "linear_7.w_0")
|
||||
["Add.214"] "Add.215" = Add ("p2o.pd_op.matmul.11.0", "linear_7.b_0")
|
||||
["Add.216"] "Add.217" = Add ("Add.207", "Add.215")
|
||||
"Add.221" = LayerNormalization <axis: int = -1, epsilon: float = 1e-06, stash_type: int = 1> ("Add.217", "helper.reshape.8", "helper.reshape.9")
|
||||
"p2o.pd_op.reshape.36.0" = Unsqueeze ("Add.221", rec_unsqueeze_axis)
|
||||
["Transpose.7"] "p2o.pd_op.transpose.7.0" = Transpose <perm: ints = [0, 3, 1, 2]> ("p2o.pd_op.reshape.36.0")
|
||||
"p2o.pd_op.batch_norm_.3.0" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.transpose.7.0", "conv2d_133.w_0", "conv2d_133.w_0_bias")
|
||||
["Sigmoid.8"] "Sigmoid.9" = Sigmoid ("p2o.pd_op.batch_norm_.3.0")
|
||||
["Mul.134"] "p2o.pd_op.swish.4.0" = Mul ("p2o.pd_op.batch_norm_.3.0", "Sigmoid.9")
|
||||
["Concat.3"] "Concat.4" = Concat <axis: int = 1> ("p2o.pd_op.pool2d.2.0", "p2o.pd_op.swish.4.0")
|
||||
"p2o.pd_op.batch_norm_.4.0" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 3], pads: ints = [0, 1, 0, 1], strides: ints = [1, 1]> ("Concat.4", "conv2d_134.w_0", "conv2d_134.w_0_bias")
|
||||
["Sigmoid.10"] "Sigmoid.11" = Sigmoid ("p2o.pd_op.batch_norm_.4.0")
|
||||
["Mul.135"] "p2o.pd_op.swish.5.0" = Mul ("p2o.pd_op.batch_norm_.4.0", "Sigmoid.11")
|
||||
"p2o.pd_op.batch_norm_.5.0" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.swish.5.0", "conv2d_135.w_0", "conv2d_135.w_0_bias")
|
||||
["Sigmoid.12"] "Sigmoid.13" = Sigmoid ("p2o.pd_op.batch_norm_.5.0")
|
||||
["Mul.136"] "p2o.pd_op.swish.6.0" = Mul ("p2o.pd_op.batch_norm_.5.0", "Sigmoid.13")
|
||||
["Squeeze.8"] "p2o.pd_op.squeeze.0.0" = Squeeze ("p2o.pd_op.swish.6.0", "helper.constant.9")
|
||||
["Transpose.8"] "p2o.pd_op.transpose.8.0" = Transpose <perm: ints = [0, 2, 1]> ("p2o.pd_op.squeeze.0.0")
|
||||
["MatMul.12"] "p2o.pd_op.matmul.12.0" = MatMul ("p2o.pd_op.transpose.8.0", "linear_8.w_0")
|
||||
["Add.222"] "Add.223" = Add ("p2o.pd_op.matmul.12.0", "linear_8.b_0")
|
||||
[n0_2] tmp_2 = ArgMax <axis: int = 2, keepdims: int = 0> ("Add.223")
|
||||
[n1_2] ctc_indices = Cast <to: int = 6> (tmp_2)
|
||||
[n3_2] max_logits = ReduceMax <keepdims: int = 1> ("Add.223", "helper.constant.9")
|
||||
[n4_2] tmp_0_2 = Sub ("Add.223", max_logits)
|
||||
[n5] tmp_1 = Exp (tmp_0_2)
|
||||
[n7] tmp_3 = ReduceSum <keepdims: int = 0> (tmp_1, "helper.constant.9")
|
||||
[n8] ctc_confidence = Reciprocal (tmp_3)
|
||||
}
|
||||
|
||||
weights:
|
||||
Add.183_qkv_shape INT64[4] 003762987fc4
|
||||
Add.183_qkv_sizes INT64[3] 49f92c4a88e0
|
||||
auto.cast.38 INT64[3] b190f2a09873
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_0.w_0 FLOAT[16,3,3,3] 7da3ef9a90f6
|
||||
conv2d_0.w_0_bias FLOAT[16] 4d9cec9f4e74
|
||||
conv2d_107.w_0 FLOAT[120,480,1,1] b36fbe5cef8d
|
||||
conv2d_108.w_0 FLOAT[480,120,1,1] 94437c28918a
|
||||
conv2d_131.w_0 FLOAT[60,480,1,3] 4db8f8ca1409
|
||||
conv2d_131.w_0_bias FLOAT[60] 457314af9d69
|
||||
conv2d_132.w_0 FLOAT[120,60,1,1] 01422e4c500f
|
||||
conv2d_132.w_0_bias FLOAT[120] 679f5bb1fb07
|
||||
conv2d_133.w_0 FLOAT[480,120,1,1] ae210aedaa54
|
||||
conv2d_133.w_0_bias FLOAT[480] 7a6d0ccda933
|
||||
conv2d_134.w_0 FLOAT[60,960,1,3] 0c5f2486941f
|
||||
conv2d_134.w_0_bias FLOAT[60] 683a819c0aee
|
||||
conv2d_135.w_0 FLOAT[120,60,1,1] 6277cef6d6e5
|
||||
conv2d_135.w_0_bias FLOAT[120] cac86cfe5616
|
||||
conv2d_136.w_0_lab FLOAT[16,1,3,3] 7af9aca8c874
|
||||
conv2d_137.w_0_lab_lab FLOAT[32,16,1,1] e410e1bbe640
|
||||
conv2d_138.w_0_lab_laboffset FLOAT[] 3a78f3460e42
|
||||
conv2d_138.w_0_lab_labscale FLOAT[32,1,3,3] 7b28e65e824b
|
||||
conv2d_139.w_0_lab_lab FLOAT[64,32,1,1] a88ecd6492ae
|
||||
conv2d_140.w_0_lab_laboffset FLOAT[] 1c6941fb9da9
|
||||
conv2d_140.w_0_lab_labscale FLOAT[64,1,3,3] e8f61cb6ee8c
|
||||
conv2d_141.w_0_lab_lab FLOAT[64,64,1,1] b233317f3473
|
||||
conv2d_142.w_0_lab_laboffset FLOAT[] ae3c8b684181
|
||||
conv2d_142.w_0_lab_labscale FLOAT[64,1,3,3] 3a0bdcb15a87
|
||||
conv2d_143.w_0_lab_lab FLOAT[128,64,1,1] f22020933f0b
|
||||
conv2d_144.w_0_lab_laboffset FLOAT[] f63f258a3f9d
|
||||
conv2d_144.w_0_lab_labscale FLOAT[128,1,3,3] aaf38724e6c7
|
||||
conv2d_145.w_0_lab_lab FLOAT[128,128,1,1] d31f4b828e59
|
||||
conv2d_146.w_0_lab_laboffset FLOAT[] c09547b7e0bc
|
||||
conv2d_146.w_0_lab_labscale FLOAT[128,1,3,3] 87ba7579579e
|
||||
conv2d_147.w_0_lab_lab FLOAT[240,128,1,1] 040ff71cb5e9
|
||||
conv2d_148.w_0_lab_laboffset FLOAT[] 8a7debbc506a
|
||||
conv2d_148.w_0_lab_labscale FLOAT[240,1,5,5] 61e4d6b6955f
|
||||
conv2d_149.w_0_lab_lab FLOAT[240,240,1,1] 689b6a80c84e
|
||||
conv2d_150.w_0_lab_laboffset FLOAT[] 4267a796c1be
|
||||
conv2d_150.w_0_lab_labscale FLOAT[240,1,5,5] bdf274685fd7
|
||||
conv2d_151.w_0_lab_lab FLOAT[240,240,1,1] 8f1990d1e528
|
||||
conv2d_152.w_0_lab_laboffset FLOAT[] 088a3d94cd8e
|
||||
conv2d_152.w_0_lab_labscale FLOAT[240,1,5,5] 3f7d21db5289
|
||||
conv2d_153.w_0_lab_lab FLOAT[240,240,1,1] 985af983a13b
|
||||
conv2d_154.w_0_lab_laboffset FLOAT[] e4df6676727a
|
||||
conv2d_154.w_0_lab_labscale FLOAT[240,1,5,5] cce264a1bf5b
|
||||
conv2d_155.w_0_lab_lab FLOAT[240,240,1,1] 3936573f5b14
|
||||
conv2d_156.w_0_lab_laboffset FLOAT[] 57c234324d12
|
||||
conv2d_156.w_0_lab_labscale FLOAT[240,1,5,5] abed3f84de8e
|
||||
conv2d_157.w_0_lab FLOAT[480,240,1,1] cabd47e396e6
|
||||
conv2d_158.w_0_lab_laboffset FLOAT[] 0775db21b349
|
||||
conv2d_158.w_0_lab_labscale FLOAT[480,1,5,5] 93184cc8d5b5
|
||||
conv2d_159.w_0_lab FLOAT[480,480,1,1] 6f937a862a36
|
||||
conv2d_160.w_0_lab_laboffset FLOAT[] aee4b2f0c75f
|
||||
conv2d_160.w_0_lab_labscale FLOAT[480,1,5,5] be5da1909e98
|
||||
conv2d_161.w_0_lab_lab FLOAT[480,480,1,1] 909ffe466795
|
||||
conv2d_162.w_0_lab_laboffset FLOAT[] bca50107f55a
|
||||
conv2d_162.w_0_lab_labscale FLOAT[480,1,5,5] 557116ffeb12
|
||||
conv2d_163.w_0_lab_lab FLOAT[480,480,1,1] 4ff91a197915
|
||||
conv2d_96.w_0 FLOAT[60,240,1,1] c603f4303bcf
|
||||
conv2d_97.w_0 FLOAT[240,60,1,1] 6c322f4033f3
|
||||
helper.constant.9 INT64[1] d86e8112f3c4
|
||||
helper.reshape.0 FLOAT[120] 0095c8fb9231
|
||||
helper.reshape.1 FLOAT[120] d9b5d7daa6c7
|
||||
helper.reshape.2 FLOAT[120] 735434d89c32
|
||||
helper.reshape.3 FLOAT[120] 1c19d766d3bd
|
||||
helper.reshape.4 FLOAT[120] b574066219c4
|
||||
helper.reshape.5 FLOAT[120] bcc08e54e9ad
|
||||
helper.reshape.6 FLOAT[120] 66819650665e
|
||||
helper.reshape.7 FLOAT[120] 1cc22c67b6f4
|
||||
helper.reshape.8 FLOAT[120] f9856686d3cc
|
||||
helper.reshape.9 FLOAT[120] 2c3b96027c2d
|
||||
learnable_affine_block_41.w_0 FLOAT[1] 9de26120cb27
|
||||
learnable_affine_block_41.w_1 FLOAT[1] 01f546f5d9c1
|
||||
learnable_affine_block_45.w_0 FLOAT[1] 18964e40f39f
|
||||
learnable_affine_block_45.w_1 FLOAT[1] 870cb3edcce3
|
||||
learnable_affine_block_55.w_0 FLOAT[1] 6f2e06ffa755
|
||||
learnable_affine_block_55.w_1 FLOAT[1] 239d0ba581f0
|
||||
linear_0.b_0_qkv_scaled FLOAT[360] 644ab5085a9f
|
||||
linear_0.w_0_qkv_scaled FLOAT[120,360] e1c6d2e0352a
|
||||
linear_1.b_0 FLOAT[120] 75263760bd2d
|
||||
linear_1.w_0 FLOAT[120,120] 4e92c5e77476
|
||||
linear_2.b_0 FLOAT[240] edd5e04f654b
|
||||
linear_2.w_0 FLOAT[120,240] 70c07aa7230d
|
||||
linear_3.b_0 FLOAT[120] ab01989d92ff
|
||||
linear_3.w_0 FLOAT[240,120] 61f8188c6be7
|
||||
linear_4.b_0_qkv_scaled FLOAT[360] 7e9579850b64
|
||||
linear_4.w_0_qkv_scaled FLOAT[120,360] 24034a7ab871
|
||||
linear_5.b_0 FLOAT[120] b26cbbf72625
|
||||
linear_5.w_0 FLOAT[120,120] 9ba4a0b337d6
|
||||
linear_6.b_0 FLOAT[240] 2513e15a93fd
|
||||
linear_6.w_0 FLOAT[120,240] 64e22f8d498f
|
||||
linear_7.b_0 FLOAT[120] 48ed05325c44
|
||||
linear_7.w_0 FLOAT[240,120] f7153a4cd64a
|
||||
linear_8.b_0 FLOAT[356] e727efeddb80
|
||||
linear_8.w_0 FLOAT[120,356] efa7dcd8490d
|
||||
p2o.pd_op.conv2d.1.0_bias_lab_lab FLOAT[32] 616b103a4c85
|
||||
p2o.pd_op.conv2d.10.0_bias_lab_lab FLOAT[240] 2006e0f76fe2
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[60] c92217c217a7
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[240] 5250bdab6caf
|
||||
p2o.pd_op.conv2d.13.0_bias_lab FLOAT[480] b8886bea7fd7
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[120] da9616e99771
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[480] 3aa799e43ed4
|
||||
p2o.pd_op.conv2d.16.0_bias_lab FLOAT[480] 45660288e4bd
|
||||
p2o.pd_op.conv2d.17.0_bias_lab_lab FLOAT[480] 1f6294521f37
|
||||
p2o.pd_op.conv2d.18.0_bias_lab_lab FLOAT[480] deb3473ea941
|
||||
p2o.pd_op.conv2d.2.0_bias_lab_lab FLOAT[64] 73e831ae4c0f
|
||||
p2o.pd_op.conv2d.3.0_bias_lab_lab FLOAT[64] eb65b01e566d
|
||||
p2o.pd_op.conv2d.4.0_bias_lab_lab FLOAT[128] 05dec2b4e10b
|
||||
p2o.pd_op.conv2d.5.0_bias_lab_lab FLOAT[128] 7fdbf36b03ae
|
||||
p2o.pd_op.conv2d.6.0_bias_lab_lab FLOAT[240] d73ef2bcadb2
|
||||
p2o.pd_op.conv2d.7.0_bias_lab_lab FLOAT[240] aec19626a5cf
|
||||
p2o.pd_op.conv2d.8.0_bias_lab_lab FLOAT[240] a18736b71e73
|
||||
p2o.pd_op.conv2d.9.0_bias_lab_lab FLOAT[240] 11f4ab091e88
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias_lab FLOAT[16] 55a2996ca924
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias_lab FLOAT[32] 5f93417b4004
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias_lab FLOAT[240] 7d623c0cd4a1
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias_lab FLOAT[480] 4edc79a5d06a
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias_lab FLOAT[480] 483305797ea2
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias_lab FLOAT[480] 6bb53d674965
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias_lab FLOAT[64] 8e7213902738
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias_lab FLOAT[64] 3f1dd10783d6
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias_lab FLOAT[128] 8f6f999e5b66
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias_lab FLOAT[128] f1eed07fd46f
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias_lab FLOAT[240] afde38d0389b
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias_lab FLOAT[240] 3313b0debcf8
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias_lab FLOAT[240] 2f5f53adb8f8
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias_lab FLOAT[240] 2480b8f9be30
|
||||
rec_unsqueeze_axis INT64[1] 7c9fa136d441
|
||||
@@ -0,0 +1,468 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,192,unk__22,unk__23] "Add.105"
|
||||
float[batch,192,unk__22,unk__23] "Add.111"
|
||||
float[batch,192,unk__42,unk__43] "Add.117"
|
||||
float[batch,48,1,1] "Add.119"
|
||||
float[batch,192,1,1] "Add.121"
|
||||
float[batch,384,unk__42,unk__43] "Add.125"
|
||||
float[batch,384,unk__42,unk__43] "Add.131"
|
||||
float[batch,384,unk__42,unk__43] "Add.133"
|
||||
float[batch,96,1,1] "Add.135"
|
||||
float[batch,384,1,1] "Add.137"
|
||||
float[batch,384,unk__42,unk__43] "Add.141"
|
||||
float[batch,384,unk__42,unk__43] "Add.147"
|
||||
float[batch,32,unk__6,unk__7] "Add.15"
|
||||
float[batch,384,unk__42,unk__43] "Add.153"
|
||||
float[batch,384,unk__42,unk__43] "Add.159"
|
||||
float[batch,384,unk__42,unk__43] "Add.165"
|
||||
float[batch,96,unk__42,unk__43] "Add.181"
|
||||
float[batch,96,unk__22,unk__23] "Add.187"
|
||||
float[batch,48,unk__6,unk__7] "Add.19"
|
||||
float[batch,96,unk__14,unk__15] "Add.193"
|
||||
float[batch,96,unk__6,unk__7] "Add.199"
|
||||
float[batch,96,unk__22,unk__23] "Add.201"
|
||||
float[batch,96,unk__14,unk__15] "Add.203"
|
||||
float[batch,96,unk__6,unk__7] "Add.205"
|
||||
float[batch,24,unk__42,unk__43] "Add.211"
|
||||
float[batch,24,unk__22,unk__23] "Add.217"
|
||||
float[batch,24,unk__14,unk__15] "Add.223"
|
||||
float[batch,24,unk__6,unk__7] "Add.229"
|
||||
float[batch,1,height,width] "Add.233"
|
||||
float[batch,48,unk__6,unk__7] "Add.25"
|
||||
float[batch,16,unk__0,unk__1] "Add.3"
|
||||
float[batch,48,unk__6,unk__7] "Add.31"
|
||||
float[batch,48,unk__14,unk__15] "Add.37"
|
||||
float[batch,96,unk__14,unk__15] "Add.41"
|
||||
float[batch,96,unk__14,unk__15] "Add.47"
|
||||
float[batch,96,unk__14,unk__15] "Add.53"
|
||||
float[batch,96,unk__22,unk__23] "Add.59"
|
||||
float[batch,192,unk__22,unk__23] "Add.63"
|
||||
float[batch,192,unk__22,unk__23] "Add.69"
|
||||
float[batch,192,unk__22,unk__23] "Add.75"
|
||||
float[batch,192,unk__22,unk__23] "Add.81"
|
||||
float[batch,192,unk__22,unk__23] "Add.87"
|
||||
float[batch,32,unk__0,unk__1] "Add.9"
|
||||
float[batch,192,unk__22,unk__23] "Add.93"
|
||||
float[batch,192,unk__22,unk__23] "Add.99"
|
||||
float[batch,96,unk__6,unk__7] "Concat.1"
|
||||
float[batch,192,unk__42,unk__43] "Mul.77"
|
||||
float[batch,384,unk__42,unk__43] "Mul.85"
|
||||
float[batch,384,unk__42,unk__43] "Mul.87"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,96,unk__42,unk__43] "p2o.pd_op.conv2d.23.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.conv2d.26.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.conv2d.29.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.conv2d.32.0"
|
||||
float[batch,24,unk__42,unk__43] "p2o.pd_op.conv2d.35.0"
|
||||
float[batch,24,unk__22,unk__23] "p2o.pd_op.conv2d.38.0"
|
||||
float[batch,24,unk__14,unk__15] "p2o.pd_op.conv2d.41.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.conv2d.44.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.hardswish.0.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.hardswish.1.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.10.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.11.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.12.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.13.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.14.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.15.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.16.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.17.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.18.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.19.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.2.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.20.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.21.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.22.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.23.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.3.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.4.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.5.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.6.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.7.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.8.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.9.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.pool2d.1.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.2.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.3.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.4.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.5.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.6.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.7.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.8.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.9.0"
|
||||
float[batch,48,1,1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.relu.10.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.relu.11.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.2.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.3.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.4.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.5.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.6.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.7.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.8.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.9.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,96,1,1] se_group0_down
|
||||
float[batch,384,1,1] se_group0_gates
|
||||
float[batch,384,1,1] se_group0_pooled
|
||||
float[batch,96,1,1] se_group0_relu
|
||||
float[batch,384,1,1] se_group0_up
|
||||
float[batch,24,1,1] se_group1_down
|
||||
float[batch,96,1,1] se_group1_gates
|
||||
float[batch,96,1,1] se_group1_pooled
|
||||
float[batch,24,1,1] se_group1_relu
|
||||
float[batch,96,1,1] se_group1_up
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,16,unk__0,unk__1] val_0
|
||||
float[batch,32,unk__0,unk__1] val_1
|
||||
float[batch,96,unk__14,unk__15] val_10
|
||||
float[batch,96,unk__14,unk__15] val_11
|
||||
float[batch,96,unk__14,unk__15] val_12
|
||||
float[batch,192,unk__22,unk__23] val_13
|
||||
float[batch,192,unk__22,unk__23] val_14
|
||||
float[batch,192,unk__22,unk__23] val_15
|
||||
float[batch,192,unk__22,unk__23] val_16
|
||||
float[batch,192,unk__22,unk__23] val_17
|
||||
float[batch,192,unk__22,unk__23] val_18
|
||||
float[batch,192,unk__22,unk__23] val_19
|
||||
float[batch,32,unk__0,unk__1] val_2
|
||||
float[batch,192,unk__22,unk__23] val_20
|
||||
float[batch,192,unk__22,unk__23] val_21
|
||||
float[batch,192,unk__22,unk__23] val_22
|
||||
float[batch,192,unk__22,unk__23] val_23
|
||||
float[batch,192,unk__22,unk__23] val_24
|
||||
float[batch,192,unk__22,unk__23] val_25
|
||||
float[batch,192,unk__22,unk__23] val_26
|
||||
float[batch,384,unk__42,unk__43] val_27
|
||||
float[batch,384,unk__42,unk__43] val_28
|
||||
float[batch,384,unk__42,unk__43] val_29
|
||||
float[batch,48,unk__6,unk__7] val_3
|
||||
float[batch,384,unk__42,unk__43] val_30
|
||||
float[batch,384,unk__42,unk__43] val_31
|
||||
float[batch,384,unk__42,unk__43] val_32
|
||||
float[batch,384,unk__42,unk__43] val_33
|
||||
float[batch,384,unk__42,unk__43] val_34
|
||||
float[batch,384,unk__42,unk__43] val_35
|
||||
float[batch,384,unk__42,unk__43] val_36
|
||||
float[batch,96,1,1] val_37
|
||||
float[batch,96,1,1] val_38
|
||||
float[batch,96,1,1] val_39
|
||||
float[batch,48,unk__6,unk__7] val_4
|
||||
float[batch,96,1,1] val_40
|
||||
float[batch,24,1,1] val_41
|
||||
float[batch,24,1,1] val_42
|
||||
float[batch,24,1,1] val_43
|
||||
float[batch,24,1,1] val_44
|
||||
float[batch,48,unk__6,unk__7] val_5
|
||||
float[batch,48,unk__6,unk__7] val_6
|
||||
float[batch,48,unk__6,unk__7] val_7
|
||||
float[batch,96,unk__14,unk__15] val_8
|
||||
float[batch,96,unk__14,unk__15] val_9
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_0.w_0", "conv2d_0.w_0_bias")
|
||||
"Add.3" = Conv <dilations: ints = [1, 1], group: int = 16, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.0.0", "conv2d_161.w_0_lab", "p2o.pd_op.depthwise_conv2d.0.0_bias_lab")
|
||||
val_0 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.3")
|
||||
"p2o.pd_op.hardswish.0.0" = Mul ("Add.3", val_0)
|
||||
"Add.9" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.0.0", "conv2d_162.w_0_lab_lab", "p2o.pd_op.conv2d.1.0_bias_lab_lab")
|
||||
val_1 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.9")
|
||||
"p2o.pd_op.hardswish.1.0" = Mul ("Add.9", val_1)
|
||||
val_2 = Add ("p2o.pd_op.hardswish.1.0", "conv2d_163.w_0_lab_laboffset")
|
||||
"Add.15" = Conv <dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_2, "conv2d_163.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.1.0_bias_lab")
|
||||
"Add.19" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.15", "conv2d_164.w_0_lab", "p2o.pd_op.conv2d.2.0_bias_lab")
|
||||
val_3 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.19")
|
||||
"p2o.pd_op.hardswish.2.0" = Mul ("Add.19", val_3)
|
||||
val_4 = Add ("p2o.pd_op.hardswish.2.0", "conv2d_165.w_0_lab_laboffset")
|
||||
"Add.25" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_4, "conv2d_165.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.2.0_bias_lab")
|
||||
val_5 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.25")
|
||||
"p2o.pd_op.hardswish.3.0" = Mul ("Add.25", val_5)
|
||||
"Add.31" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.3.0", "conv2d_166.w_0_lab_lab", "p2o.pd_op.conv2d.3.0_bias_lab_lab")
|
||||
val_6 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.31")
|
||||
"p2o.pd_op.hardswish.4.0" = Mul ("Add.31", val_6)
|
||||
val_7 = Add ("p2o.pd_op.hardswish.4.0", "conv2d_167.w_0_lab_laboffset")
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_7, "conv2d_167.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.3.0_bias_lab")
|
||||
"Add.41" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.37", "conv2d_168.w_0_lab", "p2o.pd_op.conv2d.4.0_bias_lab")
|
||||
val_8 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.41")
|
||||
"p2o.pd_op.hardswish.5.0" = Mul ("Add.41", val_8)
|
||||
val_9 = Add ("p2o.pd_op.hardswish.5.0", "conv2d_169.w_0_lab_laboffset")
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_9, "conv2d_169.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.4.0_bias_lab")
|
||||
val_10 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.47")
|
||||
"p2o.pd_op.hardswish.6.0" = Mul ("Add.47", val_10)
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.6.0", "conv2d_170.w_0_lab_lab", "p2o.pd_op.conv2d.5.0_bias_lab_lab")
|
||||
val_11 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.53")
|
||||
"p2o.pd_op.hardswish.7.0" = Mul ("Add.53", val_11)
|
||||
val_12 = Add ("p2o.pd_op.hardswish.7.0", "conv2d_171.w_0_lab_laboffset")
|
||||
"Add.59" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_12, "conv2d_171.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.5.0_bias_lab")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.59", "conv2d_172.w_0_lab", "p2o.pd_op.conv2d.6.0_bias_lab")
|
||||
val_13 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.63")
|
||||
"p2o.pd_op.hardswish.8.0" = Mul ("Add.63", val_13)
|
||||
val_14 = Add ("p2o.pd_op.hardswish.8.0", "conv2d_173.w_0_lab_laboffset")
|
||||
"Add.69" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_14, "conv2d_173.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.6.0_bias_lab")
|
||||
val_15 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.69")
|
||||
"p2o.pd_op.hardswish.9.0" = Mul ("Add.69", val_15)
|
||||
"Add.75" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.9.0", "conv2d_174.w_0_lab_lab", "p2o.pd_op.conv2d.7.0_bias_lab_lab")
|
||||
val_16 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.75")
|
||||
"p2o.pd_op.hardswish.10.0" = Mul ("Add.75", val_16)
|
||||
val_17 = Add ("p2o.pd_op.hardswish.10.0", "conv2d_175.w_0_lab_laboffset")
|
||||
"Add.81" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_17, "conv2d_175.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.7.0_bias_lab")
|
||||
val_18 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.81")
|
||||
"p2o.pd_op.hardswish.11.0" = Mul ("Add.81", val_18)
|
||||
"Add.87" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.11.0", "conv2d_176.w_0_lab_lab", "p2o.pd_op.conv2d.8.0_bias_lab_lab")
|
||||
val_19 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.87")
|
||||
"p2o.pd_op.hardswish.12.0" = Mul ("Add.87", val_19)
|
||||
val_20 = Add ("p2o.pd_op.hardswish.12.0", "conv2d_177.w_0_lab_laboffset")
|
||||
"Add.93" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_20, "conv2d_177.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.8.0_bias_lab")
|
||||
val_21 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.93")
|
||||
"p2o.pd_op.hardswish.13.0" = Mul ("Add.93", val_21)
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.13.0", "conv2d_178.w_0_lab_lab", "p2o.pd_op.conv2d.9.0_bias_lab_lab")
|
||||
val_22 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.99")
|
||||
"p2o.pd_op.hardswish.14.0" = Mul ("Add.99", val_22)
|
||||
val_23 = Add ("p2o.pd_op.hardswish.14.0", "conv2d_179.w_0_lab_laboffset")
|
||||
"Add.105" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_23, "conv2d_179.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.9.0_bias_lab")
|
||||
val_24 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.105")
|
||||
"p2o.pd_op.hardswish.15.0" = Mul ("Add.105", val_24)
|
||||
"Add.111" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.15.0", "conv2d_180.w_0_lab_lab", "p2o.pd_op.conv2d.10.0_bias_lab_lab")
|
||||
val_25 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.111")
|
||||
"p2o.pd_op.hardswish.16.0" = Mul ("Add.111", val_25)
|
||||
val_26 = Add ("p2o.pd_op.hardswish.16.0", "conv2d_181.w_0_lab_laboffset")
|
||||
"Add.117" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [2, 2]> (val_26, "conv2d_181.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.10.0_bias_lab")
|
||||
["GlobalAveragePool.0"] "p2o.pd_op.pool2d.0.0" = GlobalAveragePool ("Add.117")
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.0.0", "conv2d_96.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.119")
|
||||
"Add.121" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_97.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.121")
|
||||
["Mul.76"] "Mul.77" = Mul ("Add.117", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.77", "conv2d_182.w_0_lab", "p2o.pd_op.conv2d.13.0_bias_lab")
|
||||
val_27 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.125")
|
||||
"p2o.pd_op.hardswish.17.0" = Mul ("Add.125", val_27)
|
||||
val_28 = Add ("p2o.pd_op.hardswish.17.0", "conv2d_183.w_0_lab_laboffset")
|
||||
"Add.131" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_28, "conv2d_183.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.11.0_bias_lab")
|
||||
val_29 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.131")
|
||||
"p2o.pd_op.hardswish.18.0" = Mul ("Add.131", val_29)
|
||||
["Mul.84"] "Mul.85" = Mul ("learnable_affine_block_45.w_0", "p2o.pd_op.hardswish.18.0")
|
||||
["Add.132"] "Add.133" = Add ("Mul.85", "learnable_affine_block_45.w_1")
|
||||
["GlobalAveragePool.1"] "p2o.pd_op.pool2d.1.0" = GlobalAveragePool ("Add.133")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.1.0", "conv2d_107.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.135")
|
||||
"Add.137" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_108.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.137")
|
||||
["Mul.86"] "Mul.87" = Mul ("Add.133", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.141" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.87", "conv2d_184.w_0_lab", "p2o.pd_op.conv2d.16.0_bias_lab")
|
||||
val_30 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.141")
|
||||
"p2o.pd_op.hardswish.19.0" = Mul ("Add.141", val_30)
|
||||
val_31 = Add ("p2o.pd_op.hardswish.19.0", "conv2d_185.w_0_lab_laboffset")
|
||||
"Add.147" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_31, "conv2d_185.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.12.0_bias_lab")
|
||||
val_32 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.147")
|
||||
"p2o.pd_op.hardswish.20.0" = Mul ("Add.147", val_32)
|
||||
"Add.153" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.20.0", "conv2d_186.w_0_lab_lab", "p2o.pd_op.conv2d.17.0_bias_lab_lab")
|
||||
val_33 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.153")
|
||||
"p2o.pd_op.hardswish.21.0" = Mul ("Add.153", val_33)
|
||||
val_34 = Add ("p2o.pd_op.hardswish.21.0", "conv2d_187.w_0_lab_laboffset")
|
||||
"Add.159" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_34, "conv2d_187.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.13.0_bias_lab")
|
||||
val_35 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.159")
|
||||
"p2o.pd_op.hardswish.22.0" = Mul ("Add.159", val_35)
|
||||
"Add.165" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.22.0", "conv2d_188.w_0_lab_lab", "p2o.pd_op.conv2d.18.0_bias_lab_lab")
|
||||
val_36 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.165")
|
||||
"p2o.pd_op.hardswish.23.0" = Mul ("Add.165", val_36)
|
||||
"p2o.pd_op.conv2d.23.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.23.0", "Conv.37_folded_w_lab", "Conv.37_folded_b_lab")
|
||||
["GlobalAveragePool.2"] "p2o.pd_op.pool2d.2.0" = GlobalAveragePool ("p2o.pd_op.conv2d.23.0")
|
||||
"p2o.pd_op.conv2d.26.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_26, "Conv.40_folded_w_labscale", "Conv.40_folded_b")
|
||||
["GlobalAveragePool.3"] "p2o.pd_op.pool2d.3.0" = GlobalAveragePool ("p2o.pd_op.conv2d.26.0")
|
||||
"p2o.pd_op.conv2d.29.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_12, "Conv.43_folded_w_labscale", "Conv.43_folded_b")
|
||||
["GlobalAveragePool.4"] "p2o.pd_op.pool2d.4.0" = GlobalAveragePool ("p2o.pd_op.conv2d.29.0")
|
||||
"p2o.pd_op.conv2d.32.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_7, "Conv.46_folded_w_labscale", "Conv.46_folded_b")
|
||||
["GlobalAveragePool.5"] "p2o.pd_op.pool2d.5.0" = GlobalAveragePool ("p2o.pd_op.conv2d.32.0")
|
||||
se_group0_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.2.0", "p2o.pd_op.pool2d.3.0", "p2o.pd_op.pool2d.4.0", "p2o.pd_op.pool2d.5.0")
|
||||
se_group0_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_pooled, se_group0_down1, se_group0_down2)
|
||||
se_group0_relu = Relu (se_group0_down)
|
||||
se_group0_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_relu, se_group0_up1, se_group0_up2)
|
||||
se_group0_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group0_up)
|
||||
"se_group0_p2o.pd_op.hardsigmoid.2.0", "se_group0_p2o.pd_op.hardsigmoid.3.0", "se_group0_p2o.pd_op.hardsigmoid.4.0", "se_group0_p2o.pd_op.hardsigmoid.5.0" = Split <axis: int = 1> (se_group0_gates, se_group0_sizes)
|
||||
val_37 = Add ("se_group0_p2o.pd_op.hardsigmoid.2.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.181" = Mul ("p2o.pd_op.conv2d.23.0", val_37)
|
||||
val_38 = Add ("se_group0_p2o.pd_op.hardsigmoid.3.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.187" = Mul ("p2o.pd_op.conv2d.26.0", val_38)
|
||||
val_39 = Add ("se_group0_p2o.pd_op.hardsigmoid.4.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.193" = Mul ("p2o.pd_op.conv2d.29.0", val_39)
|
||||
val_40 = Add ("se_group0_p2o.pd_op.hardsigmoid.5.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.199" = Mul ("p2o.pd_op.conv2d.32.0", val_40)
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.181", "helper.constant.1", "helper.constant.0")
|
||||
["Add.200"] "Add.201" = Add ("Add.187", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.201", "helper.constant.1", "helper.constant.0")
|
||||
["Add.202"] "Add.203" = Add ("Add.193", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.203", "helper.constant.1", "helper.constant.0")
|
||||
["Add.204"] "Add.205" = Add ("Add.199", "p2o.pd_op.nearest_interp.2.0")
|
||||
["Conv.49"] "p2o.pd_op.conv2d.35.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.181", "conv2d_156.w_0")
|
||||
["GlobalAveragePool.6"] "p2o.pd_op.pool2d.6.0" = GlobalAveragePool ("p2o.pd_op.conv2d.35.0")
|
||||
["Conv.52"] "p2o.pd_op.conv2d.38.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.201", "conv2d_150.w_0")
|
||||
["GlobalAveragePool.7"] "p2o.pd_op.pool2d.7.0" = GlobalAveragePool ("p2o.pd_op.conv2d.38.0")
|
||||
["Conv.55"] "p2o.pd_op.conv2d.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.203", "conv2d_144.w_0")
|
||||
["GlobalAveragePool.8"] "p2o.pd_op.pool2d.8.0" = GlobalAveragePool ("p2o.pd_op.conv2d.41.0")
|
||||
["Conv.58"] "p2o.pd_op.conv2d.44.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.205", "conv2d_138.w_0")
|
||||
["GlobalAveragePool.9"] "p2o.pd_op.pool2d.9.0" = GlobalAveragePool ("p2o.pd_op.conv2d.44.0")
|
||||
se_group1_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.6.0", "p2o.pd_op.pool2d.7.0", "p2o.pd_op.pool2d.8.0", "p2o.pd_op.pool2d.9.0")
|
||||
se_group1_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_pooled, se_group1_down1, se_group1_down2)
|
||||
se_group1_relu = Relu (se_group1_down)
|
||||
se_group1_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_relu, se_group1_up1, se_group1_up2)
|
||||
se_group1_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group1_up)
|
||||
"se_group1_p2o.pd_op.hardsigmoid.6.0", "se_group1_p2o.pd_op.hardsigmoid.7.0", "se_group1_p2o.pd_op.hardsigmoid.8.0", "se_group1_p2o.pd_op.hardsigmoid.9.0" = Split <axis: int = 1> (se_group1_gates, se_group1_sizes)
|
||||
val_41 = Add ("se_group1_p2o.pd_op.hardsigmoid.6.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.211" = Mul ("p2o.pd_op.conv2d.35.0", val_41)
|
||||
val_42 = Add ("se_group1_p2o.pd_op.hardsigmoid.7.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.217" = Mul ("p2o.pd_op.conv2d.38.0", val_42)
|
||||
val_43 = Add ("se_group1_p2o.pd_op.hardsigmoid.8.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.223" = Mul ("p2o.pd_op.conv2d.41.0", val_43)
|
||||
val_44 = Add ("se_group1_p2o.pd_op.hardsigmoid.9.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.229" = Mul ("p2o.pd_op.conv2d.44.0", val_44)
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.211", "helper.constant.1", "helper.constant.6")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.217", "helper.constant.1", "helper.constant.8")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.223", "helper.constant.1", "helper.constant.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.229")
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.1", "conv2d_159.w_0", "conv2d_159.w_0_bias")
|
||||
["Relu.10"] "p2o.pd_op.relu.10.0" = Relu ("p2o.pd_op.batch_norm_.1.0")
|
||||
"p2o.pd_op.batch_norm_.2.0" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.10.0", "auto.cast.57", "ConvTranspose.1_bias")
|
||||
["Relu.11"] "p2o.pd_op.relu.11.0" = Relu ("p2o.pd_op.batch_norm_.2.0")
|
||||
"Add.233" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.11.0", "auto.cast.60", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] fetch_name_0 = Sigmoid ("Add.233")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
Conv.37_folded_b_lab FLOAT[96] 0d571951a1e0
|
||||
Conv.37_folded_w_lab FLOAT[96,384,1,1] 1d0305563ea7
|
||||
Conv.40_folded_b FLOAT[96] dcfdd514912d
|
||||
Conv.40_folded_w_labscale FLOAT[96,192,1,1] bacc8274202e
|
||||
Conv.43_folded_b FLOAT[96] ee902cf71aad
|
||||
Conv.43_folded_w_labscale FLOAT[96,96,1,1] b17e08485dc5
|
||||
Conv.46_folded_b FLOAT[96] 6541e510a35d
|
||||
Conv.46_folded_w_labscale FLOAT[96,48,1,1] 9423b2c0951a
|
||||
ConvTranspose.1_bias FLOAT[24] 64cabf62980d
|
||||
ConvTranspose.3_bias FLOAT[1] 55c86fee1edb
|
||||
auto.cast.57 FLOAT[24,24,2,2] 1dc864bec64f
|
||||
auto.cast.60 FLOAT[24,1,2,2] c9862b3a19bc
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_0.w_0 FLOAT[16,3,3,3] 7841f2f3efae
|
||||
conv2d_0.w_0_bias FLOAT[16] 2713bf453fd1
|
||||
conv2d_107.w_0 FLOAT[96,384,1,1] 2fc401aa1ec6
|
||||
conv2d_108.w_0 FLOAT[384,96,1,1] f2a9a9261c07
|
||||
conv2d_138.w_0 FLOAT[24,96,3,3] 47aa8ba1db50
|
||||
conv2d_144.w_0 FLOAT[24,96,3,3] cd85b03c436c
|
||||
conv2d_150.w_0 FLOAT[24,96,3,3] 591f14004ce0
|
||||
conv2d_156.w_0 FLOAT[24,96,3,3] 5e0bc4bf821e
|
||||
conv2d_159.w_0 FLOAT[24,96,3,3] 43b6b1b17bef
|
||||
conv2d_159.w_0_bias FLOAT[24] c98267f8273d
|
||||
conv2d_161.w_0_lab FLOAT[16,1,3,3] 22528d709d37
|
||||
conv2d_162.w_0_lab_lab FLOAT[32,16,1,1] 051645505e21
|
||||
conv2d_163.w_0_lab_laboffset FLOAT[] 92a142f7dc41
|
||||
conv2d_163.w_0_lab_labscale FLOAT[32,1,3,3] 8694842bd3fb
|
||||
conv2d_164.w_0_lab FLOAT[48,32,1,1] 0c937f040d0e
|
||||
conv2d_165.w_0_lab_laboffset FLOAT[] 012179917694
|
||||
conv2d_165.w_0_lab_labscale FLOAT[48,1,3,3] 7d779e5616fa
|
||||
conv2d_166.w_0_lab_lab FLOAT[48,48,1,1] d70c86b2d1ec
|
||||
conv2d_167.w_0_lab_laboffset FLOAT[] 9741b37d98e3
|
||||
conv2d_167.w_0_lab_labscale FLOAT[48,1,3,3] fa2e1db2eb62
|
||||
conv2d_168.w_0_lab FLOAT[96,48,1,1] 81e13e0bd382
|
||||
conv2d_169.w_0_lab_laboffset FLOAT[] f3e015d53e9a
|
||||
conv2d_169.w_0_lab_labscale FLOAT[96,1,3,3] 75bbb69deb68
|
||||
conv2d_170.w_0_lab_lab FLOAT[96,96,1,1] 59b22a69e345
|
||||
conv2d_171.w_0_lab_laboffset FLOAT[] f42328163f40
|
||||
conv2d_171.w_0_lab_labscale FLOAT[96,1,3,3] 65cbca6287a2
|
||||
conv2d_172.w_0_lab FLOAT[192,96,1,1] ff93ca701d2f
|
||||
conv2d_173.w_0_lab_laboffset FLOAT[] b76450d3656f
|
||||
conv2d_173.w_0_lab_labscale FLOAT[192,1,5,5] 28d7de00679c
|
||||
conv2d_174.w_0_lab_lab FLOAT[192,192,1,1] 53cf6f343ec2
|
||||
conv2d_175.w_0_lab_laboffset FLOAT[] e665434a5d2d
|
||||
conv2d_175.w_0_lab_labscale FLOAT[192,1,5,5] 3c0aa815839d
|
||||
conv2d_176.w_0_lab_lab FLOAT[192,192,1,1] cb45f031f07b
|
||||
conv2d_177.w_0_lab_laboffset FLOAT[] e095ffc76247
|
||||
conv2d_177.w_0_lab_labscale FLOAT[192,1,5,5] 22fe03b75591
|
||||
conv2d_178.w_0_lab_lab FLOAT[192,192,1,1] c259022f5c3d
|
||||
conv2d_179.w_0_lab_laboffset FLOAT[] 5842420f0e64
|
||||
conv2d_179.w_0_lab_labscale FLOAT[192,1,5,5] 408bbab0d507
|
||||
conv2d_180.w_0_lab_lab FLOAT[192,192,1,1] 85871ea30bf1
|
||||
conv2d_181.w_0_lab_laboffset FLOAT[] 9e0407355f14
|
||||
conv2d_181.w_0_lab_labscale FLOAT[192,1,5,5] 75764b0f5265
|
||||
conv2d_182.w_0_lab FLOAT[384,192,1,1] 81235d1a972f
|
||||
conv2d_183.w_0_lab_laboffset FLOAT[] e648d792317a
|
||||
conv2d_183.w_0_lab_labscale FLOAT[384,1,5,5] f5341adaad28
|
||||
conv2d_184.w_0_lab FLOAT[384,384,1,1] c37a7cec640b
|
||||
conv2d_185.w_0_lab_laboffset FLOAT[] 768fa13da14b
|
||||
conv2d_185.w_0_lab_labscale FLOAT[384,1,5,5] 6bacb713155c
|
||||
conv2d_186.w_0_lab_lab FLOAT[384,384,1,1] 2fa80ae1b18f
|
||||
conv2d_187.w_0_lab_laboffset FLOAT[] ad505dafbd90
|
||||
conv2d_187.w_0_lab_labscale FLOAT[384,1,5,5] a221bd8406f2
|
||||
conv2d_188.w_0_lab_lab FLOAT[384,384,1,1] 9ea062b2f1b4
|
||||
conv2d_96.w_0 FLOAT[48,192,1,1] 6d73ce1fb738
|
||||
conv2d_97.w_0 FLOAT[192,48,1,1] 8098a00a81f0
|
||||
helper.constant.0 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.1 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.6 FLOAT[4] cf5451a623be
|
||||
helper.constant.8 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
learnable_affine_block_45.w_0 FLOAT[1] 65444e550b77
|
||||
learnable_affine_block_45.w_1 FLOAT[1] f2ee18a061af
|
||||
p2o.pd_op.conv2d.1.0_bias_lab_lab FLOAT[32] 3f4be24e33b8
|
||||
p2o.pd_op.conv2d.10.0_bias_lab_lab FLOAT[192] e32536500417
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[48] 961ec85108cb
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[192] c348751cbed0
|
||||
p2o.pd_op.conv2d.13.0_bias_lab FLOAT[384] 1b6d0aa0e977
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[96] 7876208c6fb1
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[384] 871907fff11d
|
||||
p2o.pd_op.conv2d.16.0_bias_lab FLOAT[384] fd15d67f1e85
|
||||
p2o.pd_op.conv2d.17.0_bias_lab_lab FLOAT[384] 097f0d068f05
|
||||
p2o.pd_op.conv2d.18.0_bias_lab_lab FLOAT[384] b8e228cae698
|
||||
p2o.pd_op.conv2d.2.0_bias_lab FLOAT[48] 8138a593f8f2
|
||||
p2o.pd_op.conv2d.3.0_bias_lab_lab FLOAT[48] 57128b896e31
|
||||
p2o.pd_op.conv2d.4.0_bias_lab FLOAT[96] d2230ff7a27e
|
||||
p2o.pd_op.conv2d.5.0_bias_lab_lab FLOAT[96] 05b9a5f236b6
|
||||
p2o.pd_op.conv2d.6.0_bias_lab FLOAT[192] a990b3fed4dd
|
||||
p2o.pd_op.conv2d.7.0_bias_lab_lab FLOAT[192] 74df3e4f22b6
|
||||
p2o.pd_op.conv2d.8.0_bias_lab_lab FLOAT[192] 9c072f4b4032
|
||||
p2o.pd_op.conv2d.9.0_bias_lab_lab FLOAT[192] 8f6e7021fe63
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias_lab FLOAT[16] 5b3de9e3f7c2
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias_lab FLOAT[32] bb4239a962eb
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias_lab FLOAT[192] 81ac3c08eae1
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias_lab FLOAT[384] 2236a6b52e38
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias_lab FLOAT[384] 14c22d416e3b
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias_lab FLOAT[384] 4eebd04fbeb4
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias_lab FLOAT[48] aaee6f6db9c1
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias_lab FLOAT[48] dcc78f972645
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias_lab FLOAT[96] dbd763cef105
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias_lab FLOAT[96] 5849d6801824
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias_lab FLOAT[192] 01e9219938aa
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias_lab FLOAT[192] e35d55fdac89
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias_lab FLOAT[192] fd7c6cc0a8fb
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias_lab FLOAT[192] aedc2ab77e2b
|
||||
p2o.pd_op.hardsigmoid.2.0_one FLOAT[] e00e5eb94441
|
||||
se_group0_down1 FLOAT[96,96,1,1] 4c8c888b01f2
|
||||
se_group0_down2 FLOAT[96] b99146f86442
|
||||
se_group0_sizes INT64[4] 4bb249469bee
|
||||
se_group0_up1 FLOAT[384,24,1,1] 1446892243f3
|
||||
se_group0_up2 FLOAT[384] 8538540d9317
|
||||
se_group1_down1 FLOAT[24,24,1,1] 01a670ee8021
|
||||
se_group1_down2 FLOAT[24] 7f8067be0db7
|
||||
se_group1_sizes INT64[4] 5c995dc6a0ef
|
||||
se_group1_up1 FLOAT[96,6,1,1] 3e47b305535b
|
||||
se_group1_up2 FLOAT[96] ed3a93d396c3
|
||||
@@ -0,0 +1,975 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20],
|
||||
metadata_props: ["character": "0
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
à
|
||||
á
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
Ρ
|
||||
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|
||||
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|
||||
Υ
|
||||
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|
||||
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|
||||
Ψ
|
||||
Ω
|
||||
α
|
||||
β
|
||||
γ
|
||||
δ
|
||||
ε
|
||||
ζ
|
||||
η
|
||||
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|
||||
ι
|
||||
κ
|
||||
λ
|
||||
μ
|
||||
ν
|
||||
ξ
|
||||
ο
|
||||
π
|
||||
ρ
|
||||
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|
||||
ς
|
||||
τ
|
||||
υ
|
||||
φ
|
||||
χ
|
||||
ψ
|
||||
ω
|
||||
Å
|
||||
ℏ
|
||||
⌀
|
||||
⍺
|
||||
⍵
|
||||
𝑢
|
||||
𝜓
|
||||
०
|
||||
‥
|
||||
︽
|
||||
﹥
|
||||
•
|
||||
÷
|
||||
∕
|
||||
∙
|
||||
⋅
|
||||
·
|
||||
±
|
||||
∓
|
||||
∟
|
||||
∠
|
||||
∡
|
||||
∢
|
||||
℧
|
||||
☺
|
||||
"]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,48,width,3] image) => (int32[batch,seq] ctc_indices, float[batch,seq] ctc_confidence)
|
||||
<
|
||||
float[batch,240,12,unk__11] "Add.105"
|
||||
float[batch,240,12,unk__11] "Add.111"
|
||||
float[batch,240,12,unk__11] "Add.117"
|
||||
float[batch,240,6,unk__11] "Add.123"
|
||||
float[batch,240,6,unk__11] "Add.125"
|
||||
float[batch,60,1,1] "Add.127"
|
||||
float[batch,240,1,1] "Add.129"
|
||||
float[batch,480,6,unk__11] "Add.133"
|
||||
float[batch,480,6,unk__11] "Add.139"
|
||||
float[batch,480,6,unk__11] "Add.141"
|
||||
float[batch,120,1,1] "Add.143"
|
||||
float[batch,480,1,1] "Add.145"
|
||||
float[batch,480,6,unk__11] "Add.149"
|
||||
float[batch,32,24,unk__0] "Add.15"
|
||||
float[batch,480,3,unk__11] "Add.155"
|
||||
float[batch,480,3,unk__11] "Add.161"
|
||||
float[batch,480,3,unk__11] "Add.167"
|
||||
float[batch,480,3,unk__11] "Add.173"
|
||||
float[batch,seq,120] "Add.181"
|
||||
float[batch,seq,360] "Add.183"
|
||||
float[batch,8,seq,15] "Add.183_k"
|
||||
float[batch,8,seq,15] "Add.183_q"
|
||||
float[batch,seq,24,15] "Add.183_qkv"
|
||||
float[batch,24,seq,15] "Add.183_qkv_heads"
|
||||
float[batch,8,seq,15] "Add.183_v"
|
||||
float[batch,seq,120] "Add.185"
|
||||
float[batch,seq,120] "Add.187"
|
||||
float[batch,seq,120] "Add.191"
|
||||
float[batch,seq,240] "Add.193"
|
||||
float[batch,seq,120] "Add.195"
|
||||
float[batch,seq,120] "Add.197"
|
||||
float[batch,seq,120] "Add.201"
|
||||
float[batch,seq,360] "Add.203"
|
||||
float[batch,8,seq,15] "Add.203_k"
|
||||
float[batch,8,seq,15] "Add.203_q"
|
||||
float[batch,seq,24,15] "Add.203_qkv"
|
||||
float[batch,24,seq,15] "Add.203_qkv_heads"
|
||||
float[batch,8,seq,15] "Add.203_v"
|
||||
float[batch,seq,120] "Add.205"
|
||||
float[batch,seq,120] "Add.207"
|
||||
float[batch,64,24,unk__0] "Add.21"
|
||||
float[batch,seq,120] "Add.211"
|
||||
float[batch,seq,240] "Add.213"
|
||||
float[batch,seq,120] "Add.215"
|
||||
float[batch,seq,120] "Add.217"
|
||||
float[batch,seq,120] "Add.221"
|
||||
float[batch,seq,438] "Add.223"
|
||||
float[batch,64,24,unk__0] "Add.27"
|
||||
float[batch,16,24,unk__0] "Add.3"
|
||||
float[batch,64,24,unk__0] "Add.33"
|
||||
float[batch,64,12,unk__0] "Add.39"
|
||||
float[batch,128,12,unk__0] "Add.45"
|
||||
float[batch,128,12,unk__0] "Add.51"
|
||||
float[batch,128,12,unk__0] "Add.57"
|
||||
float[batch,128,12,unk__11] "Add.63"
|
||||
float[batch,240,12,unk__11] "Add.69"
|
||||
float[batch,240,12,unk__11] "Add.75"
|
||||
float[batch,240,12,unk__11] "Add.81"
|
||||
float[batch,240,12,unk__11] "Add.87"
|
||||
float[batch,32,24,unk__0] "Add.9"
|
||||
float[batch,240,12,unk__11] "Add.93"
|
||||
float[batch,240,12,unk__11] "Add.99"
|
||||
float[batch,960,1,seq] "Concat.4"
|
||||
float[batch,240,6,unk__11] "Mul.83"
|
||||
float[batch,240,6,unk__11] "Mul.85"
|
||||
float[batch,480,6,unk__11] "Mul.93"
|
||||
float[batch,480,6,unk__11] "Mul.95"
|
||||
float[batch,60,1,seq] "Sigmoid.1"
|
||||
float[batch,60,1,seq] "Sigmoid.11"
|
||||
float[batch,120,1,seq] "Sigmoid.13"
|
||||
float[batch,120,1,seq] "Sigmoid.3"
|
||||
float[batch,seq,240] "Sigmoid.5"
|
||||
float[batch,seq,240] "Sigmoid.7"
|
||||
float[batch,480,1,seq] "Sigmoid.9"
|
||||
float[batch,16,24,unk__0] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,60,1,seq] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,120,1,seq] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,480,1,seq] "p2o.pd_op.batch_norm_.3.0"
|
||||
float[batch,60,1,seq] "p2o.pd_op.batch_norm_.4.0"
|
||||
float[batch,120,1,seq] "p2o.pd_op.batch_norm_.5.0"
|
||||
float[batch,120,seq] "p2o.pd_op.flatten.0.0"
|
||||
float[batch,240,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,480,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,16,24,unk__0] "p2o.pd_op.hardswish.0.0"
|
||||
float[batch,32,24,unk__0] "p2o.pd_op.hardswish.1.0"
|
||||
float[batch,128,12,unk__11] "p2o.pd_op.hardswish.10.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.11.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.12.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.13.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.14.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.15.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.16.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.17.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.18.0"
|
||||
float[batch,240,12,unk__11] "p2o.pd_op.hardswish.19.0"
|
||||
float[batch,32,24,unk__0] "p2o.pd_op.hardswish.2.0"
|
||||
float[batch,240,6,unk__11] "p2o.pd_op.hardswish.20.0"
|
||||
float[batch,480,6,unk__11] "p2o.pd_op.hardswish.21.0"
|
||||
float[batch,480,6,unk__11] "p2o.pd_op.hardswish.22.0"
|
||||
float[batch,480,6,unk__11] "p2o.pd_op.hardswish.23.0"
|
||||
float[batch,480,3,unk__11] "p2o.pd_op.hardswish.24.0"
|
||||
float[batch,480,3,unk__11] "p2o.pd_op.hardswish.25.0"
|
||||
float[batch,480,3,unk__11] "p2o.pd_op.hardswish.26.0"
|
||||
float[batch,480,3,unk__11] "p2o.pd_op.hardswish.27.0"
|
||||
float[batch,64,24,unk__0] "p2o.pd_op.hardswish.3.0"
|
||||
float[batch,64,24,unk__0] "p2o.pd_op.hardswish.4.0"
|
||||
float[batch,64,24,unk__0] "p2o.pd_op.hardswish.5.0"
|
||||
float[batch,64,12,unk__0] "p2o.pd_op.hardswish.6.0"
|
||||
float[batch,128,12,unk__0] "p2o.pd_op.hardswish.7.0"
|
||||
float[batch,128,12,unk__0] "p2o.pd_op.hardswish.8.0"
|
||||
float[batch,128,12,unk__0] "p2o.pd_op.hardswish.9.0"
|
||||
float[batch,seq,360] "p2o.pd_op.matmul.0.0"
|
||||
float[batch,8,seq,seq] "p2o.pd_op.matmul.1.0"
|
||||
float[batch,seq,240] "p2o.pd_op.matmul.10.0"
|
||||
float[batch,seq,120] "p2o.pd_op.matmul.11.0"
|
||||
float[batch,seq,438] "p2o.pd_op.matmul.12.0"
|
||||
float[batch,8,seq,15] "p2o.pd_op.matmul.2.0"
|
||||
float[batch,seq,120] "p2o.pd_op.matmul.3.0"
|
||||
float[batch,seq,240] "p2o.pd_op.matmul.4.0"
|
||||
float[batch,seq,120] "p2o.pd_op.matmul.5.0"
|
||||
float[batch,seq,360] "p2o.pd_op.matmul.6.0"
|
||||
float[batch,8,seq,seq] "p2o.pd_op.matmul.7.0"
|
||||
float[batch,8,seq,15] "p2o.pd_op.matmul.8.0"
|
||||
float[batch,seq,120] "p2o.pd_op.matmul.9.0"
|
||||
float[batch,240,1,1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,480,1,1] "p2o.pd_op.pool2d.1.0"
|
||||
float[batch,480,1,seq] "p2o.pd_op.pool2d.2.0"
|
||||
float[batch,60,1,1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,120,1,1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,seq,120] "p2o.pd_op.reshape.33.0"
|
||||
float[batch,seq,120] "p2o.pd_op.reshape.35.0"
|
||||
float[batch,1,seq,120] "p2o.pd_op.reshape.36.0"
|
||||
float[batch,8,seq,seq] "p2o.pd_op.softmax.0.0"
|
||||
float[batch,8,seq,seq] "p2o.pd_op.softmax.1.0"
|
||||
float[batch,120,seq] "p2o.pd_op.squeeze.0.0"
|
||||
float[batch,60,1,seq] "p2o.pd_op.swish.0.0"
|
||||
float[batch,120,1,seq] "p2o.pd_op.swish.1.0"
|
||||
float[batch,seq,240] "p2o.pd_op.swish.2.0"
|
||||
float[batch,seq,240] "p2o.pd_op.swish.3.0"
|
||||
float[batch,480,1,seq] "p2o.pd_op.swish.4.0"
|
||||
float[batch,60,1,seq] "p2o.pd_op.swish.5.0"
|
||||
float[batch,120,1,seq] "p2o.pd_op.swish.6.0"
|
||||
float[batch,seq,120] "p2o.pd_op.transpose.0.0"
|
||||
float[batch,8,15,seq] "p2o.pd_op.transpose.2.0"
|
||||
float[batch,seq,8,15] "p2o.pd_op.transpose.3.0"
|
||||
float[batch,8,15,seq] "p2o.pd_op.transpose.5.0"
|
||||
float[batch,seq,8,15] "p2o.pd_op.transpose.6.0"
|
||||
float[batch,120,1,seq] "p2o.pd_op.transpose.7.0"
|
||||
float[batch,seq,120] "p2o.pd_op.transpose.8.0"
|
||||
float[batch,seq,1] max_logits
|
||||
float[batch,48,width,3] tmp
|
||||
float[batch,3,48,width] tmp_0
|
||||
float[batch,seq,438] tmp_0_2
|
||||
float[batch,seq,438] tmp_1
|
||||
int64[batch,seq] tmp_2
|
||||
float[batch,seq] tmp_3
|
||||
float[batch,16,24,unk__0] val_0
|
||||
float[batch,32,24,unk__0] val_1
|
||||
float[batch,128,12,unk__0] val_10
|
||||
float[batch,128,12,unk__0] val_11
|
||||
float[batch,128,12,unk__0] val_12
|
||||
float[batch,128,12,unk__0] val_13
|
||||
float[batch,128,12,unk__0] val_14
|
||||
float[batch,128,12,unk__11] val_15
|
||||
float[batch,240,12,unk__11] val_16
|
||||
float[batch,240,12,unk__11] val_17
|
||||
float[batch,240,12,unk__11] val_18
|
||||
float[batch,240,12,unk__11] val_19
|
||||
float[batch,32,24,unk__0] val_2
|
||||
float[batch,240,12,unk__11] val_20
|
||||
float[batch,240,12,unk__11] val_21
|
||||
float[batch,240,12,unk__11] val_22
|
||||
float[batch,240,12,unk__11] val_23
|
||||
float[batch,240,12,unk__11] val_24
|
||||
float[batch,240,12,unk__11] val_25
|
||||
float[batch,240,12,unk__11] val_26
|
||||
float[batch,240,12,unk__11] val_27
|
||||
float[batch,240,12,unk__11] val_28
|
||||
float[batch,240,12,unk__11] val_29
|
||||
float[batch,32,24,unk__0] val_3
|
||||
float[batch,240,6,unk__11] val_30
|
||||
float[batch,480,6,unk__11] val_31
|
||||
float[batch,480,6,unk__11] val_32
|
||||
float[batch,480,6,unk__11] val_33
|
||||
float[batch,480,6,unk__11] val_34
|
||||
float[batch,480,6,unk__11] val_35
|
||||
float[batch,480,3,unk__11] val_36
|
||||
float[batch,480,3,unk__11] val_37
|
||||
float[batch,480,3,unk__11] val_38
|
||||
float[batch,480,3,unk__11] val_39
|
||||
float[batch,64,24,unk__0] val_4
|
||||
float[batch,480,3,unk__11] val_40
|
||||
float[batch,480,1,seq] val_41
|
||||
float[batch,480,1,seq] val_42
|
||||
float[batch,64,24,unk__0] val_5
|
||||
float[batch,64,24,unk__0] val_6
|
||||
float[batch,64,24,unk__0] val_7
|
||||
float[batch,64,24,unk__0] val_8
|
||||
float[batch,64,12,unk__0] val_9
|
||||
float[batch,3,48,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_0.w_0", "conv2d_0.w_0_bias")
|
||||
"Add.3" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 16, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.0.0", "conv2d_136.w_0_lab", "p2o.pd_op.depthwise_conv2d.0.0_bias_lab")
|
||||
val_0 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.3")
|
||||
"p2o.pd_op.hardswish.0.0" = Mul ("Add.3", val_0)
|
||||
"Add.9" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.0.0", "conv2d_137.w_0_lab_lab", "p2o.pd_op.conv2d.1.0_bias_lab_lab")
|
||||
val_1 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.9")
|
||||
"p2o.pd_op.hardswish.1.0" = Mul ("Add.9", val_1)
|
||||
val_2 = Add ("p2o.pd_op.hardswish.1.0", "conv2d_138.w_0_lab_laboffset")
|
||||
"Add.15" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_2, "conv2d_138.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.1.0_bias_lab")
|
||||
val_3 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.15")
|
||||
"p2o.pd_op.hardswish.2.0" = Mul ("Add.15", val_3)
|
||||
"Add.21" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.2.0", "conv2d_139.w_0_lab_lab", "p2o.pd_op.conv2d.2.0_bias_lab_lab")
|
||||
val_4 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.21")
|
||||
"p2o.pd_op.hardswish.3.0" = Mul ("Add.21", val_4)
|
||||
val_5 = Add ("p2o.pd_op.hardswish.3.0", "conv2d_140.w_0_lab_laboffset")
|
||||
"Add.27" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_5, "conv2d_140.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.2.0_bias_lab")
|
||||
val_6 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.27")
|
||||
"p2o.pd_op.hardswish.4.0" = Mul ("Add.27", val_6)
|
||||
"Add.33" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.4.0", "conv2d_141.w_0_lab_lab", "p2o.pd_op.conv2d.3.0_bias_lab_lab")
|
||||
val_7 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.33")
|
||||
"p2o.pd_op.hardswish.5.0" = Mul ("Add.33", val_7)
|
||||
val_8 = Add ("p2o.pd_op.hardswish.5.0", "conv2d_142.w_0_lab_laboffset")
|
||||
"Add.39" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 1]> (val_8, "conv2d_142.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.3.0_bias_lab")
|
||||
val_9 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.39")
|
||||
"p2o.pd_op.hardswish.6.0" = Mul ("Add.39", val_9)
|
||||
"Add.45" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.6.0", "conv2d_143.w_0_lab_lab", "p2o.pd_op.conv2d.4.0_bias_lab_lab")
|
||||
val_10 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.45")
|
||||
"p2o.pd_op.hardswish.7.0" = Mul ("Add.45", val_10)
|
||||
val_11 = Add ("p2o.pd_op.hardswish.7.0", "conv2d_144.w_0_lab_laboffset")
|
||||
"Add.51" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 128, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_11, "conv2d_144.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.4.0_bias_lab")
|
||||
val_12 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.51")
|
||||
"p2o.pd_op.hardswish.8.0" = Mul ("Add.51", val_12)
|
||||
"Add.57" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.8.0", "conv2d_145.w_0_lab_lab", "p2o.pd_op.conv2d.5.0_bias_lab_lab")
|
||||
val_13 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.57")
|
||||
"p2o.pd_op.hardswish.9.0" = Mul ("Add.57", val_13)
|
||||
val_14 = Add ("p2o.pd_op.hardswish.9.0", "conv2d_146.w_0_lab_laboffset")
|
||||
"Add.63" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 128, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 2]> (val_14, "conv2d_146.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.5.0_bias_lab")
|
||||
val_15 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.63")
|
||||
"p2o.pd_op.hardswish.10.0" = Mul ("Add.63", val_15)
|
||||
"Add.69" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.10.0", "conv2d_147.w_0_lab_lab", "p2o.pd_op.conv2d.6.0_bias_lab_lab")
|
||||
val_16 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.69")
|
||||
"p2o.pd_op.hardswish.11.0" = Mul ("Add.69", val_16)
|
||||
val_17 = Add ("p2o.pd_op.hardswish.11.0", "conv2d_148.w_0_lab_laboffset")
|
||||
"Add.75" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 240, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_17, "conv2d_148.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.6.0_bias_lab")
|
||||
val_18 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.75")
|
||||
"p2o.pd_op.hardswish.12.0" = Mul ("Add.75", val_18)
|
||||
"Add.81" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.12.0", "conv2d_149.w_0_lab_lab", "p2o.pd_op.conv2d.7.0_bias_lab_lab")
|
||||
val_19 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.81")
|
||||
"p2o.pd_op.hardswish.13.0" = Mul ("Add.81", val_19)
|
||||
val_20 = Add ("p2o.pd_op.hardswish.13.0", "conv2d_150.w_0_lab_laboffset")
|
||||
"Add.87" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 240, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_20, "conv2d_150.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.7.0_bias_lab")
|
||||
val_21 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.87")
|
||||
"p2o.pd_op.hardswish.14.0" = Mul ("Add.87", val_21)
|
||||
"Add.93" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.14.0", "conv2d_151.w_0_lab_lab", "p2o.pd_op.conv2d.8.0_bias_lab_lab")
|
||||
val_22 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.93")
|
||||
"p2o.pd_op.hardswish.15.0" = Mul ("Add.93", val_22)
|
||||
val_23 = Add ("p2o.pd_op.hardswish.15.0", "conv2d_152.w_0_lab_laboffset")
|
||||
"Add.99" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 240, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_23, "conv2d_152.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.8.0_bias_lab")
|
||||
val_24 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.99")
|
||||
"p2o.pd_op.hardswish.16.0" = Mul ("Add.99", val_24)
|
||||
"Add.105" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.16.0", "conv2d_153.w_0_lab_lab", "p2o.pd_op.conv2d.9.0_bias_lab_lab")
|
||||
val_25 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.105")
|
||||
"p2o.pd_op.hardswish.17.0" = Mul ("Add.105", val_25)
|
||||
val_26 = Add ("p2o.pd_op.hardswish.17.0", "conv2d_154.w_0_lab_laboffset")
|
||||
"Add.111" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 240, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_26, "conv2d_154.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.9.0_bias_lab")
|
||||
val_27 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.111")
|
||||
"p2o.pd_op.hardswish.18.0" = Mul ("Add.111", val_27)
|
||||
"Add.117" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.18.0", "conv2d_155.w_0_lab_lab", "p2o.pd_op.conv2d.10.0_bias_lab_lab")
|
||||
val_28 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.117")
|
||||
"p2o.pd_op.hardswish.19.0" = Mul ("Add.117", val_28)
|
||||
val_29 = Add ("p2o.pd_op.hardswish.19.0", "conv2d_156.w_0_lab_laboffset")
|
||||
"Add.123" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 240, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [2, 1]> (val_29, "conv2d_156.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.10.0_bias_lab")
|
||||
val_30 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.123")
|
||||
"p2o.pd_op.hardswish.20.0" = Mul ("Add.123", val_30)
|
||||
["Mul.82"] "Mul.83" = Mul ("learnable_affine_block_41.w_0", "p2o.pd_op.hardswish.20.0")
|
||||
["Add.124"] "Add.125" = Add ("Mul.83", "learnable_affine_block_41.w_1")
|
||||
["GlobalAveragePool.0"] "p2o.pd_op.pool2d.0.0" = GlobalAveragePool ("Add.125")
|
||||
"Add.127" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.0.0", "conv2d_96.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.127")
|
||||
"Add.129" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_97.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.129")
|
||||
["Mul.84"] "Mul.85" = Mul ("Add.125", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.133" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.85", "conv2d_157.w_0_lab", "p2o.pd_op.conv2d.13.0_bias_lab")
|
||||
val_31 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.133")
|
||||
"p2o.pd_op.hardswish.21.0" = Mul ("Add.133", val_31)
|
||||
val_32 = Add ("p2o.pd_op.hardswish.21.0", "conv2d_158.w_0_lab_laboffset")
|
||||
"Add.139" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 480, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_32, "conv2d_158.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.11.0_bias_lab")
|
||||
val_33 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.139")
|
||||
"p2o.pd_op.hardswish.22.0" = Mul ("Add.139", val_33)
|
||||
["Mul.92"] "Mul.93" = Mul ("learnable_affine_block_45.w_0", "p2o.pd_op.hardswish.22.0")
|
||||
["Add.140"] "Add.141" = Add ("Mul.93", "learnable_affine_block_45.w_1")
|
||||
["GlobalAveragePool.1"] "p2o.pd_op.pool2d.1.0" = GlobalAveragePool ("Add.141")
|
||||
"Add.143" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.1.0", "conv2d_107.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.143")
|
||||
"Add.145" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_108.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.145")
|
||||
["Mul.94"] "Mul.95" = Mul ("Add.141", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.149" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.95", "conv2d_159.w_0_lab", "p2o.pd_op.conv2d.16.0_bias_lab")
|
||||
val_34 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.149")
|
||||
"p2o.pd_op.hardswish.23.0" = Mul ("Add.149", val_34)
|
||||
val_35 = Add ("p2o.pd_op.hardswish.23.0", "conv2d_160.w_0_lab_laboffset")
|
||||
"Add.155" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 480, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [2, 1]> (val_35, "conv2d_160.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.12.0_bias_lab")
|
||||
val_36 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.155")
|
||||
"p2o.pd_op.hardswish.24.0" = Mul ("Add.155", val_36)
|
||||
"Add.161" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.24.0", "conv2d_161.w_0_lab_lab", "p2o.pd_op.conv2d.17.0_bias_lab_lab")
|
||||
val_37 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.161")
|
||||
"p2o.pd_op.hardswish.25.0" = Mul ("Add.161", val_37)
|
||||
val_38 = Add ("p2o.pd_op.hardswish.25.0", "conv2d_162.w_0_lab_laboffset")
|
||||
"Add.167" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 480, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_38, "conv2d_162.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.13.0_bias_lab")
|
||||
val_39 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.167")
|
||||
"p2o.pd_op.hardswish.26.0" = Mul ("Add.167", val_39)
|
||||
"Add.173" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.26.0", "conv2d_163.w_0_lab_lab", "p2o.pd_op.conv2d.18.0_bias_lab_lab")
|
||||
val_40 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.173")
|
||||
"p2o.pd_op.hardswish.27.0" = Mul ("Add.173", val_40)
|
||||
val_41 = AveragePool <auto_pad: string = "NOTSET", ceil_mode: int = 0, count_include_pad: int = 0, kernel_shape: ints = [3, 2], pads: ints = [0, 0, 0, 0], strides: ints = [3, 2]> ("p2o.pd_op.hardswish.27.0")
|
||||
val_42 = Mul (val_41, "learnable_affine_block_55.w_0")
|
||||
"p2o.pd_op.pool2d.2.0" = Add (val_42, "learnable_affine_block_55.w_1")
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 3], pads: ints = [0, 1, 0, 1], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.2.0", "conv2d_131.w_0", "conv2d_131.w_0_bias")
|
||||
["Sigmoid.0"] "Sigmoid.1" = Sigmoid ("p2o.pd_op.batch_norm_.1.0")
|
||||
["Mul.116"] "p2o.pd_op.swish.0.0" = Mul ("p2o.pd_op.batch_norm_.1.0", "Sigmoid.1")
|
||||
"p2o.pd_op.batch_norm_.2.0" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.swish.0.0", "conv2d_132.w_0", "conv2d_132.w_0_bias")
|
||||
["Sigmoid.2"] "Sigmoid.3" = Sigmoid ("p2o.pd_op.batch_norm_.2.0")
|
||||
["Mul.117"] "p2o.pd_op.swish.1.0" = Mul ("p2o.pd_op.batch_norm_.2.0", "Sigmoid.3")
|
||||
"p2o.pd_op.flatten.0.0" = Squeeze ("p2o.pd_op.swish.1.0", "helper.constant.9")
|
||||
["Transpose.0"] "p2o.pd_op.transpose.0.0" = Transpose <perm: ints = [0, 2, 1]> ("p2o.pd_op.flatten.0.0")
|
||||
"Add.181" = LayerNormalization <axis: int = -1, epsilon: float = 1e-05, stash_type: int = 1> ("p2o.pd_op.transpose.0.0", "helper.reshape.0", "helper.reshape.1")
|
||||
["MatMul.0"] "p2o.pd_op.matmul.0.0" = MatMul ("Add.181", "linear_0.w_0_qkv_scaled")
|
||||
["Add.182"] "Add.183" = Add ("p2o.pd_op.matmul.0.0", "linear_0.b_0_qkv_scaled")
|
||||
"Add.183_qkv" = Reshape <allowzero: int = 0> ("Add.183", "Add.183_qkv_shape")
|
||||
"Add.183_qkv_heads" = Transpose <perm: ints = [0, 2, 1, 3]> ("Add.183_qkv")
|
||||
"Add.183_q", "Add.183_k", "Add.183_v" = Split <axis: int = 1> ("Add.183_qkv_heads", "Add.183_qkv_sizes")
|
||||
["Transpose.2"] "p2o.pd_op.transpose.2.0" = Transpose <perm: ints = [0, 1, 3, 2]> ("Add.183_k")
|
||||
["MatMul.1"] "p2o.pd_op.matmul.1.0" = MatMul ("Add.183_q", "p2o.pd_op.transpose.2.0")
|
||||
["Softmax.0"] "p2o.pd_op.softmax.0.0" = Softmax <axis: int = -1> ("p2o.pd_op.matmul.1.0")
|
||||
["MatMul.2"] "p2o.pd_op.matmul.2.0" = MatMul ("p2o.pd_op.softmax.0.0", "Add.183_v")
|
||||
["Transpose.3"] "p2o.pd_op.transpose.3.0" = Transpose <perm: ints = [0, 2, 1, 3]> ("p2o.pd_op.matmul.2.0")
|
||||
["Reshape.38"] "p2o.pd_op.reshape.33.0" = Reshape <allowzero: int = 0> ("p2o.pd_op.transpose.3.0", "auto.cast.38")
|
||||
["MatMul.3"] "p2o.pd_op.matmul.3.0" = MatMul ("p2o.pd_op.reshape.33.0", "linear_1.w_0")
|
||||
["Add.184"] "Add.185" = Add ("p2o.pd_op.matmul.3.0", "linear_1.b_0")
|
||||
["Add.186"] "Add.187" = Add ("p2o.pd_op.transpose.0.0", "Add.185")
|
||||
"Add.191" = LayerNormalization <axis: int = -1, epsilon: float = 1e-05, stash_type: int = 1> ("Add.187", "helper.reshape.2", "helper.reshape.3")
|
||||
["MatMul.4"] "p2o.pd_op.matmul.4.0" = MatMul ("Add.191", "linear_2.w_0")
|
||||
["Add.192"] "Add.193" = Add ("p2o.pd_op.matmul.4.0", "linear_2.b_0")
|
||||
["Sigmoid.4"] "Sigmoid.5" = Sigmoid ("Add.193")
|
||||
["Mul.124"] "p2o.pd_op.swish.2.0" = Mul ("Add.193", "Sigmoid.5")
|
||||
["MatMul.5"] "p2o.pd_op.matmul.5.0" = MatMul ("p2o.pd_op.swish.2.0", "linear_3.w_0")
|
||||
["Add.194"] "Add.195" = Add ("p2o.pd_op.matmul.5.0", "linear_3.b_0")
|
||||
["Add.196"] "Add.197" = Add ("Add.187", "Add.195")
|
||||
"Add.201" = LayerNormalization <axis: int = -1, epsilon: float = 1e-05, stash_type: int = 1> ("Add.197", "helper.reshape.4", "helper.reshape.5")
|
||||
["MatMul.6"] "p2o.pd_op.matmul.6.0" = MatMul ("Add.201", "linear_4.w_0_qkv_scaled")
|
||||
["Add.202"] "Add.203" = Add ("p2o.pd_op.matmul.6.0", "linear_4.b_0_qkv_scaled")
|
||||
"Add.203_qkv" = Reshape <allowzero: int = 0> ("Add.203", "Add.183_qkv_shape")
|
||||
"Add.203_qkv_heads" = Transpose <perm: ints = [0, 2, 1, 3]> ("Add.203_qkv")
|
||||
"Add.203_q", "Add.203_k", "Add.203_v" = Split <axis: int = 1> ("Add.203_qkv_heads", "Add.183_qkv_sizes")
|
||||
["Transpose.5"] "p2o.pd_op.transpose.5.0" = Transpose <perm: ints = [0, 1, 3, 2]> ("Add.203_k")
|
||||
["MatMul.7"] "p2o.pd_op.matmul.7.0" = MatMul ("Add.203_q", "p2o.pd_op.transpose.5.0")
|
||||
["Softmax.1"] "p2o.pd_op.softmax.1.0" = Softmax <axis: int = -1> ("p2o.pd_op.matmul.7.0")
|
||||
["MatMul.8"] "p2o.pd_op.matmul.8.0" = MatMul ("p2o.pd_op.softmax.1.0", "Add.203_v")
|
||||
["Transpose.6"] "p2o.pd_op.transpose.6.0" = Transpose <perm: ints = [0, 2, 1, 3]> ("p2o.pd_op.matmul.8.0")
|
||||
["Reshape.46"] "p2o.pd_op.reshape.35.0" = Reshape <allowzero: int = 0> ("p2o.pd_op.transpose.6.0", "auto.cast.38")
|
||||
["MatMul.9"] "p2o.pd_op.matmul.9.0" = MatMul ("p2o.pd_op.reshape.35.0", "linear_5.w_0")
|
||||
["Add.204"] "Add.205" = Add ("p2o.pd_op.matmul.9.0", "linear_5.b_0")
|
||||
["Add.206"] "Add.207" = Add ("Add.197", "Add.205")
|
||||
"Add.211" = LayerNormalization <axis: int = -1, epsilon: float = 1e-05, stash_type: int = 1> ("Add.207", "helper.reshape.6", "helper.reshape.7")
|
||||
["MatMul.10"] "p2o.pd_op.matmul.10.0" = MatMul ("Add.211", "linear_6.w_0")
|
||||
["Add.212"] "Add.213" = Add ("p2o.pd_op.matmul.10.0", "linear_6.b_0")
|
||||
["Sigmoid.6"] "Sigmoid.7" = Sigmoid ("Add.213")
|
||||
["Mul.131"] "p2o.pd_op.swish.3.0" = Mul ("Add.213", "Sigmoid.7")
|
||||
["MatMul.11"] "p2o.pd_op.matmul.11.0" = MatMul ("p2o.pd_op.swish.3.0", "linear_7.w_0")
|
||||
["Add.214"] "Add.215" = Add ("p2o.pd_op.matmul.11.0", "linear_7.b_0")
|
||||
["Add.216"] "Add.217" = Add ("Add.207", "Add.215")
|
||||
"Add.221" = LayerNormalization <axis: int = -1, epsilon: float = 1e-06, stash_type: int = 1> ("Add.217", "helper.reshape.8", "helper.reshape.9")
|
||||
"p2o.pd_op.reshape.36.0" = Unsqueeze ("Add.221", rec_unsqueeze_axis)
|
||||
["Transpose.7"] "p2o.pd_op.transpose.7.0" = Transpose <perm: ints = [0, 3, 1, 2]> ("p2o.pd_op.reshape.36.0")
|
||||
"p2o.pd_op.batch_norm_.3.0" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.transpose.7.0", "conv2d_133.w_0", "conv2d_133.w_0_bias")
|
||||
["Sigmoid.8"] "Sigmoid.9" = Sigmoid ("p2o.pd_op.batch_norm_.3.0")
|
||||
["Mul.134"] "p2o.pd_op.swish.4.0" = Mul ("p2o.pd_op.batch_norm_.3.0", "Sigmoid.9")
|
||||
["Concat.3"] "Concat.4" = Concat <axis: int = 1> ("p2o.pd_op.pool2d.2.0", "p2o.pd_op.swish.4.0")
|
||||
"p2o.pd_op.batch_norm_.4.0" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 3], pads: ints = [0, 1, 0, 1], strides: ints = [1, 1]> ("Concat.4", "conv2d_134.w_0", "conv2d_134.w_0_bias")
|
||||
["Sigmoid.10"] "Sigmoid.11" = Sigmoid ("p2o.pd_op.batch_norm_.4.0")
|
||||
["Mul.135"] "p2o.pd_op.swish.5.0" = Mul ("p2o.pd_op.batch_norm_.4.0", "Sigmoid.11")
|
||||
"p2o.pd_op.batch_norm_.5.0" = Conv <auto_pad: string = "NOTSET", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.swish.5.0", "conv2d_135.w_0", "conv2d_135.w_0_bias")
|
||||
["Sigmoid.12"] "Sigmoid.13" = Sigmoid ("p2o.pd_op.batch_norm_.5.0")
|
||||
["Mul.136"] "p2o.pd_op.swish.6.0" = Mul ("p2o.pd_op.batch_norm_.5.0", "Sigmoid.13")
|
||||
["Squeeze.8"] "p2o.pd_op.squeeze.0.0" = Squeeze ("p2o.pd_op.swish.6.0", "helper.constant.9")
|
||||
["Transpose.8"] "p2o.pd_op.transpose.8.0" = Transpose <perm: ints = [0, 2, 1]> ("p2o.pd_op.squeeze.0.0")
|
||||
["MatMul.12"] "p2o.pd_op.matmul.12.0" = MatMul ("p2o.pd_op.transpose.8.0", "linear_8.w_0")
|
||||
["Add.222"] "Add.223" = Add ("p2o.pd_op.matmul.12.0", "linear_8.b_0")
|
||||
[n0_2] tmp_2 = ArgMax <axis: int = 2, keepdims: int = 0> ("Add.223")
|
||||
[n1_2] ctc_indices = Cast <to: int = 6> (tmp_2)
|
||||
[n3_2] max_logits = ReduceMax <keepdims: int = 1> ("Add.223", "helper.constant.9")
|
||||
[n4_2] tmp_0_2 = Sub ("Add.223", max_logits)
|
||||
[n5] tmp_1 = Exp (tmp_0_2)
|
||||
[n7] tmp_3 = ReduceSum <keepdims: int = 0> (tmp_1, "helper.constant.9")
|
||||
[n8] ctc_confidence = Reciprocal (tmp_3)
|
||||
}
|
||||
|
||||
weights:
|
||||
Add.183_qkv_shape INT64[4] 003762987fc4
|
||||
Add.183_qkv_sizes INT64[3] 49f92c4a88e0
|
||||
auto.cast.38 INT64[3] b190f2a09873
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_0.w_0 FLOAT[16,3,3,3] 34df4281f729
|
||||
conv2d_0.w_0_bias FLOAT[16] 105e1f48c3a4
|
||||
conv2d_107.w_0 FLOAT[120,480,1,1] d2d0e602dcd4
|
||||
conv2d_108.w_0 FLOAT[480,120,1,1] 54272c2fc604
|
||||
conv2d_131.w_0 FLOAT[60,480,1,3] 9cc62aeb7e32
|
||||
conv2d_131.w_0_bias FLOAT[60] 463c0e2a9bdc
|
||||
conv2d_132.w_0 FLOAT[120,60,1,1] 6273465d3fca
|
||||
conv2d_132.w_0_bias FLOAT[120] 80df00d04058
|
||||
conv2d_133.w_0 FLOAT[480,120,1,1] 387d4d6defab
|
||||
conv2d_133.w_0_bias FLOAT[480] 8dec489e72b9
|
||||
conv2d_134.w_0 FLOAT[60,960,1,3] 3a6a1b6b26d2
|
||||
conv2d_134.w_0_bias FLOAT[60] 241ae9d4fba9
|
||||
conv2d_135.w_0 FLOAT[120,60,1,1] 9247d4a073a4
|
||||
conv2d_135.w_0_bias FLOAT[120] 9e33a4861e05
|
||||
conv2d_136.w_0_lab FLOAT[16,1,3,3] 882eed7d616a
|
||||
conv2d_137.w_0_lab_lab FLOAT[32,16,1,1] 91240265a23a
|
||||
conv2d_138.w_0_lab_laboffset FLOAT[] 3af84f5cb37c
|
||||
conv2d_138.w_0_lab_labscale FLOAT[32,1,3,3] 6f3f14baf376
|
||||
conv2d_139.w_0_lab_lab FLOAT[64,32,1,1] 360bc077c422
|
||||
conv2d_140.w_0_lab_laboffset FLOAT[] ba3f0a44cb9d
|
||||
conv2d_140.w_0_lab_labscale FLOAT[64,1,3,3] d98969f8dc48
|
||||
conv2d_141.w_0_lab_lab FLOAT[64,64,1,1] 22d3912e3b2c
|
||||
conv2d_142.w_0_lab_laboffset FLOAT[] 34eb1d1cb273
|
||||
conv2d_142.w_0_lab_labscale FLOAT[64,1,3,3] de45e41b33ac
|
||||
conv2d_143.w_0_lab_lab FLOAT[128,64,1,1] 97476cba5139
|
||||
conv2d_144.w_0_lab_laboffset FLOAT[] 5b7017a87ec6
|
||||
conv2d_144.w_0_lab_labscale FLOAT[128,1,3,3] 571e48d95cbe
|
||||
conv2d_145.w_0_lab_lab FLOAT[128,128,1,1] 23aa9c5596ae
|
||||
conv2d_146.w_0_lab_laboffset FLOAT[] 52b7962899a9
|
||||
conv2d_146.w_0_lab_labscale FLOAT[128,1,3,3] e4ca13a8ddd5
|
||||
conv2d_147.w_0_lab_lab FLOAT[240,128,1,1] 3585c9631761
|
||||
conv2d_148.w_0_lab_laboffset FLOAT[] 3ac71f1a131b
|
||||
conv2d_148.w_0_lab_labscale FLOAT[240,1,5,5] 59f3c8906d08
|
||||
conv2d_149.w_0_lab_lab FLOAT[240,240,1,1] 70deb1cafa9b
|
||||
conv2d_150.w_0_lab_laboffset FLOAT[] d1690af3307f
|
||||
conv2d_150.w_0_lab_labscale FLOAT[240,1,5,5] 0a0faefb0475
|
||||
conv2d_151.w_0_lab_lab FLOAT[240,240,1,1] 754032ccee3b
|
||||
conv2d_152.w_0_lab_laboffset FLOAT[] 2209f068c6fe
|
||||
conv2d_152.w_0_lab_labscale FLOAT[240,1,5,5] 254c5dbcf414
|
||||
conv2d_153.w_0_lab_lab FLOAT[240,240,1,1] 1d33db0c2dd4
|
||||
conv2d_154.w_0_lab_laboffset FLOAT[] c2b6b5366d2f
|
||||
conv2d_154.w_0_lab_labscale FLOAT[240,1,5,5] 43d670509d34
|
||||
conv2d_155.w_0_lab_lab FLOAT[240,240,1,1] 5d893afc4586
|
||||
conv2d_156.w_0_lab_laboffset FLOAT[] 3f5ff85e6d1b
|
||||
conv2d_156.w_0_lab_labscale FLOAT[240,1,5,5] a73bca002144
|
||||
conv2d_157.w_0_lab FLOAT[480,240,1,1] 65f2f72963a0
|
||||
conv2d_158.w_0_lab_laboffset FLOAT[] c01ea59574f3
|
||||
conv2d_158.w_0_lab_labscale FLOAT[480,1,5,5] 57abbc03e61a
|
||||
conv2d_159.w_0_lab FLOAT[480,480,1,1] c995d038d333
|
||||
conv2d_160.w_0_lab_laboffset FLOAT[] 05a6b61cdacd
|
||||
conv2d_160.w_0_lab_labscale FLOAT[480,1,5,5] 843f31741161
|
||||
conv2d_161.w_0_lab_lab FLOAT[480,480,1,1] 30258baac013
|
||||
conv2d_162.w_0_lab_laboffset FLOAT[] c75eaa0e917f
|
||||
conv2d_162.w_0_lab_labscale FLOAT[480,1,5,5] 558cd9018869
|
||||
conv2d_163.w_0_lab_lab FLOAT[480,480,1,1] f87831201cc0
|
||||
conv2d_96.w_0 FLOAT[60,240,1,1] ab552f547bfd
|
||||
conv2d_97.w_0 FLOAT[240,60,1,1] 219d3804e0f9
|
||||
helper.constant.9 INT64[1] d86e8112f3c4
|
||||
helper.reshape.0 FLOAT[120] a95eba1df2c1
|
||||
helper.reshape.1 FLOAT[120] dd4096eae7bb
|
||||
helper.reshape.2 FLOAT[120] 02a8a48a3ad9
|
||||
helper.reshape.3 FLOAT[120] 0567c9663a13
|
||||
helper.reshape.4 FLOAT[120] 88b348a46bae
|
||||
helper.reshape.5 FLOAT[120] ba47abcac5c2
|
||||
helper.reshape.6 FLOAT[120] aed9ffb9191d
|
||||
helper.reshape.7 FLOAT[120] 4a9fbf95eb59
|
||||
helper.reshape.8 FLOAT[120] 49d0bb05fe10
|
||||
helper.reshape.9 FLOAT[120] e8034e7a2162
|
||||
learnable_affine_block_41.w_0 FLOAT[1] a76ac811e4e2
|
||||
learnable_affine_block_41.w_1 FLOAT[1] f4475e39b3a2
|
||||
learnable_affine_block_45.w_0 FLOAT[1] 1d81fef0f259
|
||||
learnable_affine_block_45.w_1 FLOAT[1] da21e4ca8ce4
|
||||
learnable_affine_block_55.w_0 FLOAT[1] 0df6ea541c62
|
||||
learnable_affine_block_55.w_1 FLOAT[1] 5473b1fddf91
|
||||
linear_0.b_0_qkv_scaled FLOAT[360] 7ceb4d414364
|
||||
linear_0.w_0_qkv_scaled FLOAT[120,360] 4aa391da940d
|
||||
linear_1.b_0 FLOAT[120] 3720201dc965
|
||||
linear_1.w_0 FLOAT[120,120] 3c4d20984273
|
||||
linear_2.b_0 FLOAT[240] bbc55bb7b4ea
|
||||
linear_2.w_0 FLOAT[120,240] 25faa7183517
|
||||
linear_3.b_0 FLOAT[120] dc336862d5ae
|
||||
linear_3.w_0 FLOAT[240,120] ed26f23747f2
|
||||
linear_4.b_0_qkv_scaled FLOAT[360] ba4b2a7fedf3
|
||||
linear_4.w_0_qkv_scaled FLOAT[120,360] 4f9667f45038
|
||||
linear_5.b_0 FLOAT[120] 8e1c4ab966c8
|
||||
linear_5.w_0 FLOAT[120,120] 9eff89d7ce09
|
||||
linear_6.b_0 FLOAT[240] 0d6a49832bc1
|
||||
linear_6.w_0 FLOAT[120,240] e7fd1cdcbf33
|
||||
linear_7.b_0 FLOAT[120] f9b16daaa082
|
||||
linear_7.w_0 FLOAT[240,120] 4ae86a74e1c6
|
||||
linear_8.b_0 FLOAT[438] c6737f64d40d
|
||||
linear_8.w_0 FLOAT[120,438] 03285bb134ec
|
||||
p2o.pd_op.conv2d.1.0_bias_lab_lab FLOAT[32] 7aa5d9fee267
|
||||
p2o.pd_op.conv2d.10.0_bias_lab_lab FLOAT[240] 3502847e7fb1
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[60] d99fd1b549fb
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[240] b221bbc745aa
|
||||
p2o.pd_op.conv2d.13.0_bias_lab FLOAT[480] db53118362d3
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[120] d24bad2a28a0
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[480] 67ea0d2e8d77
|
||||
p2o.pd_op.conv2d.16.0_bias_lab FLOAT[480] 2b5ef9f63456
|
||||
p2o.pd_op.conv2d.17.0_bias_lab_lab FLOAT[480] c584b9daef76
|
||||
p2o.pd_op.conv2d.18.0_bias_lab_lab FLOAT[480] 12c64e71133e
|
||||
p2o.pd_op.conv2d.2.0_bias_lab_lab FLOAT[64] 091974adb85f
|
||||
p2o.pd_op.conv2d.3.0_bias_lab_lab FLOAT[64] 408e43f10893
|
||||
p2o.pd_op.conv2d.4.0_bias_lab_lab FLOAT[128] f3f71737ace8
|
||||
p2o.pd_op.conv2d.5.0_bias_lab_lab FLOAT[128] d3f630e2cc43
|
||||
p2o.pd_op.conv2d.6.0_bias_lab_lab FLOAT[240] 6cc72581a18e
|
||||
p2o.pd_op.conv2d.7.0_bias_lab_lab FLOAT[240] 7f76813a0764
|
||||
p2o.pd_op.conv2d.8.0_bias_lab_lab FLOAT[240] 6b037b067778
|
||||
p2o.pd_op.conv2d.9.0_bias_lab_lab FLOAT[240] 733286ec6907
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias_lab FLOAT[16] d2d86949eede
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias_lab FLOAT[32] cb5966d61b11
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias_lab FLOAT[240] f4dfbd05f740
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias_lab FLOAT[480] 0c9931a92f7a
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias_lab FLOAT[480] 3c17c69734b2
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias_lab FLOAT[480] 6e0ade206f4d
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias_lab FLOAT[64] 1e031ef81848
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias_lab FLOAT[64] b379432f1ab6
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias_lab FLOAT[128] b7527030fb10
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias_lab FLOAT[128] 0b74e3d7dea7
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias_lab FLOAT[240] 4f3a618f3948
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias_lab FLOAT[240] c2203c76fb14
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias_lab FLOAT[240] e87a59914a91
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias_lab FLOAT[240] f9bc97532929
|
||||
rec_unsqueeze_axis INT64[1] 7c9fa136d441
|
||||
@@ -0,0 +1,468 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,192,unk__22,unk__23] "Add.105"
|
||||
float[batch,192,unk__22,unk__23] "Add.111"
|
||||
float[batch,192,unk__42,unk__43] "Add.117"
|
||||
float[batch,48,1,1] "Add.119"
|
||||
float[batch,192,1,1] "Add.121"
|
||||
float[batch,384,unk__42,unk__43] "Add.125"
|
||||
float[batch,384,unk__42,unk__43] "Add.131"
|
||||
float[batch,384,unk__42,unk__43] "Add.133"
|
||||
float[batch,96,1,1] "Add.135"
|
||||
float[batch,384,1,1] "Add.137"
|
||||
float[batch,384,unk__42,unk__43] "Add.141"
|
||||
float[batch,384,unk__42,unk__43] "Add.147"
|
||||
float[batch,32,unk__6,unk__7] "Add.15"
|
||||
float[batch,384,unk__42,unk__43] "Add.153"
|
||||
float[batch,384,unk__42,unk__43] "Add.159"
|
||||
float[batch,384,unk__42,unk__43] "Add.165"
|
||||
float[batch,96,unk__42,unk__43] "Add.181"
|
||||
float[batch,96,unk__22,unk__23] "Add.187"
|
||||
float[batch,48,unk__6,unk__7] "Add.19"
|
||||
float[batch,96,unk__14,unk__15] "Add.193"
|
||||
float[batch,96,unk__6,unk__7] "Add.199"
|
||||
float[batch,96,unk__22,unk__23] "Add.201"
|
||||
float[batch,96,unk__14,unk__15] "Add.203"
|
||||
float[batch,96,unk__6,unk__7] "Add.205"
|
||||
float[batch,24,unk__42,unk__43] "Add.211"
|
||||
float[batch,24,unk__22,unk__23] "Add.217"
|
||||
float[batch,24,unk__14,unk__15] "Add.223"
|
||||
float[batch,24,unk__6,unk__7] "Add.229"
|
||||
float[batch,1,height,width] "Add.233"
|
||||
float[batch,48,unk__6,unk__7] "Add.25"
|
||||
float[batch,16,unk__0,unk__1] "Add.3"
|
||||
float[batch,48,unk__6,unk__7] "Add.31"
|
||||
float[batch,48,unk__14,unk__15] "Add.37"
|
||||
float[batch,96,unk__14,unk__15] "Add.41"
|
||||
float[batch,96,unk__14,unk__15] "Add.47"
|
||||
float[batch,96,unk__14,unk__15] "Add.53"
|
||||
float[batch,96,unk__22,unk__23] "Add.59"
|
||||
float[batch,192,unk__22,unk__23] "Add.63"
|
||||
float[batch,192,unk__22,unk__23] "Add.69"
|
||||
float[batch,192,unk__22,unk__23] "Add.75"
|
||||
float[batch,192,unk__22,unk__23] "Add.81"
|
||||
float[batch,192,unk__22,unk__23] "Add.87"
|
||||
float[batch,32,unk__0,unk__1] "Add.9"
|
||||
float[batch,192,unk__22,unk__23] "Add.93"
|
||||
float[batch,192,unk__22,unk__23] "Add.99"
|
||||
float[batch,96,unk__6,unk__7] "Concat.1"
|
||||
float[batch,192,unk__42,unk__43] "Mul.77"
|
||||
float[batch,384,unk__42,unk__43] "Mul.85"
|
||||
float[batch,384,unk__42,unk__43] "Mul.87"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,96,unk__42,unk__43] "p2o.pd_op.conv2d.23.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.conv2d.26.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.conv2d.29.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.conv2d.32.0"
|
||||
float[batch,24,unk__42,unk__43] "p2o.pd_op.conv2d.35.0"
|
||||
float[batch,24,unk__22,unk__23] "p2o.pd_op.conv2d.38.0"
|
||||
float[batch,24,unk__14,unk__15] "p2o.pd_op.conv2d.41.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.conv2d.44.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.hardswish.0.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.hardswish.1.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.10.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.11.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.12.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.13.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.14.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.15.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.16.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.17.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.18.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.19.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.2.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.20.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.21.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.22.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.23.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.3.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.4.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.5.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.6.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.7.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.8.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.9.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.pool2d.1.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.2.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.3.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.4.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.5.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.6.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.7.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.8.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.9.0"
|
||||
float[batch,48,1,1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.relu.10.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.relu.11.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.2.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.3.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.4.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.5.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.6.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.7.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.8.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.9.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,96,1,1] se_group0_down
|
||||
float[batch,384,1,1] se_group0_gates
|
||||
float[batch,384,1,1] se_group0_pooled
|
||||
float[batch,96,1,1] se_group0_relu
|
||||
float[batch,384,1,1] se_group0_up
|
||||
float[batch,24,1,1] se_group1_down
|
||||
float[batch,96,1,1] se_group1_gates
|
||||
float[batch,96,1,1] se_group1_pooled
|
||||
float[batch,24,1,1] se_group1_relu
|
||||
float[batch,96,1,1] se_group1_up
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,16,unk__0,unk__1] val_0
|
||||
float[batch,32,unk__0,unk__1] val_1
|
||||
float[batch,96,unk__14,unk__15] val_10
|
||||
float[batch,96,unk__14,unk__15] val_11
|
||||
float[batch,96,unk__14,unk__15] val_12
|
||||
float[batch,192,unk__22,unk__23] val_13
|
||||
float[batch,192,unk__22,unk__23] val_14
|
||||
float[batch,192,unk__22,unk__23] val_15
|
||||
float[batch,192,unk__22,unk__23] val_16
|
||||
float[batch,192,unk__22,unk__23] val_17
|
||||
float[batch,192,unk__22,unk__23] val_18
|
||||
float[batch,192,unk__22,unk__23] val_19
|
||||
float[batch,32,unk__0,unk__1] val_2
|
||||
float[batch,192,unk__22,unk__23] val_20
|
||||
float[batch,192,unk__22,unk__23] val_21
|
||||
float[batch,192,unk__22,unk__23] val_22
|
||||
float[batch,192,unk__22,unk__23] val_23
|
||||
float[batch,192,unk__22,unk__23] val_24
|
||||
float[batch,192,unk__22,unk__23] val_25
|
||||
float[batch,192,unk__22,unk__23] val_26
|
||||
float[batch,384,unk__42,unk__43] val_27
|
||||
float[batch,384,unk__42,unk__43] val_28
|
||||
float[batch,384,unk__42,unk__43] val_29
|
||||
float[batch,48,unk__6,unk__7] val_3
|
||||
float[batch,384,unk__42,unk__43] val_30
|
||||
float[batch,384,unk__42,unk__43] val_31
|
||||
float[batch,384,unk__42,unk__43] val_32
|
||||
float[batch,384,unk__42,unk__43] val_33
|
||||
float[batch,384,unk__42,unk__43] val_34
|
||||
float[batch,384,unk__42,unk__43] val_35
|
||||
float[batch,384,unk__42,unk__43] val_36
|
||||
float[batch,96,1,1] val_37
|
||||
float[batch,96,1,1] val_38
|
||||
float[batch,96,1,1] val_39
|
||||
float[batch,48,unk__6,unk__7] val_4
|
||||
float[batch,96,1,1] val_40
|
||||
float[batch,24,1,1] val_41
|
||||
float[batch,24,1,1] val_42
|
||||
float[batch,24,1,1] val_43
|
||||
float[batch,24,1,1] val_44
|
||||
float[batch,48,unk__6,unk__7] val_5
|
||||
float[batch,48,unk__6,unk__7] val_6
|
||||
float[batch,48,unk__6,unk__7] val_7
|
||||
float[batch,96,unk__14,unk__15] val_8
|
||||
float[batch,96,unk__14,unk__15] val_9
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_0.w_0", "conv2d_0.w_0_bias")
|
||||
"Add.3" = Conv <dilations: ints = [1, 1], group: int = 16, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.0.0", "conv2d_161.w_0_lab", "p2o.pd_op.depthwise_conv2d.0.0_bias_lab")
|
||||
val_0 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.3")
|
||||
"p2o.pd_op.hardswish.0.0" = Mul ("Add.3", val_0)
|
||||
"Add.9" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.0.0", "conv2d_162.w_0_lab_lab", "p2o.pd_op.conv2d.1.0_bias_lab_lab")
|
||||
val_1 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.9")
|
||||
"p2o.pd_op.hardswish.1.0" = Mul ("Add.9", val_1)
|
||||
val_2 = Add ("p2o.pd_op.hardswish.1.0", "conv2d_163.w_0_lab_laboffset")
|
||||
"Add.15" = Conv <dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_2, "conv2d_163.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.1.0_bias_lab")
|
||||
"Add.19" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.15", "conv2d_164.w_0_lab", "p2o.pd_op.conv2d.2.0_bias_lab")
|
||||
val_3 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.19")
|
||||
"p2o.pd_op.hardswish.2.0" = Mul ("Add.19", val_3)
|
||||
val_4 = Add ("p2o.pd_op.hardswish.2.0", "conv2d_165.w_0_lab_laboffset")
|
||||
"Add.25" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_4, "conv2d_165.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.2.0_bias_lab")
|
||||
val_5 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.25")
|
||||
"p2o.pd_op.hardswish.3.0" = Mul ("Add.25", val_5)
|
||||
"Add.31" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.3.0", "conv2d_166.w_0_lab_lab", "p2o.pd_op.conv2d.3.0_bias_lab_lab")
|
||||
val_6 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.31")
|
||||
"p2o.pd_op.hardswish.4.0" = Mul ("Add.31", val_6)
|
||||
val_7 = Add ("p2o.pd_op.hardswish.4.0", "conv2d_167.w_0_lab_laboffset")
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_7, "conv2d_167.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.3.0_bias_lab")
|
||||
"Add.41" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.37", "conv2d_168.w_0_lab", "p2o.pd_op.conv2d.4.0_bias_lab")
|
||||
val_8 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.41")
|
||||
"p2o.pd_op.hardswish.5.0" = Mul ("Add.41", val_8)
|
||||
val_9 = Add ("p2o.pd_op.hardswish.5.0", "conv2d_169.w_0_lab_laboffset")
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_9, "conv2d_169.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.4.0_bias_lab")
|
||||
val_10 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.47")
|
||||
"p2o.pd_op.hardswish.6.0" = Mul ("Add.47", val_10)
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.6.0", "conv2d_170.w_0_lab_lab", "p2o.pd_op.conv2d.5.0_bias_lab_lab")
|
||||
val_11 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.53")
|
||||
"p2o.pd_op.hardswish.7.0" = Mul ("Add.53", val_11)
|
||||
val_12 = Add ("p2o.pd_op.hardswish.7.0", "conv2d_171.w_0_lab_laboffset")
|
||||
"Add.59" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_12, "conv2d_171.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.5.0_bias_lab")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.59", "conv2d_172.w_0_lab", "p2o.pd_op.conv2d.6.0_bias_lab")
|
||||
val_13 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.63")
|
||||
"p2o.pd_op.hardswish.8.0" = Mul ("Add.63", val_13)
|
||||
val_14 = Add ("p2o.pd_op.hardswish.8.0", "conv2d_173.w_0_lab_laboffset")
|
||||
"Add.69" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_14, "conv2d_173.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.6.0_bias_lab")
|
||||
val_15 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.69")
|
||||
"p2o.pd_op.hardswish.9.0" = Mul ("Add.69", val_15)
|
||||
"Add.75" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.9.0", "conv2d_174.w_0_lab_lab", "p2o.pd_op.conv2d.7.0_bias_lab_lab")
|
||||
val_16 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.75")
|
||||
"p2o.pd_op.hardswish.10.0" = Mul ("Add.75", val_16)
|
||||
val_17 = Add ("p2o.pd_op.hardswish.10.0", "conv2d_175.w_0_lab_laboffset")
|
||||
"Add.81" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_17, "conv2d_175.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.7.0_bias_lab")
|
||||
val_18 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.81")
|
||||
"p2o.pd_op.hardswish.11.0" = Mul ("Add.81", val_18)
|
||||
"Add.87" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.11.0", "conv2d_176.w_0_lab_lab", "p2o.pd_op.conv2d.8.0_bias_lab_lab")
|
||||
val_19 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.87")
|
||||
"p2o.pd_op.hardswish.12.0" = Mul ("Add.87", val_19)
|
||||
val_20 = Add ("p2o.pd_op.hardswish.12.0", "conv2d_177.w_0_lab_laboffset")
|
||||
"Add.93" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_20, "conv2d_177.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.8.0_bias_lab")
|
||||
val_21 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.93")
|
||||
"p2o.pd_op.hardswish.13.0" = Mul ("Add.93", val_21)
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.13.0", "conv2d_178.w_0_lab_lab", "p2o.pd_op.conv2d.9.0_bias_lab_lab")
|
||||
val_22 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.99")
|
||||
"p2o.pd_op.hardswish.14.0" = Mul ("Add.99", val_22)
|
||||
val_23 = Add ("p2o.pd_op.hardswish.14.0", "conv2d_179.w_0_lab_laboffset")
|
||||
"Add.105" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_23, "conv2d_179.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.9.0_bias_lab")
|
||||
val_24 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.105")
|
||||
"p2o.pd_op.hardswish.15.0" = Mul ("Add.105", val_24)
|
||||
"Add.111" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.15.0", "conv2d_180.w_0_lab_lab", "p2o.pd_op.conv2d.10.0_bias_lab_lab")
|
||||
val_25 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.111")
|
||||
"p2o.pd_op.hardswish.16.0" = Mul ("Add.111", val_25)
|
||||
val_26 = Add ("p2o.pd_op.hardswish.16.0", "conv2d_181.w_0_lab_laboffset")
|
||||
"Add.117" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [2, 2]> (val_26, "conv2d_181.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.10.0_bias_lab")
|
||||
["GlobalAveragePool.0"] "p2o.pd_op.pool2d.0.0" = GlobalAveragePool ("Add.117")
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.0.0", "conv2d_96.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.119")
|
||||
"Add.121" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_97.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.121")
|
||||
["Mul.76"] "Mul.77" = Mul ("Add.117", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.77", "conv2d_182.w_0_lab", "p2o.pd_op.conv2d.13.0_bias_lab")
|
||||
val_27 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.125")
|
||||
"p2o.pd_op.hardswish.17.0" = Mul ("Add.125", val_27)
|
||||
val_28 = Add ("p2o.pd_op.hardswish.17.0", "conv2d_183.w_0_lab_laboffset")
|
||||
"Add.131" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_28, "conv2d_183.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.11.0_bias_lab")
|
||||
val_29 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.131")
|
||||
"p2o.pd_op.hardswish.18.0" = Mul ("Add.131", val_29)
|
||||
["Mul.84"] "Mul.85" = Mul ("learnable_affine_block_45.w_0", "p2o.pd_op.hardswish.18.0")
|
||||
["Add.132"] "Add.133" = Add ("Mul.85", "learnable_affine_block_45.w_1")
|
||||
["GlobalAveragePool.1"] "p2o.pd_op.pool2d.1.0" = GlobalAveragePool ("Add.133")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.1.0", "conv2d_107.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.135")
|
||||
"Add.137" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_108.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.137")
|
||||
["Mul.86"] "Mul.87" = Mul ("Add.133", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.141" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.87", "conv2d_184.w_0_lab", "p2o.pd_op.conv2d.16.0_bias_lab")
|
||||
val_30 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.141")
|
||||
"p2o.pd_op.hardswish.19.0" = Mul ("Add.141", val_30)
|
||||
val_31 = Add ("p2o.pd_op.hardswish.19.0", "conv2d_185.w_0_lab_laboffset")
|
||||
"Add.147" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_31, "conv2d_185.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.12.0_bias_lab")
|
||||
val_32 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.147")
|
||||
"p2o.pd_op.hardswish.20.0" = Mul ("Add.147", val_32)
|
||||
"Add.153" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.20.0", "conv2d_186.w_0_lab_lab", "p2o.pd_op.conv2d.17.0_bias_lab_lab")
|
||||
val_33 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.153")
|
||||
"p2o.pd_op.hardswish.21.0" = Mul ("Add.153", val_33)
|
||||
val_34 = Add ("p2o.pd_op.hardswish.21.0", "conv2d_187.w_0_lab_laboffset")
|
||||
"Add.159" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_34, "conv2d_187.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.13.0_bias_lab")
|
||||
val_35 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.159")
|
||||
"p2o.pd_op.hardswish.22.0" = Mul ("Add.159", val_35)
|
||||
"Add.165" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.22.0", "conv2d_188.w_0_lab_lab", "p2o.pd_op.conv2d.18.0_bias_lab_lab")
|
||||
val_36 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.165")
|
||||
"p2o.pd_op.hardswish.23.0" = Mul ("Add.165", val_36)
|
||||
"p2o.pd_op.conv2d.23.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.23.0", "Conv.37_folded_w_lab", "Conv.37_folded_b_lab")
|
||||
["GlobalAveragePool.2"] "p2o.pd_op.pool2d.2.0" = GlobalAveragePool ("p2o.pd_op.conv2d.23.0")
|
||||
"p2o.pd_op.conv2d.26.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_26, "Conv.40_folded_w_labscale", "Conv.40_folded_b")
|
||||
["GlobalAveragePool.3"] "p2o.pd_op.pool2d.3.0" = GlobalAveragePool ("p2o.pd_op.conv2d.26.0")
|
||||
"p2o.pd_op.conv2d.29.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_12, "Conv.43_folded_w_labscale", "Conv.43_folded_b")
|
||||
["GlobalAveragePool.4"] "p2o.pd_op.pool2d.4.0" = GlobalAveragePool ("p2o.pd_op.conv2d.29.0")
|
||||
"p2o.pd_op.conv2d.32.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_7, "Conv.46_folded_w_labscale", "Conv.46_folded_b")
|
||||
["GlobalAveragePool.5"] "p2o.pd_op.pool2d.5.0" = GlobalAveragePool ("p2o.pd_op.conv2d.32.0")
|
||||
se_group0_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.2.0", "p2o.pd_op.pool2d.3.0", "p2o.pd_op.pool2d.4.0", "p2o.pd_op.pool2d.5.0")
|
||||
se_group0_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_pooled, se_group0_down1, se_group0_down2)
|
||||
se_group0_relu = Relu (se_group0_down)
|
||||
se_group0_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_relu, se_group0_up1, se_group0_up2)
|
||||
se_group0_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group0_up)
|
||||
"se_group0_p2o.pd_op.hardsigmoid.2.0", "se_group0_p2o.pd_op.hardsigmoid.3.0", "se_group0_p2o.pd_op.hardsigmoid.4.0", "se_group0_p2o.pd_op.hardsigmoid.5.0" = Split <axis: int = 1> (se_group0_gates, se_group0_sizes)
|
||||
val_37 = Add ("se_group0_p2o.pd_op.hardsigmoid.2.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.181" = Mul ("p2o.pd_op.conv2d.23.0", val_37)
|
||||
val_38 = Add ("se_group0_p2o.pd_op.hardsigmoid.3.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.187" = Mul ("p2o.pd_op.conv2d.26.0", val_38)
|
||||
val_39 = Add ("se_group0_p2o.pd_op.hardsigmoid.4.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.193" = Mul ("p2o.pd_op.conv2d.29.0", val_39)
|
||||
val_40 = Add ("se_group0_p2o.pd_op.hardsigmoid.5.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.199" = Mul ("p2o.pd_op.conv2d.32.0", val_40)
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.181", "helper.constant.1", "helper.constant.0")
|
||||
["Add.200"] "Add.201" = Add ("Add.187", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.201", "helper.constant.1", "helper.constant.0")
|
||||
["Add.202"] "Add.203" = Add ("Add.193", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.203", "helper.constant.1", "helper.constant.0")
|
||||
["Add.204"] "Add.205" = Add ("Add.199", "p2o.pd_op.nearest_interp.2.0")
|
||||
["Conv.49"] "p2o.pd_op.conv2d.35.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.181", "conv2d_156.w_0")
|
||||
["GlobalAveragePool.6"] "p2o.pd_op.pool2d.6.0" = GlobalAveragePool ("p2o.pd_op.conv2d.35.0")
|
||||
["Conv.52"] "p2o.pd_op.conv2d.38.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.201", "conv2d_150.w_0")
|
||||
["GlobalAveragePool.7"] "p2o.pd_op.pool2d.7.0" = GlobalAveragePool ("p2o.pd_op.conv2d.38.0")
|
||||
["Conv.55"] "p2o.pd_op.conv2d.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.203", "conv2d_144.w_0")
|
||||
["GlobalAveragePool.8"] "p2o.pd_op.pool2d.8.0" = GlobalAveragePool ("p2o.pd_op.conv2d.41.0")
|
||||
["Conv.58"] "p2o.pd_op.conv2d.44.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.205", "conv2d_138.w_0")
|
||||
["GlobalAveragePool.9"] "p2o.pd_op.pool2d.9.0" = GlobalAveragePool ("p2o.pd_op.conv2d.44.0")
|
||||
se_group1_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.6.0", "p2o.pd_op.pool2d.7.0", "p2o.pd_op.pool2d.8.0", "p2o.pd_op.pool2d.9.0")
|
||||
se_group1_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_pooled, se_group1_down1, se_group1_down2)
|
||||
se_group1_relu = Relu (se_group1_down)
|
||||
se_group1_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_relu, se_group1_up1, se_group1_up2)
|
||||
se_group1_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group1_up)
|
||||
"se_group1_p2o.pd_op.hardsigmoid.6.0", "se_group1_p2o.pd_op.hardsigmoid.7.0", "se_group1_p2o.pd_op.hardsigmoid.8.0", "se_group1_p2o.pd_op.hardsigmoid.9.0" = Split <axis: int = 1> (se_group1_gates, se_group1_sizes)
|
||||
val_41 = Add ("se_group1_p2o.pd_op.hardsigmoid.6.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.211" = Mul ("p2o.pd_op.conv2d.35.0", val_41)
|
||||
val_42 = Add ("se_group1_p2o.pd_op.hardsigmoid.7.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.217" = Mul ("p2o.pd_op.conv2d.38.0", val_42)
|
||||
val_43 = Add ("se_group1_p2o.pd_op.hardsigmoid.8.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.223" = Mul ("p2o.pd_op.conv2d.41.0", val_43)
|
||||
val_44 = Add ("se_group1_p2o.pd_op.hardsigmoid.9.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.229" = Mul ("p2o.pd_op.conv2d.44.0", val_44)
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.211", "helper.constant.1", "helper.constant.6")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.217", "helper.constant.1", "helper.constant.8")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.223", "helper.constant.1", "helper.constant.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.229")
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.1", "conv2d_159.w_0", "conv2d_159.w_0_bias")
|
||||
["Relu.10"] "p2o.pd_op.relu.10.0" = Relu ("p2o.pd_op.batch_norm_.1.0")
|
||||
"p2o.pd_op.batch_norm_.2.0" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.10.0", "auto.cast.57", "ConvTranspose.1_bias")
|
||||
["Relu.11"] "p2o.pd_op.relu.11.0" = Relu ("p2o.pd_op.batch_norm_.2.0")
|
||||
"Add.233" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.11.0", "auto.cast.60", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] fetch_name_0 = Sigmoid ("Add.233")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
Conv.37_folded_b_lab FLOAT[96] 0d571951a1e0
|
||||
Conv.37_folded_w_lab FLOAT[96,384,1,1] 1d0305563ea7
|
||||
Conv.40_folded_b FLOAT[96] dcfdd514912d
|
||||
Conv.40_folded_w_labscale FLOAT[96,192,1,1] bacc8274202e
|
||||
Conv.43_folded_b FLOAT[96] ee902cf71aad
|
||||
Conv.43_folded_w_labscale FLOAT[96,96,1,1] b17e08485dc5
|
||||
Conv.46_folded_b FLOAT[96] 6541e510a35d
|
||||
Conv.46_folded_w_labscale FLOAT[96,48,1,1] 9423b2c0951a
|
||||
ConvTranspose.1_bias FLOAT[24] 64cabf62980d
|
||||
ConvTranspose.3_bias FLOAT[1] 55c86fee1edb
|
||||
auto.cast.57 FLOAT[24,24,2,2] 1dc864bec64f
|
||||
auto.cast.60 FLOAT[24,1,2,2] c9862b3a19bc
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_0.w_0 FLOAT[16,3,3,3] 7841f2f3efae
|
||||
conv2d_0.w_0_bias FLOAT[16] 2713bf453fd1
|
||||
conv2d_107.w_0 FLOAT[96,384,1,1] 2fc401aa1ec6
|
||||
conv2d_108.w_0 FLOAT[384,96,1,1] f2a9a9261c07
|
||||
conv2d_138.w_0 FLOAT[24,96,3,3] 47aa8ba1db50
|
||||
conv2d_144.w_0 FLOAT[24,96,3,3] cd85b03c436c
|
||||
conv2d_150.w_0 FLOAT[24,96,3,3] 591f14004ce0
|
||||
conv2d_156.w_0 FLOAT[24,96,3,3] 5e0bc4bf821e
|
||||
conv2d_159.w_0 FLOAT[24,96,3,3] 43b6b1b17bef
|
||||
conv2d_159.w_0_bias FLOAT[24] c98267f8273d
|
||||
conv2d_161.w_0_lab FLOAT[16,1,3,3] 22528d709d37
|
||||
conv2d_162.w_0_lab_lab FLOAT[32,16,1,1] 051645505e21
|
||||
conv2d_163.w_0_lab_laboffset FLOAT[] 92a142f7dc41
|
||||
conv2d_163.w_0_lab_labscale FLOAT[32,1,3,3] 8694842bd3fb
|
||||
conv2d_164.w_0_lab FLOAT[48,32,1,1] 0c937f040d0e
|
||||
conv2d_165.w_0_lab_laboffset FLOAT[] 012179917694
|
||||
conv2d_165.w_0_lab_labscale FLOAT[48,1,3,3] 7d779e5616fa
|
||||
conv2d_166.w_0_lab_lab FLOAT[48,48,1,1] d70c86b2d1ec
|
||||
conv2d_167.w_0_lab_laboffset FLOAT[] 9741b37d98e3
|
||||
conv2d_167.w_0_lab_labscale FLOAT[48,1,3,3] fa2e1db2eb62
|
||||
conv2d_168.w_0_lab FLOAT[96,48,1,1] 81e13e0bd382
|
||||
conv2d_169.w_0_lab_laboffset FLOAT[] f3e015d53e9a
|
||||
conv2d_169.w_0_lab_labscale FLOAT[96,1,3,3] 75bbb69deb68
|
||||
conv2d_170.w_0_lab_lab FLOAT[96,96,1,1] 59b22a69e345
|
||||
conv2d_171.w_0_lab_laboffset FLOAT[] f42328163f40
|
||||
conv2d_171.w_0_lab_labscale FLOAT[96,1,3,3] 65cbca6287a2
|
||||
conv2d_172.w_0_lab FLOAT[192,96,1,1] ff93ca701d2f
|
||||
conv2d_173.w_0_lab_laboffset FLOAT[] b76450d3656f
|
||||
conv2d_173.w_0_lab_labscale FLOAT[192,1,5,5] 28d7de00679c
|
||||
conv2d_174.w_0_lab_lab FLOAT[192,192,1,1] 53cf6f343ec2
|
||||
conv2d_175.w_0_lab_laboffset FLOAT[] e665434a5d2d
|
||||
conv2d_175.w_0_lab_labscale FLOAT[192,1,5,5] 3c0aa815839d
|
||||
conv2d_176.w_0_lab_lab FLOAT[192,192,1,1] cb45f031f07b
|
||||
conv2d_177.w_0_lab_laboffset FLOAT[] e095ffc76247
|
||||
conv2d_177.w_0_lab_labscale FLOAT[192,1,5,5] 22fe03b75591
|
||||
conv2d_178.w_0_lab_lab FLOAT[192,192,1,1] c259022f5c3d
|
||||
conv2d_179.w_0_lab_laboffset FLOAT[] 5842420f0e64
|
||||
conv2d_179.w_0_lab_labscale FLOAT[192,1,5,5] 408bbab0d507
|
||||
conv2d_180.w_0_lab_lab FLOAT[192,192,1,1] 85871ea30bf1
|
||||
conv2d_181.w_0_lab_laboffset FLOAT[] 9e0407355f14
|
||||
conv2d_181.w_0_lab_labscale FLOAT[192,1,5,5] 75764b0f5265
|
||||
conv2d_182.w_0_lab FLOAT[384,192,1,1] 81235d1a972f
|
||||
conv2d_183.w_0_lab_laboffset FLOAT[] e648d792317a
|
||||
conv2d_183.w_0_lab_labscale FLOAT[384,1,5,5] f5341adaad28
|
||||
conv2d_184.w_0_lab FLOAT[384,384,1,1] c37a7cec640b
|
||||
conv2d_185.w_0_lab_laboffset FLOAT[] 768fa13da14b
|
||||
conv2d_185.w_0_lab_labscale FLOAT[384,1,5,5] 6bacb713155c
|
||||
conv2d_186.w_0_lab_lab FLOAT[384,384,1,1] 2fa80ae1b18f
|
||||
conv2d_187.w_0_lab_laboffset FLOAT[] ad505dafbd90
|
||||
conv2d_187.w_0_lab_labscale FLOAT[384,1,5,5] a221bd8406f2
|
||||
conv2d_188.w_0_lab_lab FLOAT[384,384,1,1] 9ea062b2f1b4
|
||||
conv2d_96.w_0 FLOAT[48,192,1,1] 6d73ce1fb738
|
||||
conv2d_97.w_0 FLOAT[192,48,1,1] 8098a00a81f0
|
||||
helper.constant.0 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.1 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.6 FLOAT[4] cf5451a623be
|
||||
helper.constant.8 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
learnable_affine_block_45.w_0 FLOAT[1] 65444e550b77
|
||||
learnable_affine_block_45.w_1 FLOAT[1] f2ee18a061af
|
||||
p2o.pd_op.conv2d.1.0_bias_lab_lab FLOAT[32] 3f4be24e33b8
|
||||
p2o.pd_op.conv2d.10.0_bias_lab_lab FLOAT[192] e32536500417
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[48] 961ec85108cb
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[192] c348751cbed0
|
||||
p2o.pd_op.conv2d.13.0_bias_lab FLOAT[384] 1b6d0aa0e977
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[96] 7876208c6fb1
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[384] 871907fff11d
|
||||
p2o.pd_op.conv2d.16.0_bias_lab FLOAT[384] fd15d67f1e85
|
||||
p2o.pd_op.conv2d.17.0_bias_lab_lab FLOAT[384] 097f0d068f05
|
||||
p2o.pd_op.conv2d.18.0_bias_lab_lab FLOAT[384] b8e228cae698
|
||||
p2o.pd_op.conv2d.2.0_bias_lab FLOAT[48] 8138a593f8f2
|
||||
p2o.pd_op.conv2d.3.0_bias_lab_lab FLOAT[48] 57128b896e31
|
||||
p2o.pd_op.conv2d.4.0_bias_lab FLOAT[96] d2230ff7a27e
|
||||
p2o.pd_op.conv2d.5.0_bias_lab_lab FLOAT[96] 05b9a5f236b6
|
||||
p2o.pd_op.conv2d.6.0_bias_lab FLOAT[192] a990b3fed4dd
|
||||
p2o.pd_op.conv2d.7.0_bias_lab_lab FLOAT[192] 74df3e4f22b6
|
||||
p2o.pd_op.conv2d.8.0_bias_lab_lab FLOAT[192] 9c072f4b4032
|
||||
p2o.pd_op.conv2d.9.0_bias_lab_lab FLOAT[192] 8f6e7021fe63
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias_lab FLOAT[16] 5b3de9e3f7c2
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias_lab FLOAT[32] bb4239a962eb
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias_lab FLOAT[192] 81ac3c08eae1
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias_lab FLOAT[384] 2236a6b52e38
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias_lab FLOAT[384] 14c22d416e3b
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias_lab FLOAT[384] 4eebd04fbeb4
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias_lab FLOAT[48] aaee6f6db9c1
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias_lab FLOAT[48] dcc78f972645
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias_lab FLOAT[96] dbd763cef105
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias_lab FLOAT[96] 5849d6801824
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias_lab FLOAT[192] 01e9219938aa
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias_lab FLOAT[192] e35d55fdac89
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias_lab FLOAT[192] fd7c6cc0a8fb
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias_lab FLOAT[192] aedc2ab77e2b
|
||||
p2o.pd_op.hardsigmoid.2.0_one FLOAT[] e00e5eb94441
|
||||
se_group0_down1 FLOAT[96,96,1,1] 4c8c888b01f2
|
||||
se_group0_down2 FLOAT[96] b99146f86442
|
||||
se_group0_sizes INT64[4] 4bb249469bee
|
||||
se_group0_up1 FLOAT[384,24,1,1] 1446892243f3
|
||||
se_group0_up2 FLOAT[384] 8538540d9317
|
||||
se_group1_down1 FLOAT[24,24,1,1] 01a670ee8021
|
||||
se_group1_down2 FLOAT[24] 7f8067be0db7
|
||||
se_group1_sizes INT64[4] 5c995dc6a0ef
|
||||
se_group1_up1 FLOAT[96,6,1,1] 3e47b305535b
|
||||
se_group1_up2 FLOAT[96] ed3a93d396c3
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,468 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,192,unk__22,unk__23] "Add.105"
|
||||
float[batch,192,unk__22,unk__23] "Add.111"
|
||||
float[batch,192,unk__42,unk__43] "Add.117"
|
||||
float[batch,48,1,1] "Add.119"
|
||||
float[batch,192,1,1] "Add.121"
|
||||
float[batch,384,unk__42,unk__43] "Add.125"
|
||||
float[batch,384,unk__42,unk__43] "Add.131"
|
||||
float[batch,384,unk__42,unk__43] "Add.133"
|
||||
float[batch,96,1,1] "Add.135"
|
||||
float[batch,384,1,1] "Add.137"
|
||||
float[batch,384,unk__42,unk__43] "Add.141"
|
||||
float[batch,384,unk__42,unk__43] "Add.147"
|
||||
float[batch,32,unk__6,unk__7] "Add.15"
|
||||
float[batch,384,unk__42,unk__43] "Add.153"
|
||||
float[batch,384,unk__42,unk__43] "Add.159"
|
||||
float[batch,384,unk__42,unk__43] "Add.165"
|
||||
float[batch,96,unk__42,unk__43] "Add.181"
|
||||
float[batch,96,unk__22,unk__23] "Add.187"
|
||||
float[batch,48,unk__6,unk__7] "Add.19"
|
||||
float[batch,96,unk__14,unk__15] "Add.193"
|
||||
float[batch,96,unk__6,unk__7] "Add.199"
|
||||
float[batch,96,unk__22,unk__23] "Add.201"
|
||||
float[batch,96,unk__14,unk__15] "Add.203"
|
||||
float[batch,96,unk__6,unk__7] "Add.205"
|
||||
float[batch,24,unk__42,unk__43] "Add.211"
|
||||
float[batch,24,unk__22,unk__23] "Add.217"
|
||||
float[batch,24,unk__14,unk__15] "Add.223"
|
||||
float[batch,24,unk__6,unk__7] "Add.229"
|
||||
float[batch,1,height,width] "Add.233"
|
||||
float[batch,48,unk__6,unk__7] "Add.25"
|
||||
float[batch,16,unk__0,unk__1] "Add.3"
|
||||
float[batch,48,unk__6,unk__7] "Add.31"
|
||||
float[batch,48,unk__14,unk__15] "Add.37"
|
||||
float[batch,96,unk__14,unk__15] "Add.41"
|
||||
float[batch,96,unk__14,unk__15] "Add.47"
|
||||
float[batch,96,unk__14,unk__15] "Add.53"
|
||||
float[batch,96,unk__22,unk__23] "Add.59"
|
||||
float[batch,192,unk__22,unk__23] "Add.63"
|
||||
float[batch,192,unk__22,unk__23] "Add.69"
|
||||
float[batch,192,unk__22,unk__23] "Add.75"
|
||||
float[batch,192,unk__22,unk__23] "Add.81"
|
||||
float[batch,192,unk__22,unk__23] "Add.87"
|
||||
float[batch,32,unk__0,unk__1] "Add.9"
|
||||
float[batch,192,unk__22,unk__23] "Add.93"
|
||||
float[batch,192,unk__22,unk__23] "Add.99"
|
||||
float[batch,96,unk__6,unk__7] "Concat.1"
|
||||
float[batch,192,unk__42,unk__43] "Mul.77"
|
||||
float[batch,384,unk__42,unk__43] "Mul.85"
|
||||
float[batch,384,unk__42,unk__43] "Mul.87"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,96,unk__42,unk__43] "p2o.pd_op.conv2d.23.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.conv2d.26.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.conv2d.29.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.conv2d.32.0"
|
||||
float[batch,24,unk__42,unk__43] "p2o.pd_op.conv2d.35.0"
|
||||
float[batch,24,unk__22,unk__23] "p2o.pd_op.conv2d.38.0"
|
||||
float[batch,24,unk__14,unk__15] "p2o.pd_op.conv2d.41.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.conv2d.44.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.hardswish.0.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.hardswish.1.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.10.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.11.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.12.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.13.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.14.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.15.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.16.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.17.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.18.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.19.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.2.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.20.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.21.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.22.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.23.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.3.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.4.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.5.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.6.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.7.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.8.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.9.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.pool2d.1.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.2.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.3.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.4.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.5.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.6.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.7.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.8.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.9.0"
|
||||
float[batch,48,1,1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.relu.10.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.relu.11.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.2.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.3.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.4.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.5.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.6.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.7.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.8.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.9.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,96,1,1] se_group0_down
|
||||
float[batch,384,1,1] se_group0_gates
|
||||
float[batch,384,1,1] se_group0_pooled
|
||||
float[batch,96,1,1] se_group0_relu
|
||||
float[batch,384,1,1] se_group0_up
|
||||
float[batch,24,1,1] se_group1_down
|
||||
float[batch,96,1,1] se_group1_gates
|
||||
float[batch,96,1,1] se_group1_pooled
|
||||
float[batch,24,1,1] se_group1_relu
|
||||
float[batch,96,1,1] se_group1_up
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,16,unk__0,unk__1] val_0
|
||||
float[batch,32,unk__0,unk__1] val_1
|
||||
float[batch,96,unk__14,unk__15] val_10
|
||||
float[batch,96,unk__14,unk__15] val_11
|
||||
float[batch,96,unk__14,unk__15] val_12
|
||||
float[batch,192,unk__22,unk__23] val_13
|
||||
float[batch,192,unk__22,unk__23] val_14
|
||||
float[batch,192,unk__22,unk__23] val_15
|
||||
float[batch,192,unk__22,unk__23] val_16
|
||||
float[batch,192,unk__22,unk__23] val_17
|
||||
float[batch,192,unk__22,unk__23] val_18
|
||||
float[batch,192,unk__22,unk__23] val_19
|
||||
float[batch,32,unk__0,unk__1] val_2
|
||||
float[batch,192,unk__22,unk__23] val_20
|
||||
float[batch,192,unk__22,unk__23] val_21
|
||||
float[batch,192,unk__22,unk__23] val_22
|
||||
float[batch,192,unk__22,unk__23] val_23
|
||||
float[batch,192,unk__22,unk__23] val_24
|
||||
float[batch,192,unk__22,unk__23] val_25
|
||||
float[batch,192,unk__22,unk__23] val_26
|
||||
float[batch,384,unk__42,unk__43] val_27
|
||||
float[batch,384,unk__42,unk__43] val_28
|
||||
float[batch,384,unk__42,unk__43] val_29
|
||||
float[batch,48,unk__6,unk__7] val_3
|
||||
float[batch,384,unk__42,unk__43] val_30
|
||||
float[batch,384,unk__42,unk__43] val_31
|
||||
float[batch,384,unk__42,unk__43] val_32
|
||||
float[batch,384,unk__42,unk__43] val_33
|
||||
float[batch,384,unk__42,unk__43] val_34
|
||||
float[batch,384,unk__42,unk__43] val_35
|
||||
float[batch,384,unk__42,unk__43] val_36
|
||||
float[batch,96,1,1] val_37
|
||||
float[batch,96,1,1] val_38
|
||||
float[batch,96,1,1] val_39
|
||||
float[batch,48,unk__6,unk__7] val_4
|
||||
float[batch,96,1,1] val_40
|
||||
float[batch,24,1,1] val_41
|
||||
float[batch,24,1,1] val_42
|
||||
float[batch,24,1,1] val_43
|
||||
float[batch,24,1,1] val_44
|
||||
float[batch,48,unk__6,unk__7] val_5
|
||||
float[batch,48,unk__6,unk__7] val_6
|
||||
float[batch,48,unk__6,unk__7] val_7
|
||||
float[batch,96,unk__14,unk__15] val_8
|
||||
float[batch,96,unk__14,unk__15] val_9
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_0.w_0", "conv2d_0.w_0_bias")
|
||||
"Add.3" = Conv <dilations: ints = [1, 1], group: int = 16, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.0.0", "conv2d_161.w_0_lab", "p2o.pd_op.depthwise_conv2d.0.0_bias_lab")
|
||||
val_0 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.3")
|
||||
"p2o.pd_op.hardswish.0.0" = Mul ("Add.3", val_0)
|
||||
"Add.9" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.0.0", "conv2d_162.w_0_lab_lab", "p2o.pd_op.conv2d.1.0_bias_lab_lab")
|
||||
val_1 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.9")
|
||||
"p2o.pd_op.hardswish.1.0" = Mul ("Add.9", val_1)
|
||||
val_2 = Add ("p2o.pd_op.hardswish.1.0", "conv2d_163.w_0_lab_laboffset")
|
||||
"Add.15" = Conv <dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_2, "conv2d_163.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.1.0_bias_lab")
|
||||
"Add.19" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.15", "conv2d_164.w_0_lab", "p2o.pd_op.conv2d.2.0_bias_lab")
|
||||
val_3 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.19")
|
||||
"p2o.pd_op.hardswish.2.0" = Mul ("Add.19", val_3)
|
||||
val_4 = Add ("p2o.pd_op.hardswish.2.0", "conv2d_165.w_0_lab_laboffset")
|
||||
"Add.25" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_4, "conv2d_165.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.2.0_bias_lab")
|
||||
val_5 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.25")
|
||||
"p2o.pd_op.hardswish.3.0" = Mul ("Add.25", val_5)
|
||||
"Add.31" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.3.0", "conv2d_166.w_0_lab_lab", "p2o.pd_op.conv2d.3.0_bias_lab_lab")
|
||||
val_6 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.31")
|
||||
"p2o.pd_op.hardswish.4.0" = Mul ("Add.31", val_6)
|
||||
val_7 = Add ("p2o.pd_op.hardswish.4.0", "conv2d_167.w_0_lab_laboffset")
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_7, "conv2d_167.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.3.0_bias_lab")
|
||||
"Add.41" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.37", "conv2d_168.w_0_lab", "p2o.pd_op.conv2d.4.0_bias_lab")
|
||||
val_8 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.41")
|
||||
"p2o.pd_op.hardswish.5.0" = Mul ("Add.41", val_8)
|
||||
val_9 = Add ("p2o.pd_op.hardswish.5.0", "conv2d_169.w_0_lab_laboffset")
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_9, "conv2d_169.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.4.0_bias_lab")
|
||||
val_10 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.47")
|
||||
"p2o.pd_op.hardswish.6.0" = Mul ("Add.47", val_10)
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.6.0", "conv2d_170.w_0_lab_lab", "p2o.pd_op.conv2d.5.0_bias_lab_lab")
|
||||
val_11 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.53")
|
||||
"p2o.pd_op.hardswish.7.0" = Mul ("Add.53", val_11)
|
||||
val_12 = Add ("p2o.pd_op.hardswish.7.0", "conv2d_171.w_0_lab_laboffset")
|
||||
"Add.59" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_12, "conv2d_171.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.5.0_bias_lab")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.59", "conv2d_172.w_0_lab", "p2o.pd_op.conv2d.6.0_bias_lab")
|
||||
val_13 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.63")
|
||||
"p2o.pd_op.hardswish.8.0" = Mul ("Add.63", val_13)
|
||||
val_14 = Add ("p2o.pd_op.hardswish.8.0", "conv2d_173.w_0_lab_laboffset")
|
||||
"Add.69" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_14, "conv2d_173.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.6.0_bias_lab")
|
||||
val_15 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.69")
|
||||
"p2o.pd_op.hardswish.9.0" = Mul ("Add.69", val_15)
|
||||
"Add.75" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.9.0", "conv2d_174.w_0_lab_lab", "p2o.pd_op.conv2d.7.0_bias_lab_lab")
|
||||
val_16 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.75")
|
||||
"p2o.pd_op.hardswish.10.0" = Mul ("Add.75", val_16)
|
||||
val_17 = Add ("p2o.pd_op.hardswish.10.0", "conv2d_175.w_0_lab_laboffset")
|
||||
"Add.81" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_17, "conv2d_175.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.7.0_bias_lab")
|
||||
val_18 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.81")
|
||||
"p2o.pd_op.hardswish.11.0" = Mul ("Add.81", val_18)
|
||||
"Add.87" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.11.0", "conv2d_176.w_0_lab_lab", "p2o.pd_op.conv2d.8.0_bias_lab_lab")
|
||||
val_19 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.87")
|
||||
"p2o.pd_op.hardswish.12.0" = Mul ("Add.87", val_19)
|
||||
val_20 = Add ("p2o.pd_op.hardswish.12.0", "conv2d_177.w_0_lab_laboffset")
|
||||
"Add.93" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_20, "conv2d_177.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.8.0_bias_lab")
|
||||
val_21 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.93")
|
||||
"p2o.pd_op.hardswish.13.0" = Mul ("Add.93", val_21)
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.13.0", "conv2d_178.w_0_lab_lab", "p2o.pd_op.conv2d.9.0_bias_lab_lab")
|
||||
val_22 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.99")
|
||||
"p2o.pd_op.hardswish.14.0" = Mul ("Add.99", val_22)
|
||||
val_23 = Add ("p2o.pd_op.hardswish.14.0", "conv2d_179.w_0_lab_laboffset")
|
||||
"Add.105" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_23, "conv2d_179.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.9.0_bias_lab")
|
||||
val_24 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.105")
|
||||
"p2o.pd_op.hardswish.15.0" = Mul ("Add.105", val_24)
|
||||
"Add.111" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.15.0", "conv2d_180.w_0_lab_lab", "p2o.pd_op.conv2d.10.0_bias_lab_lab")
|
||||
val_25 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.111")
|
||||
"p2o.pd_op.hardswish.16.0" = Mul ("Add.111", val_25)
|
||||
val_26 = Add ("p2o.pd_op.hardswish.16.0", "conv2d_181.w_0_lab_laboffset")
|
||||
"Add.117" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [2, 2]> (val_26, "conv2d_181.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.10.0_bias_lab")
|
||||
["GlobalAveragePool.0"] "p2o.pd_op.pool2d.0.0" = GlobalAveragePool ("Add.117")
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.0.0", "conv2d_96.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.119")
|
||||
"Add.121" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_97.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.121")
|
||||
["Mul.76"] "Mul.77" = Mul ("Add.117", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.77", "conv2d_182.w_0_lab", "p2o.pd_op.conv2d.13.0_bias_lab")
|
||||
val_27 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.125")
|
||||
"p2o.pd_op.hardswish.17.0" = Mul ("Add.125", val_27)
|
||||
val_28 = Add ("p2o.pd_op.hardswish.17.0", "conv2d_183.w_0_lab_laboffset")
|
||||
"Add.131" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_28, "conv2d_183.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.11.0_bias_lab")
|
||||
val_29 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.131")
|
||||
"p2o.pd_op.hardswish.18.0" = Mul ("Add.131", val_29)
|
||||
["Mul.84"] "Mul.85" = Mul ("learnable_affine_block_45.w_0", "p2o.pd_op.hardswish.18.0")
|
||||
["Add.132"] "Add.133" = Add ("Mul.85", "learnable_affine_block_45.w_1")
|
||||
["GlobalAveragePool.1"] "p2o.pd_op.pool2d.1.0" = GlobalAveragePool ("Add.133")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.1.0", "conv2d_107.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.135")
|
||||
"Add.137" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_108.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.137")
|
||||
["Mul.86"] "Mul.87" = Mul ("Add.133", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.141" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.87", "conv2d_184.w_0_lab", "p2o.pd_op.conv2d.16.0_bias_lab")
|
||||
val_30 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.141")
|
||||
"p2o.pd_op.hardswish.19.0" = Mul ("Add.141", val_30)
|
||||
val_31 = Add ("p2o.pd_op.hardswish.19.0", "conv2d_185.w_0_lab_laboffset")
|
||||
"Add.147" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_31, "conv2d_185.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.12.0_bias_lab")
|
||||
val_32 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.147")
|
||||
"p2o.pd_op.hardswish.20.0" = Mul ("Add.147", val_32)
|
||||
"Add.153" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.20.0", "conv2d_186.w_0_lab_lab", "p2o.pd_op.conv2d.17.0_bias_lab_lab")
|
||||
val_33 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.153")
|
||||
"p2o.pd_op.hardswish.21.0" = Mul ("Add.153", val_33)
|
||||
val_34 = Add ("p2o.pd_op.hardswish.21.0", "conv2d_187.w_0_lab_laboffset")
|
||||
"Add.159" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_34, "conv2d_187.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.13.0_bias_lab")
|
||||
val_35 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.159")
|
||||
"p2o.pd_op.hardswish.22.0" = Mul ("Add.159", val_35)
|
||||
"Add.165" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.22.0", "conv2d_188.w_0_lab_lab", "p2o.pd_op.conv2d.18.0_bias_lab_lab")
|
||||
val_36 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.165")
|
||||
"p2o.pd_op.hardswish.23.0" = Mul ("Add.165", val_36)
|
||||
"p2o.pd_op.conv2d.23.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.23.0", "Conv.37_folded_w_lab", "Conv.37_folded_b_lab")
|
||||
["GlobalAveragePool.2"] "p2o.pd_op.pool2d.2.0" = GlobalAveragePool ("p2o.pd_op.conv2d.23.0")
|
||||
"p2o.pd_op.conv2d.26.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_26, "Conv.40_folded_w_labscale", "Conv.40_folded_b")
|
||||
["GlobalAveragePool.3"] "p2o.pd_op.pool2d.3.0" = GlobalAveragePool ("p2o.pd_op.conv2d.26.0")
|
||||
"p2o.pd_op.conv2d.29.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_12, "Conv.43_folded_w_labscale", "Conv.43_folded_b")
|
||||
["GlobalAveragePool.4"] "p2o.pd_op.pool2d.4.0" = GlobalAveragePool ("p2o.pd_op.conv2d.29.0")
|
||||
"p2o.pd_op.conv2d.32.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_7, "Conv.46_folded_w_labscale", "Conv.46_folded_b")
|
||||
["GlobalAveragePool.5"] "p2o.pd_op.pool2d.5.0" = GlobalAveragePool ("p2o.pd_op.conv2d.32.0")
|
||||
se_group0_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.2.0", "p2o.pd_op.pool2d.3.0", "p2o.pd_op.pool2d.4.0", "p2o.pd_op.pool2d.5.0")
|
||||
se_group0_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_pooled, se_group0_down1, se_group0_down2)
|
||||
se_group0_relu = Relu (se_group0_down)
|
||||
se_group0_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_relu, se_group0_up1, se_group0_up2)
|
||||
se_group0_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group0_up)
|
||||
"se_group0_p2o.pd_op.hardsigmoid.2.0", "se_group0_p2o.pd_op.hardsigmoid.3.0", "se_group0_p2o.pd_op.hardsigmoid.4.0", "se_group0_p2o.pd_op.hardsigmoid.5.0" = Split <axis: int = 1> (se_group0_gates, se_group0_sizes)
|
||||
val_37 = Add ("se_group0_p2o.pd_op.hardsigmoid.2.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.181" = Mul ("p2o.pd_op.conv2d.23.0", val_37)
|
||||
val_38 = Add ("se_group0_p2o.pd_op.hardsigmoid.3.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.187" = Mul ("p2o.pd_op.conv2d.26.0", val_38)
|
||||
val_39 = Add ("se_group0_p2o.pd_op.hardsigmoid.4.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.193" = Mul ("p2o.pd_op.conv2d.29.0", val_39)
|
||||
val_40 = Add ("se_group0_p2o.pd_op.hardsigmoid.5.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.199" = Mul ("p2o.pd_op.conv2d.32.0", val_40)
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.181", "helper.constant.1", "helper.constant.0")
|
||||
["Add.200"] "Add.201" = Add ("Add.187", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.201", "helper.constant.1", "helper.constant.0")
|
||||
["Add.202"] "Add.203" = Add ("Add.193", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.203", "helper.constant.1", "helper.constant.0")
|
||||
["Add.204"] "Add.205" = Add ("Add.199", "p2o.pd_op.nearest_interp.2.0")
|
||||
["Conv.49"] "p2o.pd_op.conv2d.35.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.181", "conv2d_156.w_0")
|
||||
["GlobalAveragePool.6"] "p2o.pd_op.pool2d.6.0" = GlobalAveragePool ("p2o.pd_op.conv2d.35.0")
|
||||
["Conv.52"] "p2o.pd_op.conv2d.38.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.201", "conv2d_150.w_0")
|
||||
["GlobalAveragePool.7"] "p2o.pd_op.pool2d.7.0" = GlobalAveragePool ("p2o.pd_op.conv2d.38.0")
|
||||
["Conv.55"] "p2o.pd_op.conv2d.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.203", "conv2d_144.w_0")
|
||||
["GlobalAveragePool.8"] "p2o.pd_op.pool2d.8.0" = GlobalAveragePool ("p2o.pd_op.conv2d.41.0")
|
||||
["Conv.58"] "p2o.pd_op.conv2d.44.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.205", "conv2d_138.w_0")
|
||||
["GlobalAveragePool.9"] "p2o.pd_op.pool2d.9.0" = GlobalAveragePool ("p2o.pd_op.conv2d.44.0")
|
||||
se_group1_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.6.0", "p2o.pd_op.pool2d.7.0", "p2o.pd_op.pool2d.8.0", "p2o.pd_op.pool2d.9.0")
|
||||
se_group1_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_pooled, se_group1_down1, se_group1_down2)
|
||||
se_group1_relu = Relu (se_group1_down)
|
||||
se_group1_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_relu, se_group1_up1, se_group1_up2)
|
||||
se_group1_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group1_up)
|
||||
"se_group1_p2o.pd_op.hardsigmoid.6.0", "se_group1_p2o.pd_op.hardsigmoid.7.0", "se_group1_p2o.pd_op.hardsigmoid.8.0", "se_group1_p2o.pd_op.hardsigmoid.9.0" = Split <axis: int = 1> (se_group1_gates, se_group1_sizes)
|
||||
val_41 = Add ("se_group1_p2o.pd_op.hardsigmoid.6.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.211" = Mul ("p2o.pd_op.conv2d.35.0", val_41)
|
||||
val_42 = Add ("se_group1_p2o.pd_op.hardsigmoid.7.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.217" = Mul ("p2o.pd_op.conv2d.38.0", val_42)
|
||||
val_43 = Add ("se_group1_p2o.pd_op.hardsigmoid.8.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.223" = Mul ("p2o.pd_op.conv2d.41.0", val_43)
|
||||
val_44 = Add ("se_group1_p2o.pd_op.hardsigmoid.9.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.229" = Mul ("p2o.pd_op.conv2d.44.0", val_44)
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.211", "helper.constant.1", "helper.constant.6")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.217", "helper.constant.1", "helper.constant.8")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.223", "helper.constant.1", "helper.constant.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.229")
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.1", "conv2d_159.w_0", "conv2d_159.w_0_bias")
|
||||
["Relu.10"] "p2o.pd_op.relu.10.0" = Relu ("p2o.pd_op.batch_norm_.1.0")
|
||||
"p2o.pd_op.batch_norm_.2.0" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.10.0", "auto.cast.57", "ConvTranspose.1_bias")
|
||||
["Relu.11"] "p2o.pd_op.relu.11.0" = Relu ("p2o.pd_op.batch_norm_.2.0")
|
||||
"Add.233" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.11.0", "auto.cast.60", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] fetch_name_0 = Sigmoid ("Add.233")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
Conv.37_folded_b_lab FLOAT[96] 0d571951a1e0
|
||||
Conv.37_folded_w_lab FLOAT[96,384,1,1] 1d0305563ea7
|
||||
Conv.40_folded_b FLOAT[96] dcfdd514912d
|
||||
Conv.40_folded_w_labscale FLOAT[96,192,1,1] bacc8274202e
|
||||
Conv.43_folded_b FLOAT[96] ee902cf71aad
|
||||
Conv.43_folded_w_labscale FLOAT[96,96,1,1] b17e08485dc5
|
||||
Conv.46_folded_b FLOAT[96] 6541e510a35d
|
||||
Conv.46_folded_w_labscale FLOAT[96,48,1,1] 9423b2c0951a
|
||||
ConvTranspose.1_bias FLOAT[24] 64cabf62980d
|
||||
ConvTranspose.3_bias FLOAT[1] 55c86fee1edb
|
||||
auto.cast.57 FLOAT[24,24,2,2] 1dc864bec64f
|
||||
auto.cast.60 FLOAT[24,1,2,2] c9862b3a19bc
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_0.w_0 FLOAT[16,3,3,3] 7841f2f3efae
|
||||
conv2d_0.w_0_bias FLOAT[16] 2713bf453fd1
|
||||
conv2d_107.w_0 FLOAT[96,384,1,1] 2fc401aa1ec6
|
||||
conv2d_108.w_0 FLOAT[384,96,1,1] f2a9a9261c07
|
||||
conv2d_138.w_0 FLOAT[24,96,3,3] 47aa8ba1db50
|
||||
conv2d_144.w_0 FLOAT[24,96,3,3] cd85b03c436c
|
||||
conv2d_150.w_0 FLOAT[24,96,3,3] 591f14004ce0
|
||||
conv2d_156.w_0 FLOAT[24,96,3,3] 5e0bc4bf821e
|
||||
conv2d_159.w_0 FLOAT[24,96,3,3] 43b6b1b17bef
|
||||
conv2d_159.w_0_bias FLOAT[24] c98267f8273d
|
||||
conv2d_161.w_0_lab FLOAT[16,1,3,3] 22528d709d37
|
||||
conv2d_162.w_0_lab_lab FLOAT[32,16,1,1] 051645505e21
|
||||
conv2d_163.w_0_lab_laboffset FLOAT[] 92a142f7dc41
|
||||
conv2d_163.w_0_lab_labscale FLOAT[32,1,3,3] 8694842bd3fb
|
||||
conv2d_164.w_0_lab FLOAT[48,32,1,1] 0c937f040d0e
|
||||
conv2d_165.w_0_lab_laboffset FLOAT[] 012179917694
|
||||
conv2d_165.w_0_lab_labscale FLOAT[48,1,3,3] 7d779e5616fa
|
||||
conv2d_166.w_0_lab_lab FLOAT[48,48,1,1] d70c86b2d1ec
|
||||
conv2d_167.w_0_lab_laboffset FLOAT[] 9741b37d98e3
|
||||
conv2d_167.w_0_lab_labscale FLOAT[48,1,3,3] fa2e1db2eb62
|
||||
conv2d_168.w_0_lab FLOAT[96,48,1,1] 81e13e0bd382
|
||||
conv2d_169.w_0_lab_laboffset FLOAT[] f3e015d53e9a
|
||||
conv2d_169.w_0_lab_labscale FLOAT[96,1,3,3] 75bbb69deb68
|
||||
conv2d_170.w_0_lab_lab FLOAT[96,96,1,1] 59b22a69e345
|
||||
conv2d_171.w_0_lab_laboffset FLOAT[] f42328163f40
|
||||
conv2d_171.w_0_lab_labscale FLOAT[96,1,3,3] 65cbca6287a2
|
||||
conv2d_172.w_0_lab FLOAT[192,96,1,1] ff93ca701d2f
|
||||
conv2d_173.w_0_lab_laboffset FLOAT[] b76450d3656f
|
||||
conv2d_173.w_0_lab_labscale FLOAT[192,1,5,5] 28d7de00679c
|
||||
conv2d_174.w_0_lab_lab FLOAT[192,192,1,1] 53cf6f343ec2
|
||||
conv2d_175.w_0_lab_laboffset FLOAT[] e665434a5d2d
|
||||
conv2d_175.w_0_lab_labscale FLOAT[192,1,5,5] 3c0aa815839d
|
||||
conv2d_176.w_0_lab_lab FLOAT[192,192,1,1] cb45f031f07b
|
||||
conv2d_177.w_0_lab_laboffset FLOAT[] e095ffc76247
|
||||
conv2d_177.w_0_lab_labscale FLOAT[192,1,5,5] 22fe03b75591
|
||||
conv2d_178.w_0_lab_lab FLOAT[192,192,1,1] c259022f5c3d
|
||||
conv2d_179.w_0_lab_laboffset FLOAT[] 5842420f0e64
|
||||
conv2d_179.w_0_lab_labscale FLOAT[192,1,5,5] 408bbab0d507
|
||||
conv2d_180.w_0_lab_lab FLOAT[192,192,1,1] 85871ea30bf1
|
||||
conv2d_181.w_0_lab_laboffset FLOAT[] 9e0407355f14
|
||||
conv2d_181.w_0_lab_labscale FLOAT[192,1,5,5] 75764b0f5265
|
||||
conv2d_182.w_0_lab FLOAT[384,192,1,1] 81235d1a972f
|
||||
conv2d_183.w_0_lab_laboffset FLOAT[] e648d792317a
|
||||
conv2d_183.w_0_lab_labscale FLOAT[384,1,5,5] f5341adaad28
|
||||
conv2d_184.w_0_lab FLOAT[384,384,1,1] c37a7cec640b
|
||||
conv2d_185.w_0_lab_laboffset FLOAT[] 768fa13da14b
|
||||
conv2d_185.w_0_lab_labscale FLOAT[384,1,5,5] 6bacb713155c
|
||||
conv2d_186.w_0_lab_lab FLOAT[384,384,1,1] 2fa80ae1b18f
|
||||
conv2d_187.w_0_lab_laboffset FLOAT[] ad505dafbd90
|
||||
conv2d_187.w_0_lab_labscale FLOAT[384,1,5,5] a221bd8406f2
|
||||
conv2d_188.w_0_lab_lab FLOAT[384,384,1,1] 9ea062b2f1b4
|
||||
conv2d_96.w_0 FLOAT[48,192,1,1] 6d73ce1fb738
|
||||
conv2d_97.w_0 FLOAT[192,48,1,1] 8098a00a81f0
|
||||
helper.constant.0 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.1 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.6 FLOAT[4] cf5451a623be
|
||||
helper.constant.8 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
learnable_affine_block_45.w_0 FLOAT[1] 65444e550b77
|
||||
learnable_affine_block_45.w_1 FLOAT[1] f2ee18a061af
|
||||
p2o.pd_op.conv2d.1.0_bias_lab_lab FLOAT[32] 3f4be24e33b8
|
||||
p2o.pd_op.conv2d.10.0_bias_lab_lab FLOAT[192] e32536500417
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[48] 961ec85108cb
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[192] c348751cbed0
|
||||
p2o.pd_op.conv2d.13.0_bias_lab FLOAT[384] 1b6d0aa0e977
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[96] 7876208c6fb1
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[384] 871907fff11d
|
||||
p2o.pd_op.conv2d.16.0_bias_lab FLOAT[384] fd15d67f1e85
|
||||
p2o.pd_op.conv2d.17.0_bias_lab_lab FLOAT[384] 097f0d068f05
|
||||
p2o.pd_op.conv2d.18.0_bias_lab_lab FLOAT[384] b8e228cae698
|
||||
p2o.pd_op.conv2d.2.0_bias_lab FLOAT[48] 8138a593f8f2
|
||||
p2o.pd_op.conv2d.3.0_bias_lab_lab FLOAT[48] 57128b896e31
|
||||
p2o.pd_op.conv2d.4.0_bias_lab FLOAT[96] d2230ff7a27e
|
||||
p2o.pd_op.conv2d.5.0_bias_lab_lab FLOAT[96] 05b9a5f236b6
|
||||
p2o.pd_op.conv2d.6.0_bias_lab FLOAT[192] a990b3fed4dd
|
||||
p2o.pd_op.conv2d.7.0_bias_lab_lab FLOAT[192] 74df3e4f22b6
|
||||
p2o.pd_op.conv2d.8.0_bias_lab_lab FLOAT[192] 9c072f4b4032
|
||||
p2o.pd_op.conv2d.9.0_bias_lab_lab FLOAT[192] 8f6e7021fe63
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias_lab FLOAT[16] 5b3de9e3f7c2
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias_lab FLOAT[32] bb4239a962eb
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias_lab FLOAT[192] 81ac3c08eae1
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias_lab FLOAT[384] 2236a6b52e38
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias_lab FLOAT[384] 14c22d416e3b
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias_lab FLOAT[384] 4eebd04fbeb4
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias_lab FLOAT[48] aaee6f6db9c1
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias_lab FLOAT[48] dcc78f972645
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias_lab FLOAT[96] dbd763cef105
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias_lab FLOAT[96] 5849d6801824
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias_lab FLOAT[192] 01e9219938aa
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias_lab FLOAT[192] e35d55fdac89
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias_lab FLOAT[192] fd7c6cc0a8fb
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias_lab FLOAT[192] aedc2ab77e2b
|
||||
p2o.pd_op.hardsigmoid.2.0_one FLOAT[] e00e5eb94441
|
||||
se_group0_down1 FLOAT[96,96,1,1] 4c8c888b01f2
|
||||
se_group0_down2 FLOAT[96] b99146f86442
|
||||
se_group0_sizes INT64[4] 4bb249469bee
|
||||
se_group0_up1 FLOAT[384,24,1,1] 1446892243f3
|
||||
se_group0_up2 FLOAT[384] 8538540d9317
|
||||
se_group1_down1 FLOAT[24,24,1,1] 01a670ee8021
|
||||
se_group1_down2 FLOAT[24] 7f8067be0db7
|
||||
se_group1_sizes INT64[4] 5c995dc6a0ef
|
||||
se_group1_up1 FLOAT[96,6,1,1] 3e47b305535b
|
||||
se_group1_up2 FLOAT[96] ed3a93d396c3
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,468 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,192,unk__22,unk__23] "Add.105"
|
||||
float[batch,192,unk__22,unk__23] "Add.111"
|
||||
float[batch,192,unk__42,unk__43] "Add.117"
|
||||
float[batch,48,1,1] "Add.119"
|
||||
float[batch,192,1,1] "Add.121"
|
||||
float[batch,384,unk__42,unk__43] "Add.125"
|
||||
float[batch,384,unk__42,unk__43] "Add.131"
|
||||
float[batch,384,unk__42,unk__43] "Add.133"
|
||||
float[batch,96,1,1] "Add.135"
|
||||
float[batch,384,1,1] "Add.137"
|
||||
float[batch,384,unk__42,unk__43] "Add.141"
|
||||
float[batch,384,unk__42,unk__43] "Add.147"
|
||||
float[batch,32,unk__6,unk__7] "Add.15"
|
||||
float[batch,384,unk__42,unk__43] "Add.153"
|
||||
float[batch,384,unk__42,unk__43] "Add.159"
|
||||
float[batch,384,unk__42,unk__43] "Add.165"
|
||||
float[batch,96,unk__42,unk__43] "Add.181"
|
||||
float[batch,96,unk__22,unk__23] "Add.187"
|
||||
float[batch,48,unk__6,unk__7] "Add.19"
|
||||
float[batch,96,unk__14,unk__15] "Add.193"
|
||||
float[batch,96,unk__6,unk__7] "Add.199"
|
||||
float[batch,96,unk__22,unk__23] "Add.201"
|
||||
float[batch,96,unk__14,unk__15] "Add.203"
|
||||
float[batch,96,unk__6,unk__7] "Add.205"
|
||||
float[batch,24,unk__42,unk__43] "Add.211"
|
||||
float[batch,24,unk__22,unk__23] "Add.217"
|
||||
float[batch,24,unk__14,unk__15] "Add.223"
|
||||
float[batch,24,unk__6,unk__7] "Add.229"
|
||||
float[batch,1,height,width] "Add.233"
|
||||
float[batch,48,unk__6,unk__7] "Add.25"
|
||||
float[batch,16,unk__0,unk__1] "Add.3"
|
||||
float[batch,48,unk__6,unk__7] "Add.31"
|
||||
float[batch,48,unk__14,unk__15] "Add.37"
|
||||
float[batch,96,unk__14,unk__15] "Add.41"
|
||||
float[batch,96,unk__14,unk__15] "Add.47"
|
||||
float[batch,96,unk__14,unk__15] "Add.53"
|
||||
float[batch,96,unk__22,unk__23] "Add.59"
|
||||
float[batch,192,unk__22,unk__23] "Add.63"
|
||||
float[batch,192,unk__22,unk__23] "Add.69"
|
||||
float[batch,192,unk__22,unk__23] "Add.75"
|
||||
float[batch,192,unk__22,unk__23] "Add.81"
|
||||
float[batch,192,unk__22,unk__23] "Add.87"
|
||||
float[batch,32,unk__0,unk__1] "Add.9"
|
||||
float[batch,192,unk__22,unk__23] "Add.93"
|
||||
float[batch,192,unk__22,unk__23] "Add.99"
|
||||
float[batch,96,unk__6,unk__7] "Concat.1"
|
||||
float[batch,192,unk__42,unk__43] "Mul.77"
|
||||
float[batch,384,unk__42,unk__43] "Mul.85"
|
||||
float[batch,384,unk__42,unk__43] "Mul.87"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,96,unk__42,unk__43] "p2o.pd_op.conv2d.23.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.conv2d.26.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.conv2d.29.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.conv2d.32.0"
|
||||
float[batch,24,unk__42,unk__43] "p2o.pd_op.conv2d.35.0"
|
||||
float[batch,24,unk__22,unk__23] "p2o.pd_op.conv2d.38.0"
|
||||
float[batch,24,unk__14,unk__15] "p2o.pd_op.conv2d.41.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.conv2d.44.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.hardswish.0.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.hardswish.1.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.10.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.11.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.12.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.13.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.14.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.15.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.16.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.17.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.18.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.19.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.2.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.20.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.21.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.22.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.23.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.3.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.4.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.5.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.6.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.7.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.8.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.9.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.pool2d.1.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.2.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.3.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.4.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.5.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.6.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.7.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.8.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.9.0"
|
||||
float[batch,48,1,1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.relu.10.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.relu.11.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.2.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.3.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.4.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.5.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.6.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.7.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.8.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.9.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,96,1,1] se_group0_down
|
||||
float[batch,384,1,1] se_group0_gates
|
||||
float[batch,384,1,1] se_group0_pooled
|
||||
float[batch,96,1,1] se_group0_relu
|
||||
float[batch,384,1,1] se_group0_up
|
||||
float[batch,24,1,1] se_group1_down
|
||||
float[batch,96,1,1] se_group1_gates
|
||||
float[batch,96,1,1] se_group1_pooled
|
||||
float[batch,24,1,1] se_group1_relu
|
||||
float[batch,96,1,1] se_group1_up
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,16,unk__0,unk__1] val_0
|
||||
float[batch,32,unk__0,unk__1] val_1
|
||||
float[batch,96,unk__14,unk__15] val_10
|
||||
float[batch,96,unk__14,unk__15] val_11
|
||||
float[batch,96,unk__14,unk__15] val_12
|
||||
float[batch,192,unk__22,unk__23] val_13
|
||||
float[batch,192,unk__22,unk__23] val_14
|
||||
float[batch,192,unk__22,unk__23] val_15
|
||||
float[batch,192,unk__22,unk__23] val_16
|
||||
float[batch,192,unk__22,unk__23] val_17
|
||||
float[batch,192,unk__22,unk__23] val_18
|
||||
float[batch,192,unk__22,unk__23] val_19
|
||||
float[batch,32,unk__0,unk__1] val_2
|
||||
float[batch,192,unk__22,unk__23] val_20
|
||||
float[batch,192,unk__22,unk__23] val_21
|
||||
float[batch,192,unk__22,unk__23] val_22
|
||||
float[batch,192,unk__22,unk__23] val_23
|
||||
float[batch,192,unk__22,unk__23] val_24
|
||||
float[batch,192,unk__22,unk__23] val_25
|
||||
float[batch,192,unk__22,unk__23] val_26
|
||||
float[batch,384,unk__42,unk__43] val_27
|
||||
float[batch,384,unk__42,unk__43] val_28
|
||||
float[batch,384,unk__42,unk__43] val_29
|
||||
float[batch,48,unk__6,unk__7] val_3
|
||||
float[batch,384,unk__42,unk__43] val_30
|
||||
float[batch,384,unk__42,unk__43] val_31
|
||||
float[batch,384,unk__42,unk__43] val_32
|
||||
float[batch,384,unk__42,unk__43] val_33
|
||||
float[batch,384,unk__42,unk__43] val_34
|
||||
float[batch,384,unk__42,unk__43] val_35
|
||||
float[batch,384,unk__42,unk__43] val_36
|
||||
float[batch,96,1,1] val_37
|
||||
float[batch,96,1,1] val_38
|
||||
float[batch,96,1,1] val_39
|
||||
float[batch,48,unk__6,unk__7] val_4
|
||||
float[batch,96,1,1] val_40
|
||||
float[batch,24,1,1] val_41
|
||||
float[batch,24,1,1] val_42
|
||||
float[batch,24,1,1] val_43
|
||||
float[batch,24,1,1] val_44
|
||||
float[batch,48,unk__6,unk__7] val_5
|
||||
float[batch,48,unk__6,unk__7] val_6
|
||||
float[batch,48,unk__6,unk__7] val_7
|
||||
float[batch,96,unk__14,unk__15] val_8
|
||||
float[batch,96,unk__14,unk__15] val_9
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_0.w_0", "conv2d_0.w_0_bias")
|
||||
"Add.3" = Conv <dilations: ints = [1, 1], group: int = 16, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.0.0", "conv2d_161.w_0_lab", "p2o.pd_op.depthwise_conv2d.0.0_bias_lab")
|
||||
val_0 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.3")
|
||||
"p2o.pd_op.hardswish.0.0" = Mul ("Add.3", val_0)
|
||||
"Add.9" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.0.0", "conv2d_162.w_0_lab_lab", "p2o.pd_op.conv2d.1.0_bias_lab_lab")
|
||||
val_1 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.9")
|
||||
"p2o.pd_op.hardswish.1.0" = Mul ("Add.9", val_1)
|
||||
val_2 = Add ("p2o.pd_op.hardswish.1.0", "conv2d_163.w_0_lab_laboffset")
|
||||
"Add.15" = Conv <dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_2, "conv2d_163.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.1.0_bias_lab")
|
||||
"Add.19" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.15", "conv2d_164.w_0_lab", "p2o.pd_op.conv2d.2.0_bias_lab")
|
||||
val_3 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.19")
|
||||
"p2o.pd_op.hardswish.2.0" = Mul ("Add.19", val_3)
|
||||
val_4 = Add ("p2o.pd_op.hardswish.2.0", "conv2d_165.w_0_lab_laboffset")
|
||||
"Add.25" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_4, "conv2d_165.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.2.0_bias_lab")
|
||||
val_5 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.25")
|
||||
"p2o.pd_op.hardswish.3.0" = Mul ("Add.25", val_5)
|
||||
"Add.31" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.3.0", "conv2d_166.w_0_lab_lab", "p2o.pd_op.conv2d.3.0_bias_lab_lab")
|
||||
val_6 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.31")
|
||||
"p2o.pd_op.hardswish.4.0" = Mul ("Add.31", val_6)
|
||||
val_7 = Add ("p2o.pd_op.hardswish.4.0", "conv2d_167.w_0_lab_laboffset")
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_7, "conv2d_167.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.3.0_bias_lab")
|
||||
"Add.41" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.37", "conv2d_168.w_0_lab", "p2o.pd_op.conv2d.4.0_bias_lab")
|
||||
val_8 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.41")
|
||||
"p2o.pd_op.hardswish.5.0" = Mul ("Add.41", val_8)
|
||||
val_9 = Add ("p2o.pd_op.hardswish.5.0", "conv2d_169.w_0_lab_laboffset")
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_9, "conv2d_169.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.4.0_bias_lab")
|
||||
val_10 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.47")
|
||||
"p2o.pd_op.hardswish.6.0" = Mul ("Add.47", val_10)
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.6.0", "conv2d_170.w_0_lab_lab", "p2o.pd_op.conv2d.5.0_bias_lab_lab")
|
||||
val_11 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.53")
|
||||
"p2o.pd_op.hardswish.7.0" = Mul ("Add.53", val_11)
|
||||
val_12 = Add ("p2o.pd_op.hardswish.7.0", "conv2d_171.w_0_lab_laboffset")
|
||||
"Add.59" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_12, "conv2d_171.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.5.0_bias_lab")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.59", "conv2d_172.w_0_lab", "p2o.pd_op.conv2d.6.0_bias_lab")
|
||||
val_13 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.63")
|
||||
"p2o.pd_op.hardswish.8.0" = Mul ("Add.63", val_13)
|
||||
val_14 = Add ("p2o.pd_op.hardswish.8.0", "conv2d_173.w_0_lab_laboffset")
|
||||
"Add.69" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_14, "conv2d_173.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.6.0_bias_lab")
|
||||
val_15 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.69")
|
||||
"p2o.pd_op.hardswish.9.0" = Mul ("Add.69", val_15)
|
||||
"Add.75" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.9.0", "conv2d_174.w_0_lab_lab", "p2o.pd_op.conv2d.7.0_bias_lab_lab")
|
||||
val_16 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.75")
|
||||
"p2o.pd_op.hardswish.10.0" = Mul ("Add.75", val_16)
|
||||
val_17 = Add ("p2o.pd_op.hardswish.10.0", "conv2d_175.w_0_lab_laboffset")
|
||||
"Add.81" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_17, "conv2d_175.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.7.0_bias_lab")
|
||||
val_18 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.81")
|
||||
"p2o.pd_op.hardswish.11.0" = Mul ("Add.81", val_18)
|
||||
"Add.87" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.11.0", "conv2d_176.w_0_lab_lab", "p2o.pd_op.conv2d.8.0_bias_lab_lab")
|
||||
val_19 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.87")
|
||||
"p2o.pd_op.hardswish.12.0" = Mul ("Add.87", val_19)
|
||||
val_20 = Add ("p2o.pd_op.hardswish.12.0", "conv2d_177.w_0_lab_laboffset")
|
||||
"Add.93" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_20, "conv2d_177.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.8.0_bias_lab")
|
||||
val_21 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.93")
|
||||
"p2o.pd_op.hardswish.13.0" = Mul ("Add.93", val_21)
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.13.0", "conv2d_178.w_0_lab_lab", "p2o.pd_op.conv2d.9.0_bias_lab_lab")
|
||||
val_22 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.99")
|
||||
"p2o.pd_op.hardswish.14.0" = Mul ("Add.99", val_22)
|
||||
val_23 = Add ("p2o.pd_op.hardswish.14.0", "conv2d_179.w_0_lab_laboffset")
|
||||
"Add.105" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_23, "conv2d_179.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.9.0_bias_lab")
|
||||
val_24 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.105")
|
||||
"p2o.pd_op.hardswish.15.0" = Mul ("Add.105", val_24)
|
||||
"Add.111" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.15.0", "conv2d_180.w_0_lab_lab", "p2o.pd_op.conv2d.10.0_bias_lab_lab")
|
||||
val_25 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.111")
|
||||
"p2o.pd_op.hardswish.16.0" = Mul ("Add.111", val_25)
|
||||
val_26 = Add ("p2o.pd_op.hardswish.16.0", "conv2d_181.w_0_lab_laboffset")
|
||||
"Add.117" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [2, 2]> (val_26, "conv2d_181.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.10.0_bias_lab")
|
||||
["GlobalAveragePool.0"] "p2o.pd_op.pool2d.0.0" = GlobalAveragePool ("Add.117")
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.0.0", "conv2d_96.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.119")
|
||||
"Add.121" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_97.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.121")
|
||||
["Mul.76"] "Mul.77" = Mul ("Add.117", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.77", "conv2d_182.w_0_lab", "p2o.pd_op.conv2d.13.0_bias_lab")
|
||||
val_27 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.125")
|
||||
"p2o.pd_op.hardswish.17.0" = Mul ("Add.125", val_27)
|
||||
val_28 = Add ("p2o.pd_op.hardswish.17.0", "conv2d_183.w_0_lab_laboffset")
|
||||
"Add.131" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_28, "conv2d_183.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.11.0_bias_lab")
|
||||
val_29 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.131")
|
||||
"p2o.pd_op.hardswish.18.0" = Mul ("Add.131", val_29)
|
||||
["Mul.84"] "Mul.85" = Mul ("learnable_affine_block_45.w_0", "p2o.pd_op.hardswish.18.0")
|
||||
["Add.132"] "Add.133" = Add ("Mul.85", "learnable_affine_block_45.w_1")
|
||||
["GlobalAveragePool.1"] "p2o.pd_op.pool2d.1.0" = GlobalAveragePool ("Add.133")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.1.0", "conv2d_107.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.135")
|
||||
"Add.137" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_108.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.137")
|
||||
["Mul.86"] "Mul.87" = Mul ("Add.133", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.141" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.87", "conv2d_184.w_0_lab", "p2o.pd_op.conv2d.16.0_bias_lab")
|
||||
val_30 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.141")
|
||||
"p2o.pd_op.hardswish.19.0" = Mul ("Add.141", val_30)
|
||||
val_31 = Add ("p2o.pd_op.hardswish.19.0", "conv2d_185.w_0_lab_laboffset")
|
||||
"Add.147" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_31, "conv2d_185.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.12.0_bias_lab")
|
||||
val_32 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.147")
|
||||
"p2o.pd_op.hardswish.20.0" = Mul ("Add.147", val_32)
|
||||
"Add.153" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.20.0", "conv2d_186.w_0_lab_lab", "p2o.pd_op.conv2d.17.0_bias_lab_lab")
|
||||
val_33 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.153")
|
||||
"p2o.pd_op.hardswish.21.0" = Mul ("Add.153", val_33)
|
||||
val_34 = Add ("p2o.pd_op.hardswish.21.0", "conv2d_187.w_0_lab_laboffset")
|
||||
"Add.159" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_34, "conv2d_187.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.13.0_bias_lab")
|
||||
val_35 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.159")
|
||||
"p2o.pd_op.hardswish.22.0" = Mul ("Add.159", val_35)
|
||||
"Add.165" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.22.0", "conv2d_188.w_0_lab_lab", "p2o.pd_op.conv2d.18.0_bias_lab_lab")
|
||||
val_36 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.165")
|
||||
"p2o.pd_op.hardswish.23.0" = Mul ("Add.165", val_36)
|
||||
"p2o.pd_op.conv2d.23.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.23.0", "Conv.37_folded_w_lab", "Conv.37_folded_b_lab")
|
||||
["GlobalAveragePool.2"] "p2o.pd_op.pool2d.2.0" = GlobalAveragePool ("p2o.pd_op.conv2d.23.0")
|
||||
"p2o.pd_op.conv2d.26.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_26, "Conv.40_folded_w_labscale", "Conv.40_folded_b")
|
||||
["GlobalAveragePool.3"] "p2o.pd_op.pool2d.3.0" = GlobalAveragePool ("p2o.pd_op.conv2d.26.0")
|
||||
"p2o.pd_op.conv2d.29.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_12, "Conv.43_folded_w_labscale", "Conv.43_folded_b")
|
||||
["GlobalAveragePool.4"] "p2o.pd_op.pool2d.4.0" = GlobalAveragePool ("p2o.pd_op.conv2d.29.0")
|
||||
"p2o.pd_op.conv2d.32.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_7, "Conv.46_folded_w_labscale", "Conv.46_folded_b")
|
||||
["GlobalAveragePool.5"] "p2o.pd_op.pool2d.5.0" = GlobalAveragePool ("p2o.pd_op.conv2d.32.0")
|
||||
se_group0_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.2.0", "p2o.pd_op.pool2d.3.0", "p2o.pd_op.pool2d.4.0", "p2o.pd_op.pool2d.5.0")
|
||||
se_group0_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_pooled, se_group0_down1, se_group0_down2)
|
||||
se_group0_relu = Relu (se_group0_down)
|
||||
se_group0_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_relu, se_group0_up1, se_group0_up2)
|
||||
se_group0_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group0_up)
|
||||
"se_group0_p2o.pd_op.hardsigmoid.2.0", "se_group0_p2o.pd_op.hardsigmoid.3.0", "se_group0_p2o.pd_op.hardsigmoid.4.0", "se_group0_p2o.pd_op.hardsigmoid.5.0" = Split <axis: int = 1> (se_group0_gates, se_group0_sizes)
|
||||
val_37 = Add ("se_group0_p2o.pd_op.hardsigmoid.2.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.181" = Mul ("p2o.pd_op.conv2d.23.0", val_37)
|
||||
val_38 = Add ("se_group0_p2o.pd_op.hardsigmoid.3.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.187" = Mul ("p2o.pd_op.conv2d.26.0", val_38)
|
||||
val_39 = Add ("se_group0_p2o.pd_op.hardsigmoid.4.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.193" = Mul ("p2o.pd_op.conv2d.29.0", val_39)
|
||||
val_40 = Add ("se_group0_p2o.pd_op.hardsigmoid.5.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.199" = Mul ("p2o.pd_op.conv2d.32.0", val_40)
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.181", "helper.constant.1", "helper.constant.0")
|
||||
["Add.200"] "Add.201" = Add ("Add.187", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.201", "helper.constant.1", "helper.constant.0")
|
||||
["Add.202"] "Add.203" = Add ("Add.193", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.203", "helper.constant.1", "helper.constant.0")
|
||||
["Add.204"] "Add.205" = Add ("Add.199", "p2o.pd_op.nearest_interp.2.0")
|
||||
["Conv.49"] "p2o.pd_op.conv2d.35.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.181", "conv2d_156.w_0")
|
||||
["GlobalAveragePool.6"] "p2o.pd_op.pool2d.6.0" = GlobalAveragePool ("p2o.pd_op.conv2d.35.0")
|
||||
["Conv.52"] "p2o.pd_op.conv2d.38.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.201", "conv2d_150.w_0")
|
||||
["GlobalAveragePool.7"] "p2o.pd_op.pool2d.7.0" = GlobalAveragePool ("p2o.pd_op.conv2d.38.0")
|
||||
["Conv.55"] "p2o.pd_op.conv2d.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.203", "conv2d_144.w_0")
|
||||
["GlobalAveragePool.8"] "p2o.pd_op.pool2d.8.0" = GlobalAveragePool ("p2o.pd_op.conv2d.41.0")
|
||||
["Conv.58"] "p2o.pd_op.conv2d.44.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.205", "conv2d_138.w_0")
|
||||
["GlobalAveragePool.9"] "p2o.pd_op.pool2d.9.0" = GlobalAveragePool ("p2o.pd_op.conv2d.44.0")
|
||||
se_group1_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.6.0", "p2o.pd_op.pool2d.7.0", "p2o.pd_op.pool2d.8.0", "p2o.pd_op.pool2d.9.0")
|
||||
se_group1_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_pooled, se_group1_down1, se_group1_down2)
|
||||
se_group1_relu = Relu (se_group1_down)
|
||||
se_group1_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_relu, se_group1_up1, se_group1_up2)
|
||||
se_group1_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group1_up)
|
||||
"se_group1_p2o.pd_op.hardsigmoid.6.0", "se_group1_p2o.pd_op.hardsigmoid.7.0", "se_group1_p2o.pd_op.hardsigmoid.8.0", "se_group1_p2o.pd_op.hardsigmoid.9.0" = Split <axis: int = 1> (se_group1_gates, se_group1_sizes)
|
||||
val_41 = Add ("se_group1_p2o.pd_op.hardsigmoid.6.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.211" = Mul ("p2o.pd_op.conv2d.35.0", val_41)
|
||||
val_42 = Add ("se_group1_p2o.pd_op.hardsigmoid.7.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.217" = Mul ("p2o.pd_op.conv2d.38.0", val_42)
|
||||
val_43 = Add ("se_group1_p2o.pd_op.hardsigmoid.8.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.223" = Mul ("p2o.pd_op.conv2d.41.0", val_43)
|
||||
val_44 = Add ("se_group1_p2o.pd_op.hardsigmoid.9.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.229" = Mul ("p2o.pd_op.conv2d.44.0", val_44)
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.211", "helper.constant.1", "helper.constant.6")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.217", "helper.constant.1", "helper.constant.8")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.223", "helper.constant.1", "helper.constant.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.229")
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.1", "conv2d_159.w_0", "conv2d_159.w_0_bias")
|
||||
["Relu.10"] "p2o.pd_op.relu.10.0" = Relu ("p2o.pd_op.batch_norm_.1.0")
|
||||
"p2o.pd_op.batch_norm_.2.0" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.10.0", "auto.cast.57", "ConvTranspose.1_bias")
|
||||
["Relu.11"] "p2o.pd_op.relu.11.0" = Relu ("p2o.pd_op.batch_norm_.2.0")
|
||||
"Add.233" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.11.0", "auto.cast.60", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] fetch_name_0 = Sigmoid ("Add.233")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
Conv.37_folded_b_lab FLOAT[96] 0d571951a1e0
|
||||
Conv.37_folded_w_lab FLOAT[96,384,1,1] 1d0305563ea7
|
||||
Conv.40_folded_b FLOAT[96] dcfdd514912d
|
||||
Conv.40_folded_w_labscale FLOAT[96,192,1,1] bacc8274202e
|
||||
Conv.43_folded_b FLOAT[96] ee902cf71aad
|
||||
Conv.43_folded_w_labscale FLOAT[96,96,1,1] b17e08485dc5
|
||||
Conv.46_folded_b FLOAT[96] 6541e510a35d
|
||||
Conv.46_folded_w_labscale FLOAT[96,48,1,1] 9423b2c0951a
|
||||
ConvTranspose.1_bias FLOAT[24] 64cabf62980d
|
||||
ConvTranspose.3_bias FLOAT[1] 55c86fee1edb
|
||||
auto.cast.57 FLOAT[24,24,2,2] 1dc864bec64f
|
||||
auto.cast.60 FLOAT[24,1,2,2] c9862b3a19bc
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_0.w_0 FLOAT[16,3,3,3] 7841f2f3efae
|
||||
conv2d_0.w_0_bias FLOAT[16] 2713bf453fd1
|
||||
conv2d_107.w_0 FLOAT[96,384,1,1] 2fc401aa1ec6
|
||||
conv2d_108.w_0 FLOAT[384,96,1,1] f2a9a9261c07
|
||||
conv2d_138.w_0 FLOAT[24,96,3,3] 47aa8ba1db50
|
||||
conv2d_144.w_0 FLOAT[24,96,3,3] cd85b03c436c
|
||||
conv2d_150.w_0 FLOAT[24,96,3,3] 591f14004ce0
|
||||
conv2d_156.w_0 FLOAT[24,96,3,3] 5e0bc4bf821e
|
||||
conv2d_159.w_0 FLOAT[24,96,3,3] 43b6b1b17bef
|
||||
conv2d_159.w_0_bias FLOAT[24] c98267f8273d
|
||||
conv2d_161.w_0_lab FLOAT[16,1,3,3] 22528d709d37
|
||||
conv2d_162.w_0_lab_lab FLOAT[32,16,1,1] 051645505e21
|
||||
conv2d_163.w_0_lab_laboffset FLOAT[] 92a142f7dc41
|
||||
conv2d_163.w_0_lab_labscale FLOAT[32,1,3,3] 8694842bd3fb
|
||||
conv2d_164.w_0_lab FLOAT[48,32,1,1] 0c937f040d0e
|
||||
conv2d_165.w_0_lab_laboffset FLOAT[] 012179917694
|
||||
conv2d_165.w_0_lab_labscale FLOAT[48,1,3,3] 7d779e5616fa
|
||||
conv2d_166.w_0_lab_lab FLOAT[48,48,1,1] d70c86b2d1ec
|
||||
conv2d_167.w_0_lab_laboffset FLOAT[] 9741b37d98e3
|
||||
conv2d_167.w_0_lab_labscale FLOAT[48,1,3,3] fa2e1db2eb62
|
||||
conv2d_168.w_0_lab FLOAT[96,48,1,1] 81e13e0bd382
|
||||
conv2d_169.w_0_lab_laboffset FLOAT[] f3e015d53e9a
|
||||
conv2d_169.w_0_lab_labscale FLOAT[96,1,3,3] 75bbb69deb68
|
||||
conv2d_170.w_0_lab_lab FLOAT[96,96,1,1] 59b22a69e345
|
||||
conv2d_171.w_0_lab_laboffset FLOAT[] f42328163f40
|
||||
conv2d_171.w_0_lab_labscale FLOAT[96,1,3,3] 65cbca6287a2
|
||||
conv2d_172.w_0_lab FLOAT[192,96,1,1] ff93ca701d2f
|
||||
conv2d_173.w_0_lab_laboffset FLOAT[] b76450d3656f
|
||||
conv2d_173.w_0_lab_labscale FLOAT[192,1,5,5] 28d7de00679c
|
||||
conv2d_174.w_0_lab_lab FLOAT[192,192,1,1] 53cf6f343ec2
|
||||
conv2d_175.w_0_lab_laboffset FLOAT[] e665434a5d2d
|
||||
conv2d_175.w_0_lab_labscale FLOAT[192,1,5,5] 3c0aa815839d
|
||||
conv2d_176.w_0_lab_lab FLOAT[192,192,1,1] cb45f031f07b
|
||||
conv2d_177.w_0_lab_laboffset FLOAT[] e095ffc76247
|
||||
conv2d_177.w_0_lab_labscale FLOAT[192,1,5,5] 22fe03b75591
|
||||
conv2d_178.w_0_lab_lab FLOAT[192,192,1,1] c259022f5c3d
|
||||
conv2d_179.w_0_lab_laboffset FLOAT[] 5842420f0e64
|
||||
conv2d_179.w_0_lab_labscale FLOAT[192,1,5,5] 408bbab0d507
|
||||
conv2d_180.w_0_lab_lab FLOAT[192,192,1,1] 85871ea30bf1
|
||||
conv2d_181.w_0_lab_laboffset FLOAT[] 9e0407355f14
|
||||
conv2d_181.w_0_lab_labscale FLOAT[192,1,5,5] 75764b0f5265
|
||||
conv2d_182.w_0_lab FLOAT[384,192,1,1] 81235d1a972f
|
||||
conv2d_183.w_0_lab_laboffset FLOAT[] e648d792317a
|
||||
conv2d_183.w_0_lab_labscale FLOAT[384,1,5,5] f5341adaad28
|
||||
conv2d_184.w_0_lab FLOAT[384,384,1,1] c37a7cec640b
|
||||
conv2d_185.w_0_lab_laboffset FLOAT[] 768fa13da14b
|
||||
conv2d_185.w_0_lab_labscale FLOAT[384,1,5,5] 6bacb713155c
|
||||
conv2d_186.w_0_lab_lab FLOAT[384,384,1,1] 2fa80ae1b18f
|
||||
conv2d_187.w_0_lab_laboffset FLOAT[] ad505dafbd90
|
||||
conv2d_187.w_0_lab_labscale FLOAT[384,1,5,5] a221bd8406f2
|
||||
conv2d_188.w_0_lab_lab FLOAT[384,384,1,1] 9ea062b2f1b4
|
||||
conv2d_96.w_0 FLOAT[48,192,1,1] 6d73ce1fb738
|
||||
conv2d_97.w_0 FLOAT[192,48,1,1] 8098a00a81f0
|
||||
helper.constant.0 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.1 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.6 FLOAT[4] cf5451a623be
|
||||
helper.constant.8 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
learnable_affine_block_45.w_0 FLOAT[1] 65444e550b77
|
||||
learnable_affine_block_45.w_1 FLOAT[1] f2ee18a061af
|
||||
p2o.pd_op.conv2d.1.0_bias_lab_lab FLOAT[32] 3f4be24e33b8
|
||||
p2o.pd_op.conv2d.10.0_bias_lab_lab FLOAT[192] e32536500417
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[48] 961ec85108cb
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[192] c348751cbed0
|
||||
p2o.pd_op.conv2d.13.0_bias_lab FLOAT[384] 1b6d0aa0e977
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[96] 7876208c6fb1
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[384] 871907fff11d
|
||||
p2o.pd_op.conv2d.16.0_bias_lab FLOAT[384] fd15d67f1e85
|
||||
p2o.pd_op.conv2d.17.0_bias_lab_lab FLOAT[384] 097f0d068f05
|
||||
p2o.pd_op.conv2d.18.0_bias_lab_lab FLOAT[384] b8e228cae698
|
||||
p2o.pd_op.conv2d.2.0_bias_lab FLOAT[48] 8138a593f8f2
|
||||
p2o.pd_op.conv2d.3.0_bias_lab_lab FLOAT[48] 57128b896e31
|
||||
p2o.pd_op.conv2d.4.0_bias_lab FLOAT[96] d2230ff7a27e
|
||||
p2o.pd_op.conv2d.5.0_bias_lab_lab FLOAT[96] 05b9a5f236b6
|
||||
p2o.pd_op.conv2d.6.0_bias_lab FLOAT[192] a990b3fed4dd
|
||||
p2o.pd_op.conv2d.7.0_bias_lab_lab FLOAT[192] 74df3e4f22b6
|
||||
p2o.pd_op.conv2d.8.0_bias_lab_lab FLOAT[192] 9c072f4b4032
|
||||
p2o.pd_op.conv2d.9.0_bias_lab_lab FLOAT[192] 8f6e7021fe63
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias_lab FLOAT[16] 5b3de9e3f7c2
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias_lab FLOAT[32] bb4239a962eb
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias_lab FLOAT[192] 81ac3c08eae1
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias_lab FLOAT[384] 2236a6b52e38
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias_lab FLOAT[384] 14c22d416e3b
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias_lab FLOAT[384] 4eebd04fbeb4
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias_lab FLOAT[48] aaee6f6db9c1
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias_lab FLOAT[48] dcc78f972645
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias_lab FLOAT[96] dbd763cef105
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias_lab FLOAT[96] 5849d6801824
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias_lab FLOAT[192] 01e9219938aa
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias_lab FLOAT[192] e35d55fdac89
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias_lab FLOAT[192] fd7c6cc0a8fb
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias_lab FLOAT[192] aedc2ab77e2b
|
||||
p2o.pd_op.hardsigmoid.2.0_one FLOAT[] e00e5eb94441
|
||||
se_group0_down1 FLOAT[96,96,1,1] 4c8c888b01f2
|
||||
se_group0_down2 FLOAT[96] b99146f86442
|
||||
se_group0_sizes INT64[4] 4bb249469bee
|
||||
se_group0_up1 FLOAT[384,24,1,1] 1446892243f3
|
||||
se_group0_up2 FLOAT[384] 8538540d9317
|
||||
se_group1_down1 FLOAT[24,24,1,1] 01a670ee8021
|
||||
se_group1_down2 FLOAT[24] 7f8067be0db7
|
||||
se_group1_sizes INT64[4] 5c995dc6a0ef
|
||||
se_group1_up1 FLOAT[96,6,1,1] 3e47b305535b
|
||||
se_group1_up2 FLOAT[96] ed3a93d396c3
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,468 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,192,unk__22,unk__23] "Add.105"
|
||||
float[batch,192,unk__22,unk__23] "Add.111"
|
||||
float[batch,192,unk__42,unk__43] "Add.117"
|
||||
float[batch,48,1,1] "Add.119"
|
||||
float[batch,192,1,1] "Add.121"
|
||||
float[batch,384,unk__42,unk__43] "Add.125"
|
||||
float[batch,384,unk__42,unk__43] "Add.131"
|
||||
float[batch,384,unk__42,unk__43] "Add.133"
|
||||
float[batch,96,1,1] "Add.135"
|
||||
float[batch,384,1,1] "Add.137"
|
||||
float[batch,384,unk__42,unk__43] "Add.141"
|
||||
float[batch,384,unk__42,unk__43] "Add.147"
|
||||
float[batch,32,unk__6,unk__7] "Add.15"
|
||||
float[batch,384,unk__42,unk__43] "Add.153"
|
||||
float[batch,384,unk__42,unk__43] "Add.159"
|
||||
float[batch,384,unk__42,unk__43] "Add.165"
|
||||
float[batch,96,unk__42,unk__43] "Add.181"
|
||||
float[batch,96,unk__22,unk__23] "Add.187"
|
||||
float[batch,48,unk__6,unk__7] "Add.19"
|
||||
float[batch,96,unk__14,unk__15] "Add.193"
|
||||
float[batch,96,unk__6,unk__7] "Add.199"
|
||||
float[batch,96,unk__22,unk__23] "Add.201"
|
||||
float[batch,96,unk__14,unk__15] "Add.203"
|
||||
float[batch,96,unk__6,unk__7] "Add.205"
|
||||
float[batch,24,unk__42,unk__43] "Add.211"
|
||||
float[batch,24,unk__22,unk__23] "Add.217"
|
||||
float[batch,24,unk__14,unk__15] "Add.223"
|
||||
float[batch,24,unk__6,unk__7] "Add.229"
|
||||
float[batch,1,height,width] "Add.233"
|
||||
float[batch,48,unk__6,unk__7] "Add.25"
|
||||
float[batch,16,unk__0,unk__1] "Add.3"
|
||||
float[batch,48,unk__6,unk__7] "Add.31"
|
||||
float[batch,48,unk__14,unk__15] "Add.37"
|
||||
float[batch,96,unk__14,unk__15] "Add.41"
|
||||
float[batch,96,unk__14,unk__15] "Add.47"
|
||||
float[batch,96,unk__14,unk__15] "Add.53"
|
||||
float[batch,96,unk__22,unk__23] "Add.59"
|
||||
float[batch,192,unk__22,unk__23] "Add.63"
|
||||
float[batch,192,unk__22,unk__23] "Add.69"
|
||||
float[batch,192,unk__22,unk__23] "Add.75"
|
||||
float[batch,192,unk__22,unk__23] "Add.81"
|
||||
float[batch,192,unk__22,unk__23] "Add.87"
|
||||
float[batch,32,unk__0,unk__1] "Add.9"
|
||||
float[batch,192,unk__22,unk__23] "Add.93"
|
||||
float[batch,192,unk__22,unk__23] "Add.99"
|
||||
float[batch,96,unk__6,unk__7] "Concat.1"
|
||||
float[batch,192,unk__42,unk__43] "Mul.77"
|
||||
float[batch,384,unk__42,unk__43] "Mul.85"
|
||||
float[batch,384,unk__42,unk__43] "Mul.87"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,96,unk__42,unk__43] "p2o.pd_op.conv2d.23.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.conv2d.26.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.conv2d.29.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.conv2d.32.0"
|
||||
float[batch,24,unk__42,unk__43] "p2o.pd_op.conv2d.35.0"
|
||||
float[batch,24,unk__22,unk__23] "p2o.pd_op.conv2d.38.0"
|
||||
float[batch,24,unk__14,unk__15] "p2o.pd_op.conv2d.41.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.conv2d.44.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.hardswish.0.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.hardswish.1.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.10.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.11.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.12.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.13.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.14.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.15.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.16.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.17.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.18.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.19.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.2.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.20.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.21.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.22.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.23.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.3.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.4.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.5.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.6.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.7.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.8.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.9.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.pool2d.1.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.2.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.3.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.4.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.5.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.6.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.7.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.8.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.9.0"
|
||||
float[batch,48,1,1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.relu.10.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.relu.11.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.2.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.3.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.4.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.5.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.6.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.7.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.8.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.9.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,96,1,1] se_group0_down
|
||||
float[batch,384,1,1] se_group0_gates
|
||||
float[batch,384,1,1] se_group0_pooled
|
||||
float[batch,96,1,1] se_group0_relu
|
||||
float[batch,384,1,1] se_group0_up
|
||||
float[batch,24,1,1] se_group1_down
|
||||
float[batch,96,1,1] se_group1_gates
|
||||
float[batch,96,1,1] se_group1_pooled
|
||||
float[batch,24,1,1] se_group1_relu
|
||||
float[batch,96,1,1] se_group1_up
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,16,unk__0,unk__1] val_0
|
||||
float[batch,32,unk__0,unk__1] val_1
|
||||
float[batch,96,unk__14,unk__15] val_10
|
||||
float[batch,96,unk__14,unk__15] val_11
|
||||
float[batch,96,unk__14,unk__15] val_12
|
||||
float[batch,192,unk__22,unk__23] val_13
|
||||
float[batch,192,unk__22,unk__23] val_14
|
||||
float[batch,192,unk__22,unk__23] val_15
|
||||
float[batch,192,unk__22,unk__23] val_16
|
||||
float[batch,192,unk__22,unk__23] val_17
|
||||
float[batch,192,unk__22,unk__23] val_18
|
||||
float[batch,192,unk__22,unk__23] val_19
|
||||
float[batch,32,unk__0,unk__1] val_2
|
||||
float[batch,192,unk__22,unk__23] val_20
|
||||
float[batch,192,unk__22,unk__23] val_21
|
||||
float[batch,192,unk__22,unk__23] val_22
|
||||
float[batch,192,unk__22,unk__23] val_23
|
||||
float[batch,192,unk__22,unk__23] val_24
|
||||
float[batch,192,unk__22,unk__23] val_25
|
||||
float[batch,192,unk__22,unk__23] val_26
|
||||
float[batch,384,unk__42,unk__43] val_27
|
||||
float[batch,384,unk__42,unk__43] val_28
|
||||
float[batch,384,unk__42,unk__43] val_29
|
||||
float[batch,48,unk__6,unk__7] val_3
|
||||
float[batch,384,unk__42,unk__43] val_30
|
||||
float[batch,384,unk__42,unk__43] val_31
|
||||
float[batch,384,unk__42,unk__43] val_32
|
||||
float[batch,384,unk__42,unk__43] val_33
|
||||
float[batch,384,unk__42,unk__43] val_34
|
||||
float[batch,384,unk__42,unk__43] val_35
|
||||
float[batch,384,unk__42,unk__43] val_36
|
||||
float[batch,96,1,1] val_37
|
||||
float[batch,96,1,1] val_38
|
||||
float[batch,96,1,1] val_39
|
||||
float[batch,48,unk__6,unk__7] val_4
|
||||
float[batch,96,1,1] val_40
|
||||
float[batch,24,1,1] val_41
|
||||
float[batch,24,1,1] val_42
|
||||
float[batch,24,1,1] val_43
|
||||
float[batch,24,1,1] val_44
|
||||
float[batch,48,unk__6,unk__7] val_5
|
||||
float[batch,48,unk__6,unk__7] val_6
|
||||
float[batch,48,unk__6,unk__7] val_7
|
||||
float[batch,96,unk__14,unk__15] val_8
|
||||
float[batch,96,unk__14,unk__15] val_9
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_0.w_0", "conv2d_0.w_0_bias")
|
||||
"Add.3" = Conv <dilations: ints = [1, 1], group: int = 16, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.0.0", "conv2d_161.w_0_lab", "p2o.pd_op.depthwise_conv2d.0.0_bias_lab")
|
||||
val_0 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.3")
|
||||
"p2o.pd_op.hardswish.0.0" = Mul ("Add.3", val_0)
|
||||
"Add.9" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.0.0", "conv2d_162.w_0_lab_lab", "p2o.pd_op.conv2d.1.0_bias_lab_lab")
|
||||
val_1 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.9")
|
||||
"p2o.pd_op.hardswish.1.0" = Mul ("Add.9", val_1)
|
||||
val_2 = Add ("p2o.pd_op.hardswish.1.0", "conv2d_163.w_0_lab_laboffset")
|
||||
"Add.15" = Conv <dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_2, "conv2d_163.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.1.0_bias_lab")
|
||||
"Add.19" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.15", "conv2d_164.w_0_lab", "p2o.pd_op.conv2d.2.0_bias_lab")
|
||||
val_3 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.19")
|
||||
"p2o.pd_op.hardswish.2.0" = Mul ("Add.19", val_3)
|
||||
val_4 = Add ("p2o.pd_op.hardswish.2.0", "conv2d_165.w_0_lab_laboffset")
|
||||
"Add.25" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_4, "conv2d_165.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.2.0_bias_lab")
|
||||
val_5 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.25")
|
||||
"p2o.pd_op.hardswish.3.0" = Mul ("Add.25", val_5)
|
||||
"Add.31" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.3.0", "conv2d_166.w_0_lab_lab", "p2o.pd_op.conv2d.3.0_bias_lab_lab")
|
||||
val_6 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.31")
|
||||
"p2o.pd_op.hardswish.4.0" = Mul ("Add.31", val_6)
|
||||
val_7 = Add ("p2o.pd_op.hardswish.4.0", "conv2d_167.w_0_lab_laboffset")
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_7, "conv2d_167.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.3.0_bias_lab")
|
||||
"Add.41" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.37", "conv2d_168.w_0_lab", "p2o.pd_op.conv2d.4.0_bias_lab")
|
||||
val_8 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.41")
|
||||
"p2o.pd_op.hardswish.5.0" = Mul ("Add.41", val_8)
|
||||
val_9 = Add ("p2o.pd_op.hardswish.5.0", "conv2d_169.w_0_lab_laboffset")
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_9, "conv2d_169.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.4.0_bias_lab")
|
||||
val_10 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.47")
|
||||
"p2o.pd_op.hardswish.6.0" = Mul ("Add.47", val_10)
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.6.0", "conv2d_170.w_0_lab_lab", "p2o.pd_op.conv2d.5.0_bias_lab_lab")
|
||||
val_11 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.53")
|
||||
"p2o.pd_op.hardswish.7.0" = Mul ("Add.53", val_11)
|
||||
val_12 = Add ("p2o.pd_op.hardswish.7.0", "conv2d_171.w_0_lab_laboffset")
|
||||
"Add.59" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_12, "conv2d_171.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.5.0_bias_lab")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.59", "conv2d_172.w_0_lab", "p2o.pd_op.conv2d.6.0_bias_lab")
|
||||
val_13 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.63")
|
||||
"p2o.pd_op.hardswish.8.0" = Mul ("Add.63", val_13)
|
||||
val_14 = Add ("p2o.pd_op.hardswish.8.0", "conv2d_173.w_0_lab_laboffset")
|
||||
"Add.69" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_14, "conv2d_173.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.6.0_bias_lab")
|
||||
val_15 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.69")
|
||||
"p2o.pd_op.hardswish.9.0" = Mul ("Add.69", val_15)
|
||||
"Add.75" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.9.0", "conv2d_174.w_0_lab_lab", "p2o.pd_op.conv2d.7.0_bias_lab_lab")
|
||||
val_16 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.75")
|
||||
"p2o.pd_op.hardswish.10.0" = Mul ("Add.75", val_16)
|
||||
val_17 = Add ("p2o.pd_op.hardswish.10.0", "conv2d_175.w_0_lab_laboffset")
|
||||
"Add.81" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_17, "conv2d_175.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.7.0_bias_lab")
|
||||
val_18 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.81")
|
||||
"p2o.pd_op.hardswish.11.0" = Mul ("Add.81", val_18)
|
||||
"Add.87" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.11.0", "conv2d_176.w_0_lab_lab", "p2o.pd_op.conv2d.8.0_bias_lab_lab")
|
||||
val_19 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.87")
|
||||
"p2o.pd_op.hardswish.12.0" = Mul ("Add.87", val_19)
|
||||
val_20 = Add ("p2o.pd_op.hardswish.12.0", "conv2d_177.w_0_lab_laboffset")
|
||||
"Add.93" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_20, "conv2d_177.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.8.0_bias_lab")
|
||||
val_21 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.93")
|
||||
"p2o.pd_op.hardswish.13.0" = Mul ("Add.93", val_21)
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.13.0", "conv2d_178.w_0_lab_lab", "p2o.pd_op.conv2d.9.0_bias_lab_lab")
|
||||
val_22 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.99")
|
||||
"p2o.pd_op.hardswish.14.0" = Mul ("Add.99", val_22)
|
||||
val_23 = Add ("p2o.pd_op.hardswish.14.0", "conv2d_179.w_0_lab_laboffset")
|
||||
"Add.105" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_23, "conv2d_179.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.9.0_bias_lab")
|
||||
val_24 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.105")
|
||||
"p2o.pd_op.hardswish.15.0" = Mul ("Add.105", val_24)
|
||||
"Add.111" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.15.0", "conv2d_180.w_0_lab_lab", "p2o.pd_op.conv2d.10.0_bias_lab_lab")
|
||||
val_25 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.111")
|
||||
"p2o.pd_op.hardswish.16.0" = Mul ("Add.111", val_25)
|
||||
val_26 = Add ("p2o.pd_op.hardswish.16.0", "conv2d_181.w_0_lab_laboffset")
|
||||
"Add.117" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [2, 2]> (val_26, "conv2d_181.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.10.0_bias_lab")
|
||||
["GlobalAveragePool.0"] "p2o.pd_op.pool2d.0.0" = GlobalAveragePool ("Add.117")
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.0.0", "conv2d_96.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.119")
|
||||
"Add.121" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_97.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.121")
|
||||
["Mul.76"] "Mul.77" = Mul ("Add.117", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.77", "conv2d_182.w_0_lab", "p2o.pd_op.conv2d.13.0_bias_lab")
|
||||
val_27 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.125")
|
||||
"p2o.pd_op.hardswish.17.0" = Mul ("Add.125", val_27)
|
||||
val_28 = Add ("p2o.pd_op.hardswish.17.0", "conv2d_183.w_0_lab_laboffset")
|
||||
"Add.131" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_28, "conv2d_183.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.11.0_bias_lab")
|
||||
val_29 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.131")
|
||||
"p2o.pd_op.hardswish.18.0" = Mul ("Add.131", val_29)
|
||||
["Mul.84"] "Mul.85" = Mul ("learnable_affine_block_45.w_0", "p2o.pd_op.hardswish.18.0")
|
||||
["Add.132"] "Add.133" = Add ("Mul.85", "learnable_affine_block_45.w_1")
|
||||
["GlobalAveragePool.1"] "p2o.pd_op.pool2d.1.0" = GlobalAveragePool ("Add.133")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.1.0", "conv2d_107.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.135")
|
||||
"Add.137" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_108.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.137")
|
||||
["Mul.86"] "Mul.87" = Mul ("Add.133", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.141" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.87", "conv2d_184.w_0_lab", "p2o.pd_op.conv2d.16.0_bias_lab")
|
||||
val_30 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.141")
|
||||
"p2o.pd_op.hardswish.19.0" = Mul ("Add.141", val_30)
|
||||
val_31 = Add ("p2o.pd_op.hardswish.19.0", "conv2d_185.w_0_lab_laboffset")
|
||||
"Add.147" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_31, "conv2d_185.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.12.0_bias_lab")
|
||||
val_32 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.147")
|
||||
"p2o.pd_op.hardswish.20.0" = Mul ("Add.147", val_32)
|
||||
"Add.153" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.20.0", "conv2d_186.w_0_lab_lab", "p2o.pd_op.conv2d.17.0_bias_lab_lab")
|
||||
val_33 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.153")
|
||||
"p2o.pd_op.hardswish.21.0" = Mul ("Add.153", val_33)
|
||||
val_34 = Add ("p2o.pd_op.hardswish.21.0", "conv2d_187.w_0_lab_laboffset")
|
||||
"Add.159" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_34, "conv2d_187.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.13.0_bias_lab")
|
||||
val_35 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.159")
|
||||
"p2o.pd_op.hardswish.22.0" = Mul ("Add.159", val_35)
|
||||
"Add.165" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.22.0", "conv2d_188.w_0_lab_lab", "p2o.pd_op.conv2d.18.0_bias_lab_lab")
|
||||
val_36 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.165")
|
||||
"p2o.pd_op.hardswish.23.0" = Mul ("Add.165", val_36)
|
||||
"p2o.pd_op.conv2d.23.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.23.0", "Conv.37_folded_w_lab", "Conv.37_folded_b_lab")
|
||||
["GlobalAveragePool.2"] "p2o.pd_op.pool2d.2.0" = GlobalAveragePool ("p2o.pd_op.conv2d.23.0")
|
||||
"p2o.pd_op.conv2d.26.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_26, "Conv.40_folded_w_labscale", "Conv.40_folded_b")
|
||||
["GlobalAveragePool.3"] "p2o.pd_op.pool2d.3.0" = GlobalAveragePool ("p2o.pd_op.conv2d.26.0")
|
||||
"p2o.pd_op.conv2d.29.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_12, "Conv.43_folded_w_labscale", "Conv.43_folded_b")
|
||||
["GlobalAveragePool.4"] "p2o.pd_op.pool2d.4.0" = GlobalAveragePool ("p2o.pd_op.conv2d.29.0")
|
||||
"p2o.pd_op.conv2d.32.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_7, "Conv.46_folded_w_labscale", "Conv.46_folded_b")
|
||||
["GlobalAveragePool.5"] "p2o.pd_op.pool2d.5.0" = GlobalAveragePool ("p2o.pd_op.conv2d.32.0")
|
||||
se_group0_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.2.0", "p2o.pd_op.pool2d.3.0", "p2o.pd_op.pool2d.4.0", "p2o.pd_op.pool2d.5.0")
|
||||
se_group0_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_pooled, se_group0_down1, se_group0_down2)
|
||||
se_group0_relu = Relu (se_group0_down)
|
||||
se_group0_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_relu, se_group0_up1, se_group0_up2)
|
||||
se_group0_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group0_up)
|
||||
"se_group0_p2o.pd_op.hardsigmoid.2.0", "se_group0_p2o.pd_op.hardsigmoid.3.0", "se_group0_p2o.pd_op.hardsigmoid.4.0", "se_group0_p2o.pd_op.hardsigmoid.5.0" = Split <axis: int = 1> (se_group0_gates, se_group0_sizes)
|
||||
val_37 = Add ("se_group0_p2o.pd_op.hardsigmoid.2.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.181" = Mul ("p2o.pd_op.conv2d.23.0", val_37)
|
||||
val_38 = Add ("se_group0_p2o.pd_op.hardsigmoid.3.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.187" = Mul ("p2o.pd_op.conv2d.26.0", val_38)
|
||||
val_39 = Add ("se_group0_p2o.pd_op.hardsigmoid.4.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.193" = Mul ("p2o.pd_op.conv2d.29.0", val_39)
|
||||
val_40 = Add ("se_group0_p2o.pd_op.hardsigmoid.5.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.199" = Mul ("p2o.pd_op.conv2d.32.0", val_40)
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.181", "helper.constant.1", "helper.constant.0")
|
||||
["Add.200"] "Add.201" = Add ("Add.187", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.201", "helper.constant.1", "helper.constant.0")
|
||||
["Add.202"] "Add.203" = Add ("Add.193", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.203", "helper.constant.1", "helper.constant.0")
|
||||
["Add.204"] "Add.205" = Add ("Add.199", "p2o.pd_op.nearest_interp.2.0")
|
||||
["Conv.49"] "p2o.pd_op.conv2d.35.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.181", "conv2d_156.w_0")
|
||||
["GlobalAveragePool.6"] "p2o.pd_op.pool2d.6.0" = GlobalAveragePool ("p2o.pd_op.conv2d.35.0")
|
||||
["Conv.52"] "p2o.pd_op.conv2d.38.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.201", "conv2d_150.w_0")
|
||||
["GlobalAveragePool.7"] "p2o.pd_op.pool2d.7.0" = GlobalAveragePool ("p2o.pd_op.conv2d.38.0")
|
||||
["Conv.55"] "p2o.pd_op.conv2d.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.203", "conv2d_144.w_0")
|
||||
["GlobalAveragePool.8"] "p2o.pd_op.pool2d.8.0" = GlobalAveragePool ("p2o.pd_op.conv2d.41.0")
|
||||
["Conv.58"] "p2o.pd_op.conv2d.44.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.205", "conv2d_138.w_0")
|
||||
["GlobalAveragePool.9"] "p2o.pd_op.pool2d.9.0" = GlobalAveragePool ("p2o.pd_op.conv2d.44.0")
|
||||
se_group1_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.6.0", "p2o.pd_op.pool2d.7.0", "p2o.pd_op.pool2d.8.0", "p2o.pd_op.pool2d.9.0")
|
||||
se_group1_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_pooled, se_group1_down1, se_group1_down2)
|
||||
se_group1_relu = Relu (se_group1_down)
|
||||
se_group1_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_relu, se_group1_up1, se_group1_up2)
|
||||
se_group1_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group1_up)
|
||||
"se_group1_p2o.pd_op.hardsigmoid.6.0", "se_group1_p2o.pd_op.hardsigmoid.7.0", "se_group1_p2o.pd_op.hardsigmoid.8.0", "se_group1_p2o.pd_op.hardsigmoid.9.0" = Split <axis: int = 1> (se_group1_gates, se_group1_sizes)
|
||||
val_41 = Add ("se_group1_p2o.pd_op.hardsigmoid.6.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.211" = Mul ("p2o.pd_op.conv2d.35.0", val_41)
|
||||
val_42 = Add ("se_group1_p2o.pd_op.hardsigmoid.7.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.217" = Mul ("p2o.pd_op.conv2d.38.0", val_42)
|
||||
val_43 = Add ("se_group1_p2o.pd_op.hardsigmoid.8.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.223" = Mul ("p2o.pd_op.conv2d.41.0", val_43)
|
||||
val_44 = Add ("se_group1_p2o.pd_op.hardsigmoid.9.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.229" = Mul ("p2o.pd_op.conv2d.44.0", val_44)
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.211", "helper.constant.1", "helper.constant.6")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.217", "helper.constant.1", "helper.constant.8")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.223", "helper.constant.1", "helper.constant.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.229")
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.1", "conv2d_159.w_0", "conv2d_159.w_0_bias")
|
||||
["Relu.10"] "p2o.pd_op.relu.10.0" = Relu ("p2o.pd_op.batch_norm_.1.0")
|
||||
"p2o.pd_op.batch_norm_.2.0" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.10.0", "auto.cast.57", "ConvTranspose.1_bias")
|
||||
["Relu.11"] "p2o.pd_op.relu.11.0" = Relu ("p2o.pd_op.batch_norm_.2.0")
|
||||
"Add.233" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.11.0", "auto.cast.60", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] fetch_name_0 = Sigmoid ("Add.233")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
Conv.37_folded_b_lab FLOAT[96] 0d571951a1e0
|
||||
Conv.37_folded_w_lab FLOAT[96,384,1,1] 1d0305563ea7
|
||||
Conv.40_folded_b FLOAT[96] dcfdd514912d
|
||||
Conv.40_folded_w_labscale FLOAT[96,192,1,1] bacc8274202e
|
||||
Conv.43_folded_b FLOAT[96] ee902cf71aad
|
||||
Conv.43_folded_w_labscale FLOAT[96,96,1,1] b17e08485dc5
|
||||
Conv.46_folded_b FLOAT[96] 6541e510a35d
|
||||
Conv.46_folded_w_labscale FLOAT[96,48,1,1] 9423b2c0951a
|
||||
ConvTranspose.1_bias FLOAT[24] 64cabf62980d
|
||||
ConvTranspose.3_bias FLOAT[1] 55c86fee1edb
|
||||
auto.cast.57 FLOAT[24,24,2,2] 1dc864bec64f
|
||||
auto.cast.60 FLOAT[24,1,2,2] c9862b3a19bc
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_0.w_0 FLOAT[16,3,3,3] 7841f2f3efae
|
||||
conv2d_0.w_0_bias FLOAT[16] 2713bf453fd1
|
||||
conv2d_107.w_0 FLOAT[96,384,1,1] 2fc401aa1ec6
|
||||
conv2d_108.w_0 FLOAT[384,96,1,1] f2a9a9261c07
|
||||
conv2d_138.w_0 FLOAT[24,96,3,3] 47aa8ba1db50
|
||||
conv2d_144.w_0 FLOAT[24,96,3,3] cd85b03c436c
|
||||
conv2d_150.w_0 FLOAT[24,96,3,3] 591f14004ce0
|
||||
conv2d_156.w_0 FLOAT[24,96,3,3] 5e0bc4bf821e
|
||||
conv2d_159.w_0 FLOAT[24,96,3,3] 43b6b1b17bef
|
||||
conv2d_159.w_0_bias FLOAT[24] c98267f8273d
|
||||
conv2d_161.w_0_lab FLOAT[16,1,3,3] 22528d709d37
|
||||
conv2d_162.w_0_lab_lab FLOAT[32,16,1,1] 051645505e21
|
||||
conv2d_163.w_0_lab_laboffset FLOAT[] 92a142f7dc41
|
||||
conv2d_163.w_0_lab_labscale FLOAT[32,1,3,3] 8694842bd3fb
|
||||
conv2d_164.w_0_lab FLOAT[48,32,1,1] 0c937f040d0e
|
||||
conv2d_165.w_0_lab_laboffset FLOAT[] 012179917694
|
||||
conv2d_165.w_0_lab_labscale FLOAT[48,1,3,3] 7d779e5616fa
|
||||
conv2d_166.w_0_lab_lab FLOAT[48,48,1,1] d70c86b2d1ec
|
||||
conv2d_167.w_0_lab_laboffset FLOAT[] 9741b37d98e3
|
||||
conv2d_167.w_0_lab_labscale FLOAT[48,1,3,3] fa2e1db2eb62
|
||||
conv2d_168.w_0_lab FLOAT[96,48,1,1] 81e13e0bd382
|
||||
conv2d_169.w_0_lab_laboffset FLOAT[] f3e015d53e9a
|
||||
conv2d_169.w_0_lab_labscale FLOAT[96,1,3,3] 75bbb69deb68
|
||||
conv2d_170.w_0_lab_lab FLOAT[96,96,1,1] 59b22a69e345
|
||||
conv2d_171.w_0_lab_laboffset FLOAT[] f42328163f40
|
||||
conv2d_171.w_0_lab_labscale FLOAT[96,1,3,3] 65cbca6287a2
|
||||
conv2d_172.w_0_lab FLOAT[192,96,1,1] ff93ca701d2f
|
||||
conv2d_173.w_0_lab_laboffset FLOAT[] b76450d3656f
|
||||
conv2d_173.w_0_lab_labscale FLOAT[192,1,5,5] 28d7de00679c
|
||||
conv2d_174.w_0_lab_lab FLOAT[192,192,1,1] 53cf6f343ec2
|
||||
conv2d_175.w_0_lab_laboffset FLOAT[] e665434a5d2d
|
||||
conv2d_175.w_0_lab_labscale FLOAT[192,1,5,5] 3c0aa815839d
|
||||
conv2d_176.w_0_lab_lab FLOAT[192,192,1,1] cb45f031f07b
|
||||
conv2d_177.w_0_lab_laboffset FLOAT[] e095ffc76247
|
||||
conv2d_177.w_0_lab_labscale FLOAT[192,1,5,5] 22fe03b75591
|
||||
conv2d_178.w_0_lab_lab FLOAT[192,192,1,1] c259022f5c3d
|
||||
conv2d_179.w_0_lab_laboffset FLOAT[] 5842420f0e64
|
||||
conv2d_179.w_0_lab_labscale FLOAT[192,1,5,5] 408bbab0d507
|
||||
conv2d_180.w_0_lab_lab FLOAT[192,192,1,1] 85871ea30bf1
|
||||
conv2d_181.w_0_lab_laboffset FLOAT[] 9e0407355f14
|
||||
conv2d_181.w_0_lab_labscale FLOAT[192,1,5,5] 75764b0f5265
|
||||
conv2d_182.w_0_lab FLOAT[384,192,1,1] 81235d1a972f
|
||||
conv2d_183.w_0_lab_laboffset FLOAT[] e648d792317a
|
||||
conv2d_183.w_0_lab_labscale FLOAT[384,1,5,5] f5341adaad28
|
||||
conv2d_184.w_0_lab FLOAT[384,384,1,1] c37a7cec640b
|
||||
conv2d_185.w_0_lab_laboffset FLOAT[] 768fa13da14b
|
||||
conv2d_185.w_0_lab_labscale FLOAT[384,1,5,5] 6bacb713155c
|
||||
conv2d_186.w_0_lab_lab FLOAT[384,384,1,1] 2fa80ae1b18f
|
||||
conv2d_187.w_0_lab_laboffset FLOAT[] ad505dafbd90
|
||||
conv2d_187.w_0_lab_labscale FLOAT[384,1,5,5] a221bd8406f2
|
||||
conv2d_188.w_0_lab_lab FLOAT[384,384,1,1] 9ea062b2f1b4
|
||||
conv2d_96.w_0 FLOAT[48,192,1,1] 6d73ce1fb738
|
||||
conv2d_97.w_0 FLOAT[192,48,1,1] 8098a00a81f0
|
||||
helper.constant.0 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.1 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.6 FLOAT[4] cf5451a623be
|
||||
helper.constant.8 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
learnable_affine_block_45.w_0 FLOAT[1] 65444e550b77
|
||||
learnable_affine_block_45.w_1 FLOAT[1] f2ee18a061af
|
||||
p2o.pd_op.conv2d.1.0_bias_lab_lab FLOAT[32] 3f4be24e33b8
|
||||
p2o.pd_op.conv2d.10.0_bias_lab_lab FLOAT[192] e32536500417
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[48] 961ec85108cb
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[192] c348751cbed0
|
||||
p2o.pd_op.conv2d.13.0_bias_lab FLOAT[384] 1b6d0aa0e977
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[96] 7876208c6fb1
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[384] 871907fff11d
|
||||
p2o.pd_op.conv2d.16.0_bias_lab FLOAT[384] fd15d67f1e85
|
||||
p2o.pd_op.conv2d.17.0_bias_lab_lab FLOAT[384] 097f0d068f05
|
||||
p2o.pd_op.conv2d.18.0_bias_lab_lab FLOAT[384] b8e228cae698
|
||||
p2o.pd_op.conv2d.2.0_bias_lab FLOAT[48] 8138a593f8f2
|
||||
p2o.pd_op.conv2d.3.0_bias_lab_lab FLOAT[48] 57128b896e31
|
||||
p2o.pd_op.conv2d.4.0_bias_lab FLOAT[96] d2230ff7a27e
|
||||
p2o.pd_op.conv2d.5.0_bias_lab_lab FLOAT[96] 05b9a5f236b6
|
||||
p2o.pd_op.conv2d.6.0_bias_lab FLOAT[192] a990b3fed4dd
|
||||
p2o.pd_op.conv2d.7.0_bias_lab_lab FLOAT[192] 74df3e4f22b6
|
||||
p2o.pd_op.conv2d.8.0_bias_lab_lab FLOAT[192] 9c072f4b4032
|
||||
p2o.pd_op.conv2d.9.0_bias_lab_lab FLOAT[192] 8f6e7021fe63
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias_lab FLOAT[16] 5b3de9e3f7c2
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias_lab FLOAT[32] bb4239a962eb
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias_lab FLOAT[192] 81ac3c08eae1
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias_lab FLOAT[384] 2236a6b52e38
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias_lab FLOAT[384] 14c22d416e3b
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias_lab FLOAT[384] 4eebd04fbeb4
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias_lab FLOAT[48] aaee6f6db9c1
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias_lab FLOAT[48] dcc78f972645
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias_lab FLOAT[96] dbd763cef105
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias_lab FLOAT[96] 5849d6801824
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias_lab FLOAT[192] 01e9219938aa
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias_lab FLOAT[192] e35d55fdac89
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias_lab FLOAT[192] fd7c6cc0a8fb
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias_lab FLOAT[192] aedc2ab77e2b
|
||||
p2o.pd_op.hardsigmoid.2.0_one FLOAT[] e00e5eb94441
|
||||
se_group0_down1 FLOAT[96,96,1,1] 4c8c888b01f2
|
||||
se_group0_down2 FLOAT[96] b99146f86442
|
||||
se_group0_sizes INT64[4] 4bb249469bee
|
||||
se_group0_up1 FLOAT[384,24,1,1] 1446892243f3
|
||||
se_group0_up2 FLOAT[384] 8538540d9317
|
||||
se_group1_down1 FLOAT[24,24,1,1] 01a670ee8021
|
||||
se_group1_down2 FLOAT[24] 7f8067be0db7
|
||||
se_group1_sizes INT64[4] 5c995dc6a0ef
|
||||
se_group1_up1 FLOAT[96,6,1,1] 3e47b305535b
|
||||
se_group1_up2 FLOAT[96] ed3a93d396c3
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,676 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,1024,unk__46,unk__47] "Add.1"
|
||||
float[batch,32,unk__28,unk__29] "Add.109"
|
||||
float[batch,64,unk__28,unk__29] "Add.11"
|
||||
float[batch,32,unk__28,unk__29] "Add.119"
|
||||
float[batch,64,unk__28,unk__29] "Add.123"
|
||||
float[batch,32,unk__8,unk__9] "Add.125"
|
||||
float[batch,64,unk__46,unk__47] "Add.13"
|
||||
float[batch,32,unk__8,unk__9] "Add.135"
|
||||
float[batch,32,unk__8,unk__9] "Add.145"
|
||||
float[batch,64,unk__136,unk__137] "Add.15"
|
||||
float[batch,32,unk__8,unk__9] "Add.155"
|
||||
float[batch,64,unk__8,unk__9] "Add.159"
|
||||
float[batch,1,height,width] "Add.163"
|
||||
float[batch,1,height,width] "Add.165"
|
||||
float[batch,1,height,width] "Add.167"
|
||||
float[batch,32,unk__136,unk__137] "Add.17"
|
||||
float[batch,32,unk__136,unk__137] "Add.27"
|
||||
float[batch,1024,unk__46,unk__47] "Add.3"
|
||||
float[batch,32,unk__136,unk__137] "Add.37"
|
||||
float[batch,32,unk__136,unk__137] "Add.47"
|
||||
float[batch,256,unk__46,unk__47] "Add.5"
|
||||
float[batch,64,unk__136,unk__137] "Add.51"
|
||||
float[batch,32,unk__46,unk__47] "Add.53"
|
||||
float[batch,32,unk__46,unk__47] "Add.63"
|
||||
float[batch,256,unk__28,unk__29] "Add.7"
|
||||
float[batch,32,unk__46,unk__47] "Add.73"
|
||||
float[batch,32,unk__46,unk__47] "Add.83"
|
||||
float[batch,64,unk__46,unk__47] "Add.87"
|
||||
float[batch,32,unk__28,unk__29] "Add.89"
|
||||
float[batch,256,unk__8,unk__9] "Add.9"
|
||||
float[batch,32,unk__28,unk__29] "Add.99"
|
||||
float[batch,64,unk__0,unk__1] "Concat.1"
|
||||
float[batch,2176,unk__46,unk__47] "Concat.11"
|
||||
float[batch,3328,unk__136,unk__137] "Concat.13"
|
||||
float[batch,256,unk__8,unk__9] "Concat.15"
|
||||
float[batch,65,height,width] "Concat.17"
|
||||
float[batch,336,unk__8,unk__9] "Concat.3"
|
||||
float[batch,704,unk__28,unk__29] "Concat.5"
|
||||
float[batch,1664,unk__46,unk__47] "Concat.7"
|
||||
float[batch,2176,unk__46,unk__47] "Concat.9"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.10.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.batch_norm_.11.0"
|
||||
float[batch,128,unk__8,unk__9] "p2o.pd_op.batch_norm_.12.0"
|
||||
float[batch,128,unk__28,unk__29] "p2o.pd_op.batch_norm_.13.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.batch_norm_.14.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.batch_norm_.15.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.batch_norm_.16.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.batch_norm_.17.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.batch_norm_.18.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.batch_norm_.19.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,256,unk__28,unk__29] "p2o.pd_op.batch_norm_.20.0"
|
||||
float[batch,512,unk__28,unk__29] "p2o.pd_op.batch_norm_.21.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.batch_norm_.22.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.23.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.24.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.25.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.26.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.27.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.28.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.29.0"
|
||||
float[batch,32,unk__8,unk__9] "p2o.pd_op.batch_norm_.3.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.30.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.31.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.32.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.33.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.34.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.batch_norm_.35.0"
|
||||
float[batch,1024,unk__46,unk__47] "p2o.pd_op.batch_norm_.36.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.37.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.38.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.39.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.4.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.40.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.41.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.42.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.43.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.44.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.45.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.46.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.47.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.48.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.batch_norm_.49.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.5.0"
|
||||
float[batch,1024,unk__46,unk__47] "p2o.pd_op.batch_norm_.50.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.51.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.52.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.53.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.54.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.55.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.56.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.57.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.58.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.59.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.6.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.60.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.61.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.batch_norm_.62.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.batch_norm_.63.0"
|
||||
float[batch,1024,unk__46,unk__47] "p2o.pd_op.batch_norm_.64.0"
|
||||
float[batch,1024,unk__136,unk__137] "p2o.pd_op.batch_norm_.65.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.66.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.67.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.68.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.69.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.7.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.70.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.71.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.72.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.73.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.74.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.75.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.76.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.batch_norm_.77.0"
|
||||
float[batch,1024,unk__136,unk__137] "p2o.pd_op.batch_norm_.78.0"
|
||||
float[batch,2048,unk__136,unk__137] "p2o.pd_op.batch_norm_.79.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.8.0"
|
||||
float[batch,64,unk__136,unk__137] "p2o.pd_op.batch_norm_.80.0"
|
||||
float[batch,64,unk__46,unk__47] "p2o.pd_op.batch_norm_.81.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.batch_norm_.82.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.batch_norm_.83.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.batch_norm_.84.0"
|
||||
float[batch,64,unk__0,unk__1] "p2o.pd_op.batch_norm_.85.0"
|
||||
float[batch,64,height,width] "p2o.pd_op.batch_norm_.86.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.batch_norm_.9.0"
|
||||
float[batch,256,unk__136,unk__137] "p2o.pd_op.conv2d.53.0"
|
||||
float[batch,256,unk__46,unk__47] "p2o.pd_op.conv2d.54.0"
|
||||
float[batch,256,unk__28,unk__29] "p2o.pd_op.conv2d.55.0"
|
||||
float[batch,256,unk__8,unk__9] "p2o.pd_op.conv2d.56.0"
|
||||
float[batch,64,unk__136,unk__137] "p2o.pd_op.conv2d.57.0"
|
||||
float[batch,64,unk__46,unk__47] "p2o.pd_op.conv2d.58.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.conv2d.59.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.conv2d.60.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.conv2d.61.0"
|
||||
float[batch,64,unk__46,unk__47] "p2o.pd_op.conv2d.62.0"
|
||||
float[batch,64,unk__136,unk__137] "p2o.pd_op.conv2d.63.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.conv2d.64.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.conv2d.65.0"
|
||||
float[batch,64,unk__46,unk__47] "p2o.pd_op.conv2d.66.0"
|
||||
float[batch,64,unk__136,unk__137] "p2o.pd_op.conv2d.67.0"
|
||||
float[batch,256,unk__46,unk__47] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,256,unk__28,unk__29] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,256,unk__8,unk__9] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,64,height,width] "p2o.pd_op.nearest_interp.6.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.10.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.relu.11.0"
|
||||
float[batch,128,unk__8,unk__9] "p2o.pd_op.relu.12.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.relu.13.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.relu.14.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.relu.15.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.relu.16.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.relu.17.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.relu.18.0"
|
||||
float[batch,256,unk__28,unk__29] "p2o.pd_op.relu.19.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.relu.2.0"
|
||||
float[batch,512,unk__28,unk__29] "p2o.pd_op.relu.20.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.21.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.22.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.23.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.24.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.25.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.26.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.relu.27.0"
|
||||
float[batch,1024,unk__46,unk__47] "p2o.pd_op.relu.28.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.29.0"
|
||||
float[batch,32,unk__8,unk__9] "p2o.pd_op.relu.3.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.30.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.31.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.32.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.33.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.34.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.relu.35.0"
|
||||
float[batch,1024,unk__46,unk__47] "p2o.pd_op.relu.36.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.37.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.38.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.39.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.4.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.40.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.41.0"
|
||||
float[batch,192,unk__46,unk__47] "p2o.pd_op.relu.42.0"
|
||||
float[batch,512,unk__46,unk__47] "p2o.pd_op.relu.43.0"
|
||||
float[batch,1024,unk__46,unk__47] "p2o.pd_op.relu.44.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.relu.45.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.relu.46.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.relu.47.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.relu.48.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.relu.49.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.5.0"
|
||||
float[batch,384,unk__136,unk__137] "p2o.pd_op.relu.50.0"
|
||||
float[batch,1024,unk__136,unk__137] "p2o.pd_op.relu.51.0"
|
||||
float[batch,2048,unk__136,unk__137] "p2o.pd_op.relu.52.0"
|
||||
float[batch,64,unk__136,unk__137] "p2o.pd_op.relu.53.0"
|
||||
float[batch,64,unk__46,unk__47] "p2o.pd_op.relu.54.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.relu.55.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.relu.56.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.relu.57.0"
|
||||
float[batch,64,unk__0,unk__1] "p2o.pd_op.relu.58.0"
|
||||
float[batch,64,height,width] "p2o.pd_op.relu.59.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.6.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.7.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.8.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.9.0"
|
||||
float[batch,1,height,width] "p2o.pd_op.sigmoid.0.0"
|
||||
float[batch,1,height,width] "p2o.pd_op.sigmoid.1.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_0.w_0", "conv2d_0.w_0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("p2o.pd_op.batch_norm_.0.0")
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <auto_pad: string = "SAME_UPPER", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_1.w_0", "conv2d_1.w_0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("p2o.pd_op.batch_norm_.1.0")
|
||||
"p2o.pd_op.batch_norm_.2.0" = Conv <auto_pad: string = "SAME_UPPER", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_2.w_0", "conv2d_2.w_0_bias")
|
||||
["Relu.2"] "p2o.pd_op.relu.2.0" = Relu ("p2o.pd_op.batch_norm_.2.0")
|
||||
["MaxPool.0"] "p2o.pd_op.pool2d.0.0" = MaxPool <auto_pad: string = "SAME_UPPER", ceil_mode: int = 0, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.pool2d.0.0", "p2o.pd_op.relu.2.0")
|
||||
"p2o.pd_op.batch_norm_.3.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Concat.1", "conv2d_3.w_0", "conv2d_3.w_0_bias")
|
||||
["Relu.3"] "p2o.pd_op.relu.3.0" = Relu ("p2o.pd_op.batch_norm_.3.0")
|
||||
"p2o.pd_op.batch_norm_.4.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.3.0", "conv2d_4.w_0", "conv2d_4.w_0_bias")
|
||||
["Relu.4"] "p2o.pd_op.relu.4.0" = Relu ("p2o.pd_op.batch_norm_.4.0")
|
||||
"p2o.pd_op.batch_norm_.5.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.4.0", "conv2d_5.w_0", "conv2d_5.w_0_bias")
|
||||
["Relu.5"] "p2o.pd_op.relu.5.0" = Relu ("p2o.pd_op.batch_norm_.5.0")
|
||||
"p2o.pd_op.batch_norm_.6.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.5.0", "conv2d_6.w_0", "conv2d_6.w_0_bias")
|
||||
["Relu.6"] "p2o.pd_op.relu.6.0" = Relu ("p2o.pd_op.batch_norm_.6.0")
|
||||
"p2o.pd_op.batch_norm_.7.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.6.0", "conv2d_7.w_0", "conv2d_7.w_0_bias")
|
||||
["Relu.7"] "p2o.pd_op.relu.7.0" = Relu ("p2o.pd_op.batch_norm_.7.0")
|
||||
"p2o.pd_op.batch_norm_.8.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.7.0", "conv2d_8.w_0", "conv2d_8.w_0_bias")
|
||||
["Relu.8"] "p2o.pd_op.relu.8.0" = Relu ("p2o.pd_op.batch_norm_.8.0")
|
||||
"p2o.pd_op.batch_norm_.9.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.8.0", "conv2d_9.w_0", "conv2d_9.w_0_bias")
|
||||
["Relu.9"] "p2o.pd_op.relu.9.0" = Relu ("p2o.pd_op.batch_norm_.9.0")
|
||||
"p2o.pd_op.batch_norm_.10.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.9.0", "conv2d_10.w_0", "conv2d_10.w_0_bias")
|
||||
["Relu.10"] "p2o.pd_op.relu.10.0" = Relu ("p2o.pd_op.batch_norm_.10.0")
|
||||
["Concat.2"] "Concat.3" = Concat <axis: int = 1> ("p2o.pd_op.relu.4.0", "p2o.pd_op.relu.5.0", "p2o.pd_op.relu.6.0", "p2o.pd_op.relu.7.0", "p2o.pd_op.relu.8.0", "p2o.pd_op.relu.9.0", "p2o.pd_op.relu.10.0")
|
||||
"p2o.pd_op.batch_norm_.11.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Concat.3", "conv2d_11.w_0", "conv2d_11.w_0_bias")
|
||||
["Relu.11"] "p2o.pd_op.relu.11.0" = Relu ("p2o.pd_op.batch_norm_.11.0")
|
||||
"p2o.pd_op.batch_norm_.12.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.11.0", "conv2d_12.w_0", "conv2d_12.w_0_bias")
|
||||
["Relu.12"] "p2o.pd_op.relu.12.0" = Relu ("p2o.pd_op.batch_norm_.12.0")
|
||||
"p2o.pd_op.batch_norm_.13.0" = Conv <dilations: ints = [1, 1], group: int = 128, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("p2o.pd_op.relu.12.0", "conv2d_13.w_0", "conv2d_13.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.14.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.13.0", "conv2d_14.w_0", "conv2d_14.w_0_bias")
|
||||
["Relu.13"] "p2o.pd_op.relu.13.0" = Relu ("p2o.pd_op.batch_norm_.14.0")
|
||||
"p2o.pd_op.batch_norm_.15.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.13.0", "conv2d_15.w_0", "conv2d_15.w_0_bias")
|
||||
["Relu.14"] "p2o.pd_op.relu.14.0" = Relu ("p2o.pd_op.batch_norm_.15.0")
|
||||
"p2o.pd_op.batch_norm_.16.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.14.0", "conv2d_16.w_0", "conv2d_16.w_0_bias")
|
||||
["Relu.15"] "p2o.pd_op.relu.15.0" = Relu ("p2o.pd_op.batch_norm_.16.0")
|
||||
"p2o.pd_op.batch_norm_.17.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.15.0", "conv2d_17.w_0", "conv2d_17.w_0_bias")
|
||||
["Relu.16"] "p2o.pd_op.relu.16.0" = Relu ("p2o.pd_op.batch_norm_.17.0")
|
||||
"p2o.pd_op.batch_norm_.18.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.16.0", "conv2d_18.w_0", "conv2d_18.w_0_bias")
|
||||
["Relu.17"] "p2o.pd_op.relu.17.0" = Relu ("p2o.pd_op.batch_norm_.18.0")
|
||||
"p2o.pd_op.batch_norm_.19.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.17.0", "conv2d_19.w_0", "conv2d_19.w_0_bias")
|
||||
["Relu.18"] "p2o.pd_op.relu.18.0" = Relu ("p2o.pd_op.batch_norm_.19.0")
|
||||
["Concat.4"] "Concat.5" = Concat <axis: int = 1> ("p2o.pd_op.batch_norm_.13.0", "p2o.pd_op.relu.13.0", "p2o.pd_op.relu.14.0", "p2o.pd_op.relu.15.0", "p2o.pd_op.relu.16.0", "p2o.pd_op.relu.17.0", "p2o.pd_op.relu.18.0")
|
||||
"p2o.pd_op.batch_norm_.20.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Concat.5", "conv2d_20.w_0", "conv2d_20.w_0_bias")
|
||||
["Relu.19"] "p2o.pd_op.relu.19.0" = Relu ("p2o.pd_op.batch_norm_.20.0")
|
||||
"p2o.pd_op.batch_norm_.21.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.19.0", "conv2d_21.w_0", "conv2d_21.w_0_bias")
|
||||
["Relu.20"] "p2o.pd_op.relu.20.0" = Relu ("p2o.pd_op.batch_norm_.21.0")
|
||||
"p2o.pd_op.batch_norm_.22.0" = Conv <dilations: ints = [1, 1], group: int = 512, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("p2o.pd_op.relu.20.0", "conv2d_22.w_0", "conv2d_22.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.23.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.22.0", "conv2d_23.w_0", "conv2d_23.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.24.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.23.0", "conv2d_24.w_0", "conv2d_24.w_0_bias")
|
||||
["Relu.21"] "p2o.pd_op.relu.21.0" = Relu ("p2o.pd_op.batch_norm_.24.0")
|
||||
"p2o.pd_op.batch_norm_.25.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.21.0", "conv2d_25.w_0", "conv2d_25.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.26.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.25.0", "conv2d_26.w_0", "conv2d_26.w_0_bias")
|
||||
["Relu.22"] "p2o.pd_op.relu.22.0" = Relu ("p2o.pd_op.batch_norm_.26.0")
|
||||
"p2o.pd_op.batch_norm_.27.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.22.0", "conv2d_27.w_0", "conv2d_27.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.28.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.27.0", "conv2d_28.w_0", "conv2d_28.w_0_bias")
|
||||
["Relu.23"] "p2o.pd_op.relu.23.0" = Relu ("p2o.pd_op.batch_norm_.28.0")
|
||||
"p2o.pd_op.batch_norm_.29.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.23.0", "conv2d_29.w_0", "conv2d_29.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.30.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.29.0", "conv2d_30.w_0", "conv2d_30.w_0_bias")
|
||||
["Relu.24"] "p2o.pd_op.relu.24.0" = Relu ("p2o.pd_op.batch_norm_.30.0")
|
||||
"p2o.pd_op.batch_norm_.31.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.24.0", "conv2d_31.w_0", "conv2d_31.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.32.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.31.0", "conv2d_32.w_0", "conv2d_32.w_0_bias")
|
||||
["Relu.25"] "p2o.pd_op.relu.25.0" = Relu ("p2o.pd_op.batch_norm_.32.0")
|
||||
"p2o.pd_op.batch_norm_.33.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.25.0", "conv2d_33.w_0", "conv2d_33.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.34.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.33.0", "conv2d_34.w_0", "conv2d_34.w_0_bias")
|
||||
["Relu.26"] "p2o.pd_op.relu.26.0" = Relu ("p2o.pd_op.batch_norm_.34.0")
|
||||
["Concat.6"] "Concat.7" = Concat <axis: int = 1> ("p2o.pd_op.batch_norm_.22.0", "p2o.pd_op.relu.21.0", "p2o.pd_op.relu.22.0", "p2o.pd_op.relu.23.0", "p2o.pd_op.relu.24.0", "p2o.pd_op.relu.25.0", "p2o.pd_op.relu.26.0")
|
||||
"p2o.pd_op.batch_norm_.35.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Concat.7", "conv2d_35.w_0", "conv2d_35.w_0_bias")
|
||||
["Relu.27"] "p2o.pd_op.relu.27.0" = Relu ("p2o.pd_op.batch_norm_.35.0")
|
||||
"p2o.pd_op.batch_norm_.36.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.27.0", "conv2d_36.w_0", "conv2d_36.w_0_bias")
|
||||
["Relu.28"] "p2o.pd_op.relu.28.0" = Relu ("p2o.pd_op.batch_norm_.36.0")
|
||||
"p2o.pd_op.batch_norm_.37.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.28.0", "conv2d_37.w_0", "conv2d_37.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.38.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.37.0", "conv2d_38.w_0", "conv2d_38.w_0_bias")
|
||||
["Relu.29"] "p2o.pd_op.relu.29.0" = Relu ("p2o.pd_op.batch_norm_.38.0")
|
||||
"p2o.pd_op.batch_norm_.39.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.29.0", "conv2d_39.w_0", "conv2d_39.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.40.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.39.0", "conv2d_40.w_0", "conv2d_40.w_0_bias")
|
||||
["Relu.30"] "p2o.pd_op.relu.30.0" = Relu ("p2o.pd_op.batch_norm_.40.0")
|
||||
"p2o.pd_op.batch_norm_.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.30.0", "conv2d_41.w_0", "conv2d_41.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.42.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.41.0", "conv2d_42.w_0", "conv2d_42.w_0_bias")
|
||||
["Relu.31"] "p2o.pd_op.relu.31.0" = Relu ("p2o.pd_op.batch_norm_.42.0")
|
||||
"p2o.pd_op.batch_norm_.43.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.31.0", "conv2d_43.w_0", "conv2d_43.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.44.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.43.0", "conv2d_44.w_0", "conv2d_44.w_0_bias")
|
||||
["Relu.32"] "p2o.pd_op.relu.32.0" = Relu ("p2o.pd_op.batch_norm_.44.0")
|
||||
"p2o.pd_op.batch_norm_.45.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.32.0", "conv2d_45.w_0", "conv2d_45.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.46.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.45.0", "conv2d_46.w_0", "conv2d_46.w_0_bias")
|
||||
["Relu.33"] "p2o.pd_op.relu.33.0" = Relu ("p2o.pd_op.batch_norm_.46.0")
|
||||
"p2o.pd_op.batch_norm_.47.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.33.0", "conv2d_47.w_0", "conv2d_47.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.48.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.47.0", "conv2d_48.w_0", "conv2d_48.w_0_bias")
|
||||
["Relu.34"] "p2o.pd_op.relu.34.0" = Relu ("p2o.pd_op.batch_norm_.48.0")
|
||||
["Concat.8"] "Concat.9" = Concat <axis: int = 1> ("p2o.pd_op.relu.28.0", "p2o.pd_op.relu.29.0", "p2o.pd_op.relu.30.0", "p2o.pd_op.relu.31.0", "p2o.pd_op.relu.32.0", "p2o.pd_op.relu.33.0", "p2o.pd_op.relu.34.0")
|
||||
"p2o.pd_op.batch_norm_.49.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Concat.9", "conv2d_49.w_0", "conv2d_49.w_0_bias")
|
||||
["Relu.35"] "p2o.pd_op.relu.35.0" = Relu ("p2o.pd_op.batch_norm_.49.0")
|
||||
"p2o.pd_op.batch_norm_.50.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.35.0", "conv2d_50.w_0", "conv2d_50.w_0_bias")
|
||||
["Relu.36"] "p2o.pd_op.relu.36.0" = Relu ("p2o.pd_op.batch_norm_.50.0")
|
||||
["Add.0"] "Add.1" = Add ("p2o.pd_op.relu.36.0", "p2o.pd_op.relu.28.0")
|
||||
"p2o.pd_op.batch_norm_.51.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.1", "conv2d_51.w_0", "conv2d_51.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.52.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.51.0", "conv2d_52.w_0", "conv2d_52.w_0_bias")
|
||||
["Relu.37"] "p2o.pd_op.relu.37.0" = Relu ("p2o.pd_op.batch_norm_.52.0")
|
||||
"p2o.pd_op.batch_norm_.53.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.37.0", "conv2d_53.w_0", "conv2d_53.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.54.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.53.0", "conv2d_54.w_0", "conv2d_54.w_0_bias")
|
||||
["Relu.38"] "p2o.pd_op.relu.38.0" = Relu ("p2o.pd_op.batch_norm_.54.0")
|
||||
"p2o.pd_op.batch_norm_.55.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.38.0", "conv2d_55.w_0", "conv2d_55.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.56.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.55.0", "conv2d_56.w_0", "conv2d_56.w_0_bias")
|
||||
["Relu.39"] "p2o.pd_op.relu.39.0" = Relu ("p2o.pd_op.batch_norm_.56.0")
|
||||
"p2o.pd_op.batch_norm_.57.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.39.0", "conv2d_57.w_0", "conv2d_57.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.58.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.57.0", "conv2d_58.w_0", "conv2d_58.w_0_bias")
|
||||
["Relu.40"] "p2o.pd_op.relu.40.0" = Relu ("p2o.pd_op.batch_norm_.58.0")
|
||||
"p2o.pd_op.batch_norm_.59.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.40.0", "conv2d_59.w_0", "conv2d_59.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.60.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.59.0", "conv2d_60.w_0", "conv2d_60.w_0_bias")
|
||||
["Relu.41"] "p2o.pd_op.relu.41.0" = Relu ("p2o.pd_op.batch_norm_.60.0")
|
||||
"p2o.pd_op.batch_norm_.61.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.41.0", "conv2d_61.w_0", "conv2d_61.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.62.0" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.61.0", "conv2d_62.w_0", "conv2d_62.w_0_bias")
|
||||
["Relu.42"] "p2o.pd_op.relu.42.0" = Relu ("p2o.pd_op.batch_norm_.62.0")
|
||||
["Concat.10"] "Concat.11" = Concat <axis: int = 1> ("Add.1", "p2o.pd_op.relu.37.0", "p2o.pd_op.relu.38.0", "p2o.pd_op.relu.39.0", "p2o.pd_op.relu.40.0", "p2o.pd_op.relu.41.0", "p2o.pd_op.relu.42.0")
|
||||
"p2o.pd_op.batch_norm_.63.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Concat.11", "conv2d_63.w_0", "conv2d_63.w_0_bias")
|
||||
["Relu.43"] "p2o.pd_op.relu.43.0" = Relu ("p2o.pd_op.batch_norm_.63.0")
|
||||
"p2o.pd_op.batch_norm_.64.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.43.0", "conv2d_64.w_0", "conv2d_64.w_0_bias")
|
||||
["Relu.44"] "p2o.pd_op.relu.44.0" = Relu ("p2o.pd_op.batch_norm_.64.0")
|
||||
["Add.2"] "Add.3" = Add ("p2o.pd_op.relu.44.0", "Add.1")
|
||||
"p2o.pd_op.batch_norm_.65.0" = Conv <dilations: ints = [1, 1], group: int = 1024, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.3", "conv2d_65.w_0", "conv2d_65.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.66.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.65.0", "conv2d_66.w_0", "conv2d_66.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.67.0" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.66.0", "conv2d_67.w_0", "conv2d_67.w_0_bias")
|
||||
["Relu.45"] "p2o.pd_op.relu.45.0" = Relu ("p2o.pd_op.batch_norm_.67.0")
|
||||
"p2o.pd_op.batch_norm_.68.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.45.0", "conv2d_68.w_0", "conv2d_68.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.69.0" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.68.0", "conv2d_69.w_0", "conv2d_69.w_0_bias")
|
||||
["Relu.46"] "p2o.pd_op.relu.46.0" = Relu ("p2o.pd_op.batch_norm_.69.0")
|
||||
"p2o.pd_op.batch_norm_.70.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.46.0", "conv2d_70.w_0", "conv2d_70.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.71.0" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.70.0", "conv2d_71.w_0", "conv2d_71.w_0_bias")
|
||||
["Relu.47"] "p2o.pd_op.relu.47.0" = Relu ("p2o.pd_op.batch_norm_.71.0")
|
||||
"p2o.pd_op.batch_norm_.72.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.47.0", "conv2d_72.w_0", "conv2d_72.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.73.0" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.72.0", "conv2d_73.w_0", "conv2d_73.w_0_bias")
|
||||
["Relu.48"] "p2o.pd_op.relu.48.0" = Relu ("p2o.pd_op.batch_norm_.73.0")
|
||||
"p2o.pd_op.batch_norm_.74.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.48.0", "conv2d_74.w_0", "conv2d_74.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.75.0" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.74.0", "conv2d_75.w_0", "conv2d_75.w_0_bias")
|
||||
["Relu.49"] "p2o.pd_op.relu.49.0" = Relu ("p2o.pd_op.batch_norm_.75.0")
|
||||
"p2o.pd_op.batch_norm_.76.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.49.0", "conv2d_76.w_0", "conv2d_76.w_0_bias")
|
||||
"p2o.pd_op.batch_norm_.77.0" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.76.0", "conv2d_77.w_0", "conv2d_77.w_0_bias")
|
||||
["Relu.50"] "p2o.pd_op.relu.50.0" = Relu ("p2o.pd_op.batch_norm_.77.0")
|
||||
["Concat.12"] "Concat.13" = Concat <axis: int = 1> ("p2o.pd_op.batch_norm_.65.0", "p2o.pd_op.relu.45.0", "p2o.pd_op.relu.46.0", "p2o.pd_op.relu.47.0", "p2o.pd_op.relu.48.0", "p2o.pd_op.relu.49.0", "p2o.pd_op.relu.50.0")
|
||||
"p2o.pd_op.batch_norm_.78.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Concat.13", "conv2d_78.w_0", "conv2d_78.w_0_bias")
|
||||
["Relu.51"] "p2o.pd_op.relu.51.0" = Relu ("p2o.pd_op.batch_norm_.78.0")
|
||||
"p2o.pd_op.batch_norm_.79.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.51.0", "conv2d_79.w_0", "conv2d_79.w_0_bias")
|
||||
["Relu.52"] "p2o.pd_op.relu.52.0" = Relu ("p2o.pd_op.batch_norm_.79.0")
|
||||
["Conv.80"] "p2o.pd_op.conv2d.53.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.52.0", "conv2d_92.w_0")
|
||||
["Conv.81"] "p2o.pd_op.conv2d.54.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.3", "conv2d_88.w_0")
|
||||
["Conv.82"] "p2o.pd_op.conv2d.55.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.20.0", "conv2d_84.w_0")
|
||||
["Conv.83"] "p2o.pd_op.conv2d.56.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.12.0", "conv2d_81.w_0")
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("p2o.pd_op.conv2d.53.0", "helper.constant.1", "helper.constant.0")
|
||||
["Add.4"] "Add.5" = Add ("p2o.pd_op.conv2d.54.0", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.5", "helper.constant.1", "helper.constant.0")
|
||||
["Add.6"] "Add.7" = Add ("p2o.pd_op.conv2d.55.0", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.7", "helper.constant.1", "helper.constant.0")
|
||||
["Add.8"] "Add.9" = Add ("p2o.pd_op.conv2d.56.0", "p2o.pd_op.nearest_interp.2.0")
|
||||
["Conv.84"] "p2o.pd_op.conv2d.57.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.53.0", "conv2d_93.w_0")
|
||||
["Conv.85"] "p2o.pd_op.conv2d.58.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.5", "conv2d_89.w_0")
|
||||
["Conv.86"] "p2o.pd_op.conv2d.59.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.7", "conv2d_85.w_0")
|
||||
["Conv.87"] "p2o.pd_op.conv2d.60.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.9", "conv2d_82.w_0")
|
||||
["Conv.88"] "p2o.pd_op.conv2d.61.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("p2o.pd_op.conv2d.60.0", "conv2d_86.w_0")
|
||||
["Add.10"] "Add.11" = Add ("p2o.pd_op.conv2d.59.0", "p2o.pd_op.conv2d.61.0")
|
||||
["Conv.89"] "p2o.pd_op.conv2d.62.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.11", "conv2d_90.w_0")
|
||||
["Add.12"] "Add.13" = Add ("p2o.pd_op.conv2d.58.0", "p2o.pd_op.conv2d.62.0")
|
||||
["Conv.90"] "p2o.pd_op.conv2d.63.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.13", "conv2d_94.w_0")
|
||||
["Add.14"] "Add.15" = Add ("p2o.pd_op.conv2d.57.0", "p2o.pd_op.conv2d.63.0")
|
||||
["Conv.91"] "p2o.pd_op.conv2d.64.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.60.0", "conv2d_83.w_0")
|
||||
["Conv.92"] "p2o.pd_op.conv2d.65.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.11", "conv2d_87.w_0")
|
||||
["Conv.93"] "p2o.pd_op.conv2d.66.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.13", "conv2d_91.w_0")
|
||||
["Conv.94"] "p2o.pd_op.conv2d.67.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.15", "conv2d_95.w_0")
|
||||
"Add.17" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.67.0", "conv2d_129.w_0", "p2o.pd_op.conv2d.68.0_bias")
|
||||
"Add.27" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.17", node_Conv_84_asym_w, node_Conv_84_asym_b)
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.27", node_Conv_87_asym_w, node_Conv_87_asym_b)
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.37", node_Conv_90_asym_w, node_Conv_90_asym_b)
|
||||
"p2o.pd_op.batch_norm_.80.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.47", "conv2d_130.w_0", "p2o.pd_op.conv2d.78.0_bias")
|
||||
["Relu.53"] "p2o.pd_op.relu.53.0" = Relu ("p2o.pd_op.batch_norm_.80.0")
|
||||
["Add.50"] "Add.51" = Add ("p2o.pd_op.conv2d.67.0", "p2o.pd_op.relu.53.0")
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.66.0", "conv2d_118.w_0", "p2o.pd_op.conv2d.79.0_bias")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.53", node_Conv_95_asym_w, node_Conv_95_asym_b)
|
||||
"Add.73" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.63", node_Conv_98_asym_w, node_Conv_98_asym_b)
|
||||
"Add.83" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.73", node_Conv_101_asym_w, node_Conv_101_asym_b)
|
||||
"p2o.pd_op.batch_norm_.81.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.83", "conv2d_119.w_0", "p2o.pd_op.conv2d.89.0_bias")
|
||||
["Relu.54"] "p2o.pd_op.relu.54.0" = Relu ("p2o.pd_op.batch_norm_.81.0")
|
||||
["Add.86"] "Add.87" = Add ("p2o.pd_op.conv2d.66.0", "p2o.pd_op.relu.54.0")
|
||||
"Add.89" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.65.0", "conv2d_107.w_0", "p2o.pd_op.conv2d.90.0_bias")
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.89", node_Conv_106_asym_w, node_Conv_106_asym_b)
|
||||
"Add.109" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.99", node_Conv_109_asym_w, node_Conv_109_asym_b)
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.109", node_Conv_112_asym_w, node_Conv_112_asym_b)
|
||||
"p2o.pd_op.batch_norm_.82.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.119", "conv2d_108.w_0", "p2o.pd_op.conv2d.100.0_bias")
|
||||
["Relu.55"] "p2o.pd_op.relu.55.0" = Relu ("p2o.pd_op.batch_norm_.82.0")
|
||||
["Add.122"] "Add.123" = Add ("p2o.pd_op.conv2d.65.0", "p2o.pd_op.relu.55.0")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.64.0", "conv2d_96.w_0", "p2o.pd_op.conv2d.101.0_bias")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.125", node_Conv_117_asym_w, node_Conv_117_asym_b)
|
||||
"Add.145" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.135", node_Conv_120_asym_w, node_Conv_120_asym_b)
|
||||
"Add.155" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.145", node_Conv_123_asym_w, node_Conv_123_asym_b)
|
||||
"p2o.pd_op.batch_norm_.83.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.155", "conv2d_97.w_0", "p2o.pd_op.conv2d.111.0_bias")
|
||||
["Relu.56"] "p2o.pd_op.relu.56.0" = Relu ("p2o.pd_op.batch_norm_.83.0")
|
||||
["Add.158"] "Add.159" = Add ("p2o.pd_op.conv2d.64.0", "p2o.pd_op.relu.56.0")
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.51", "helper.constant.1", "helper.constant.6")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.87", "helper.constant.1", "helper.constant.8")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.123", "helper.constant.1", "helper.constant.0")
|
||||
["Concat.14"] "Concat.15" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.159")
|
||||
"p2o.pd_op.batch_norm_.84.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.15", "conv2d_140.w_0", "conv2d_140.w_0_bias")
|
||||
["Relu.57"] "p2o.pd_op.relu.57.0" = Relu ("p2o.pd_op.batch_norm_.84.0")
|
||||
"p2o.pd_op.batch_norm_.85.0" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.57.0", "auto.cast.93", "ConvTranspose.1_bias")
|
||||
["Relu.58"] "p2o.pd_op.relu.58.0" = Relu ("p2o.pd_op.batch_norm_.85.0")
|
||||
"Add.163" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.58.0", "auto.cast.96", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] "p2o.pd_op.sigmoid.0.0" = Sigmoid ("Add.163")
|
||||
["Resize.6"] "p2o.pd_op.nearest_interp.6.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("p2o.pd_op.relu.58.0", "helper.constant.1", "helper.constant.0")
|
||||
["Concat.16"] "Concat.17" = Concat <axis: int = 1> ("p2o.pd_op.sigmoid.0.0", "p2o.pd_op.nearest_interp.6.0")
|
||||
"p2o.pd_op.batch_norm_.86.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.17", "conv2d_142.w_0", "conv2d_142.w_0_bias")
|
||||
["Relu.59"] "p2o.pd_op.relu.59.0" = Relu ("p2o.pd_op.batch_norm_.86.0")
|
||||
"Add.165" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.59.0", "conv2d_143.w_0", "p2o.pd_op.conv2d.114.0_bias")
|
||||
["Sigmoid.1"] "p2o.pd_op.sigmoid.1.0" = Sigmoid ("Add.165")
|
||||
["Add.166"] "Add.167" = Add ("p2o.pd_op.sigmoid.0.0", "p2o.pd_op.sigmoid.1.0")
|
||||
["Mul.0"] fetch_name_0 = Mul ("Add.167", "auto.cast.102")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
ConvTranspose.1_bias FLOAT[64] 4d9e09811298
|
||||
ConvTranspose.3_bias FLOAT[1] d7cf0756b564
|
||||
auto.cast.102 FLOAT[1] d99e58435243
|
||||
auto.cast.93 FLOAT[64,64,2,2] 446499e40216
|
||||
auto.cast.96 FLOAT[64,1,2,2] 6fa61becf97c
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_0.w_0 FLOAT[32,3,3,3] aed5723444c4
|
||||
conv2d_0.w_0_bias FLOAT[32] a404004a3f2d
|
||||
conv2d_1.w_0 FLOAT[16,32,2,2] 6355973c9252
|
||||
conv2d_1.w_0_bias FLOAT[16] db00ab5bf862
|
||||
conv2d_10.w_0 FLOAT[48,48,3,3] 51411ab738f8
|
||||
conv2d_10.w_0_bias FLOAT[48] 5b2cfae3b29a
|
||||
conv2d_107.w_0 FLOAT[32,64,1,1] 9f1dcbc35c35
|
||||
conv2d_108.w_0 FLOAT[64,32,1,1] f35808fcbd70
|
||||
conv2d_11.w_0 FLOAT[64,336,1,1] 83fde16b8fa0
|
||||
conv2d_11.w_0_bias FLOAT[64] c6174a10a753
|
||||
conv2d_118.w_0 FLOAT[32,64,1,1] 9f1dcbc35c35
|
||||
conv2d_119.w_0 FLOAT[64,32,1,1] eb87e44872d1
|
||||
conv2d_12.w_0 FLOAT[128,64,1,1] 5143914c85dc
|
||||
conv2d_12.w_0_bias FLOAT[128] 1a81f1411319
|
||||
conv2d_129.w_0 FLOAT[32,64,1,1] 9f1dcbc35c35
|
||||
conv2d_13.w_0 FLOAT[128,1,3,3] ae6f9b4b68af
|
||||
conv2d_13.w_0_bias FLOAT[128] 4e95a650212e
|
||||
conv2d_130.w_0 FLOAT[64,32,1,1] 1920115e5065
|
||||
conv2d_14.w_0 FLOAT[96,128,3,3] 1bbba7c1ce63
|
||||
conv2d_14.w_0_bias FLOAT[96] 51a8b2bbfe5f
|
||||
conv2d_140.w_0 FLOAT[64,256,3,3] a7695f15be7f
|
||||
conv2d_140.w_0_bias FLOAT[64] b2af6f525940
|
||||
conv2d_142.w_0 FLOAT[64,65,3,3] a31b42b48097
|
||||
conv2d_142.w_0_bias FLOAT[64] bdd4b593bf14
|
||||
conv2d_143.w_0 FLOAT[1,64,1,1] 84eabc2d820d
|
||||
conv2d_15.w_0 FLOAT[96,96,3,3] 69fd2f6e6a93
|
||||
conv2d_15.w_0_bias FLOAT[96] 2f717b0fd722
|
||||
conv2d_16.w_0 FLOAT[96,96,3,3] f732bcd2e98a
|
||||
conv2d_16.w_0_bias FLOAT[96] c6d310e2c8c4
|
||||
conv2d_17.w_0 FLOAT[96,96,3,3] 29b1c22f58f5
|
||||
conv2d_17.w_0_bias FLOAT[96] 97fe21a0d6e5
|
||||
conv2d_18.w_0 FLOAT[96,96,3,3] dd647ff9da4e
|
||||
conv2d_18.w_0_bias FLOAT[96] 6da0f2396ba0
|
||||
conv2d_19.w_0 FLOAT[96,96,3,3] 2a226b6562ff
|
||||
conv2d_19.w_0_bias FLOAT[96] afe239509ede
|
||||
conv2d_2.w_0 FLOAT[32,16,2,2] 903f80a9fc40
|
||||
conv2d_2.w_0_bias FLOAT[32] 402ab8f2e445
|
||||
conv2d_20.w_0 FLOAT[256,704,1,1] 8a6115c40624
|
||||
conv2d_20.w_0_bias FLOAT[256] 329ac342b86c
|
||||
conv2d_21.w_0 FLOAT[512,256,1,1] 895e6ce805d0
|
||||
conv2d_21.w_0_bias FLOAT[512] f014d6e30f9f
|
||||
conv2d_22.w_0 FLOAT[512,1,3,3] 122dd5643a79
|
||||
conv2d_22.w_0_bias FLOAT[512] 65118505cbb5
|
||||
conv2d_23.w_0 FLOAT[192,512,1,1] a786e504252f
|
||||
conv2d_23.w_0_bias FLOAT[192] 43bb2d7f6ea2
|
||||
conv2d_24.w_0 FLOAT[192,1,5,5] 48edfb95d59e
|
||||
conv2d_24.w_0_bias FLOAT[192] 16563dcb5fe5
|
||||
conv2d_25.w_0 FLOAT[192,192,1,1] d142c7c70596
|
||||
conv2d_25.w_0_bias FLOAT[192] 69debf8dfe33
|
||||
conv2d_26.w_0 FLOAT[192,1,5,5] 36dd82de8800
|
||||
conv2d_26.w_0_bias FLOAT[192] e5d093b7afb1
|
||||
conv2d_27.w_0 FLOAT[192,192,1,1] b137a4bcaab2
|
||||
conv2d_27.w_0_bias FLOAT[192] b585dc971a34
|
||||
conv2d_28.w_0 FLOAT[192,1,5,5] 14c15b82cb29
|
||||
conv2d_28.w_0_bias FLOAT[192] 4f74bd26f9f3
|
||||
conv2d_29.w_0 FLOAT[192,192,1,1] e25f2419665e
|
||||
conv2d_29.w_0_bias FLOAT[192] 3119aa8fd66c
|
||||
conv2d_3.w_0 FLOAT[32,64,3,3] 4933a30975d2
|
||||
conv2d_3.w_0_bias FLOAT[32] 73657ab565e9
|
||||
conv2d_30.w_0 FLOAT[192,1,5,5] 69a422cfaeb1
|
||||
conv2d_30.w_0_bias FLOAT[192] a1e447196d01
|
||||
conv2d_31.w_0 FLOAT[192,192,1,1] b144357846d3
|
||||
conv2d_31.w_0_bias FLOAT[192] f4aa4639f652
|
||||
conv2d_32.w_0 FLOAT[192,1,5,5] 1debb74f8bac
|
||||
conv2d_32.w_0_bias FLOAT[192] 83d9e916e680
|
||||
conv2d_33.w_0 FLOAT[192,192,1,1] ccdace993034
|
||||
conv2d_33.w_0_bias FLOAT[192] 641de90dc092
|
||||
conv2d_34.w_0 FLOAT[192,1,5,5] 4dc84372652b
|
||||
conv2d_34.w_0_bias FLOAT[192] e83e1469ee5b
|
||||
conv2d_35.w_0 FLOAT[512,1664,1,1] 2e1301c127b8
|
||||
conv2d_35.w_0_bias FLOAT[512] 2ee5703de97b
|
||||
conv2d_36.w_0 FLOAT[1024,512,1,1] 8f1b0de9a3b4
|
||||
conv2d_36.w_0_bias FLOAT[1024] 7a55a55e87da
|
||||
conv2d_37.w_0 FLOAT[192,1024,1,1] 00412b9131e0
|
||||
conv2d_37.w_0_bias FLOAT[192] 9689e7947a56
|
||||
conv2d_38.w_0 FLOAT[192,1,5,5] 19f1b11f6b8c
|
||||
conv2d_38.w_0_bias FLOAT[192] 0deeb692417d
|
||||
conv2d_39.w_0 FLOAT[192,192,1,1] 92026b573cfb
|
||||
conv2d_39.w_0_bias FLOAT[192] 590a0207459f
|
||||
conv2d_4.w_0 FLOAT[48,32,1,1] 3e8a7a325a2e
|
||||
conv2d_4.w_0_bias FLOAT[48] dd13b9696a60
|
||||
conv2d_40.w_0 FLOAT[192,1,5,5] cea2f56ef92e
|
||||
conv2d_40.w_0_bias FLOAT[192] 394efd933dbe
|
||||
conv2d_41.w_0 FLOAT[192,192,1,1] 083661a0266b
|
||||
conv2d_41.w_0_bias FLOAT[192] 082b3c2f5aca
|
||||
conv2d_42.w_0 FLOAT[192,1,5,5] 1915f99f1753
|
||||
conv2d_42.w_0_bias FLOAT[192] f02edaf2fa20
|
||||
conv2d_43.w_0 FLOAT[192,192,1,1] 2f561e64f6e8
|
||||
conv2d_43.w_0_bias FLOAT[192] e658c6a83708
|
||||
conv2d_44.w_0 FLOAT[192,1,5,5] 49d58ef2e1cb
|
||||
conv2d_44.w_0_bias FLOAT[192] 20b51dfab43e
|
||||
conv2d_45.w_0 FLOAT[192,192,1,1] e9f080846f2f
|
||||
conv2d_45.w_0_bias FLOAT[192] 5536be8a931c
|
||||
conv2d_46.w_0 FLOAT[192,1,5,5] 493918a100cd
|
||||
conv2d_46.w_0_bias FLOAT[192] 9950b66a4d4e
|
||||
conv2d_47.w_0 FLOAT[192,192,1,1] 701d098688e2
|
||||
conv2d_47.w_0_bias FLOAT[192] 76c58042b727
|
||||
conv2d_48.w_0 FLOAT[192,1,5,5] a48e880bce28
|
||||
conv2d_48.w_0_bias FLOAT[192] e3cfecc74be6
|
||||
conv2d_49.w_0 FLOAT[512,2176,1,1] 76108a3c4cf9
|
||||
conv2d_49.w_0_bias FLOAT[512] 3b55275475c3
|
||||
conv2d_5.w_0 FLOAT[48,48,3,3] 09008d53042f
|
||||
conv2d_5.w_0_bias FLOAT[48] 73192bdb6f5c
|
||||
conv2d_50.w_0 FLOAT[1024,512,1,1] 9ad2544c0e16
|
||||
conv2d_50.w_0_bias FLOAT[1024] 21eef1b61ac5
|
||||
conv2d_51.w_0 FLOAT[192,1024,1,1] a97e80d30eaf
|
||||
conv2d_51.w_0_bias FLOAT[192] 3402dbc6bd14
|
||||
conv2d_52.w_0 FLOAT[192,1,5,5] e9f3b5d3046b
|
||||
conv2d_52.w_0_bias FLOAT[192] 277e2bd5f1ed
|
||||
conv2d_53.w_0 FLOAT[192,192,1,1] 37629bb1cc32
|
||||
conv2d_53.w_0_bias FLOAT[192] a38560394397
|
||||
conv2d_54.w_0 FLOAT[192,1,5,5] 05fb4d6b334c
|
||||
conv2d_54.w_0_bias FLOAT[192] f3e5bf9d19e7
|
||||
conv2d_55.w_0 FLOAT[192,192,1,1] d6bf8a539a0b
|
||||
conv2d_55.w_0_bias FLOAT[192] a7f5411d539d
|
||||
conv2d_56.w_0 FLOAT[192,1,5,5] facfc96767e7
|
||||
conv2d_56.w_0_bias FLOAT[192] a04889ef0afd
|
||||
conv2d_57.w_0 FLOAT[192,192,1,1] 894777b46366
|
||||
conv2d_57.w_0_bias FLOAT[192] f0c285f1eae6
|
||||
conv2d_58.w_0 FLOAT[192,1,5,5] d5e48fbf3ee2
|
||||
conv2d_58.w_0_bias FLOAT[192] 9be347e95bb9
|
||||
conv2d_59.w_0 FLOAT[192,192,1,1] 700d4c63ea85
|
||||
conv2d_59.w_0_bias FLOAT[192] d72df89f574f
|
||||
conv2d_6.w_0 FLOAT[48,48,3,3] 308c19bfcf5e
|
||||
conv2d_6.w_0_bias FLOAT[48] 635143bd4452
|
||||
conv2d_60.w_0 FLOAT[192,1,5,5] a741705e9788
|
||||
conv2d_60.w_0_bias FLOAT[192] 7ebde9240317
|
||||
conv2d_61.w_0 FLOAT[192,192,1,1] 6b46473b3149
|
||||
conv2d_61.w_0_bias FLOAT[192] 736f11c9d244
|
||||
conv2d_62.w_0 FLOAT[192,1,5,5] c5b6bc42b776
|
||||
conv2d_62.w_0_bias FLOAT[192] 4cc54272c636
|
||||
conv2d_63.w_0 FLOAT[512,2176,1,1] 5608efb9c257
|
||||
conv2d_63.w_0_bias FLOAT[512] 47cbb56a497a
|
||||
conv2d_64.w_0 FLOAT[1024,512,1,1] 6beb7705f174
|
||||
conv2d_64.w_0_bias FLOAT[1024] 952f3e5be0c1
|
||||
conv2d_65.w_0 FLOAT[1024,1,3,3] 543854fbe506
|
||||
conv2d_65.w_0_bias FLOAT[1024] da89e73edd61
|
||||
conv2d_66.w_0 FLOAT[384,1024,1,1] ab336657501a
|
||||
conv2d_66.w_0_bias FLOAT[384] 80a676c7aab9
|
||||
conv2d_67.w_0 FLOAT[384,1,5,5] 3474a1022fdd
|
||||
conv2d_67.w_0_bias FLOAT[384] 7ee0f9d35974
|
||||
conv2d_68.w_0 FLOAT[384,384,1,1] e58fce181f95
|
||||
conv2d_68.w_0_bias FLOAT[384] 362bbfa580cd
|
||||
conv2d_69.w_0 FLOAT[384,1,5,5] 27dda3b3d0d7
|
||||
conv2d_69.w_0_bias FLOAT[384] f6a00eaaf5e8
|
||||
conv2d_7.w_0 FLOAT[48,48,3,3] adc1b4529bcc
|
||||
conv2d_7.w_0_bias FLOAT[48] a307c3d1cb1f
|
||||
conv2d_70.w_0 FLOAT[384,384,1,1] df4e87969670
|
||||
conv2d_70.w_0_bias FLOAT[384] 1bd79ee4c9e6
|
||||
conv2d_71.w_0 FLOAT[384,1,5,5] 1a44da8e03a7
|
||||
conv2d_71.w_0_bias FLOAT[384] 361d8bca6885
|
||||
conv2d_72.w_0 FLOAT[384,384,1,1] a6af4880b6db
|
||||
conv2d_72.w_0_bias FLOAT[384] 9ef132ad1dd0
|
||||
conv2d_73.w_0 FLOAT[384,1,5,5] 0feedf067bd6
|
||||
conv2d_73.w_0_bias FLOAT[384] ff0cdd3fe0b2
|
||||
conv2d_74.w_0 FLOAT[384,384,1,1] 6c644edd904d
|
||||
conv2d_74.w_0_bias FLOAT[384] 1f54b47144f7
|
||||
conv2d_75.w_0 FLOAT[384,1,5,5] 55c105e10e08
|
||||
conv2d_75.w_0_bias FLOAT[384] 1d631fb327b4
|
||||
conv2d_76.w_0 FLOAT[384,384,1,1] 1a1fc3ccdd2c
|
||||
conv2d_76.w_0_bias FLOAT[384] 90bc957eee42
|
||||
conv2d_77.w_0 FLOAT[384,1,5,5] 84e9bd430b83
|
||||
conv2d_77.w_0_bias FLOAT[384] 440d8a3dcecd
|
||||
conv2d_78.w_0 FLOAT[1024,3328,1,1] 113ea9eda44a
|
||||
conv2d_78.w_0_bias FLOAT[1024] 8c39729cf00c
|
||||
conv2d_79.w_0 FLOAT[2048,1024,1,1] 78b6983c4973
|
||||
conv2d_79.w_0_bias FLOAT[2048] dfd4aff6cd80
|
||||
conv2d_8.w_0 FLOAT[48,48,3,3] 6fcce5235f78
|
||||
conv2d_8.w_0_bias FLOAT[48] b8b149cb92e1
|
||||
conv2d_81.w_0 FLOAT[256,128,1,1] 5294b218dde6
|
||||
conv2d_82.w_0 FLOAT[64,256,9,9] 860a2c2f44ed
|
||||
conv2d_83.w_0 FLOAT[64,64,9,9] 073941384d9c
|
||||
conv2d_84.w_0 FLOAT[256,512,1,1] 355cf6d6aaf2
|
||||
conv2d_85.w_0 FLOAT[64,256,9,9] 6ab5aa7a3aaa
|
||||
conv2d_86.w_0 FLOAT[64,64,3,3] 7ec046584c86
|
||||
conv2d_87.w_0 FLOAT[64,64,9,9] 0e915f8b2a44
|
||||
conv2d_88.w_0 FLOAT[256,1024,1,1] 922be789a59b
|
||||
conv2d_89.w_0 FLOAT[64,256,9,9] 41cdf13c5867
|
||||
conv2d_9.w_0 FLOAT[48,48,3,3] ba744539217a
|
||||
conv2d_9.w_0_bias FLOAT[48] 5e225c1cd595
|
||||
conv2d_90.w_0 FLOAT[64,64,3,3] 8db0d95502bb
|
||||
conv2d_91.w_0 FLOAT[64,64,9,9] 6d6102e52c48
|
||||
conv2d_92.w_0 FLOAT[256,2048,1,1] fd9fe5ec3288
|
||||
conv2d_93.w_0 FLOAT[64,256,9,9] d6c8040de5a2
|
||||
conv2d_94.w_0 FLOAT[64,64,3,3] 7c6b6a1a0bca
|
||||
conv2d_95.w_0 FLOAT[64,64,9,9] 6db06f7cf7c6
|
||||
conv2d_96.w_0 FLOAT[32,64,1,1] 9f1dcbc35c35
|
||||
conv2d_97.w_0 FLOAT[64,32,1,1] b64d8ab1f062
|
||||
helper.constant.0 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.1 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.6 FLOAT[4] cf5451a623be
|
||||
helper.constant.8 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
node_Conv_101_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_101_asym_w FLOAT[32,32,3,3] 1c0273095382
|
||||
node_Conv_106_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_106_asym_w FLOAT[32,32,7,7] ba0ee4b797b9
|
||||
node_Conv_109_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_109_asym_w FLOAT[32,32,5,5] f627ca4c2c32
|
||||
node_Conv_112_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_112_asym_w FLOAT[32,32,3,3] 1c0273095382
|
||||
node_Conv_117_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_117_asym_w FLOAT[32,32,7,7] a5e56dbbfbc8
|
||||
node_Conv_120_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_120_asym_w FLOAT[32,32,5,5] f627ca4c2c32
|
||||
node_Conv_123_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_123_asym_w FLOAT[32,32,3,3] 1c0273095382
|
||||
node_Conv_84_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_84_asym_w FLOAT[32,32,7,7] ba0ee4b797b9
|
||||
node_Conv_87_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_87_asym_w FLOAT[32,32,5,5] f627ca4c2c32
|
||||
node_Conv_90_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_90_asym_w FLOAT[32,32,3,3] 1c0273095382
|
||||
node_Conv_95_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_95_asym_w FLOAT[32,32,7,7] ba0ee4b797b9
|
||||
node_Conv_98_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_98_asym_w FLOAT[32,32,5,5] f627ca4c2c32
|
||||
p2o.pd_op.conv2d.100.0_bias FLOAT[64] 936316c173ad
|
||||
p2o.pd_op.conv2d.101.0_bias FLOAT[32] 38723a2e5e8a
|
||||
p2o.pd_op.conv2d.111.0_bias FLOAT[64] f0eba8610837
|
||||
p2o.pd_op.conv2d.114.0_bias FLOAT[1] d894932b695a
|
||||
p2o.pd_op.conv2d.68.0_bias FLOAT[32] 38723a2e5e8a
|
||||
p2o.pd_op.conv2d.78.0_bias FLOAT[64] 78bb18b3d82f
|
||||
p2o.pd_op.conv2d.79.0_bias FLOAT[32] 38723a2e5e8a
|
||||
p2o.pd_op.conv2d.89.0_bias FLOAT[64] 4761b58748c8
|
||||
p2o.pd_op.conv2d.90.0_bias FLOAT[32] 38723a2e5e8a
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,566 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,64,unk__0,unk__1] "Add.1"
|
||||
float[batch,128,1,1] "Add.101"
|
||||
float[batch,512,1,1] "Add.103"
|
||||
float[batch,1024,unk__50,unk__51] "Add.105"
|
||||
float[batch,512,unk__50,unk__51] "Add.109"
|
||||
float[batch,128,unk__8,unk__9] "Add.11"
|
||||
float[batch,512,unk__50,unk__51] "Add.111"
|
||||
float[batch,512,unk__50,unk__51] "Add.113"
|
||||
float[batch,1024,unk__50,unk__51] "Add.115"
|
||||
float[batch,512,unk__50,unk__51] "Add.119"
|
||||
float[batch,512,unk__50,unk__51] "Add.121"
|
||||
float[batch,512,unk__88,unk__89] "Add.123"
|
||||
float[batch,1024,unk__88,unk__89] "Add.125"
|
||||
float[batch,896,unk__88,unk__89] "Add.129"
|
||||
float[batch,32,1,1] "Add.13"
|
||||
float[batch,896,unk__88,unk__89] "Add.131"
|
||||
float[batch,224,1,1] "Add.133"
|
||||
float[batch,896,1,1] "Add.135"
|
||||
float[batch,1792,unk__88,unk__89] "Add.137"
|
||||
float[batch,896,unk__88,unk__89] "Add.141"
|
||||
float[batch,896,unk__88,unk__89] "Add.143"
|
||||
float[batch,896,unk__88,unk__89] "Add.145"
|
||||
float[batch,1792,unk__88,unk__89] "Add.147"
|
||||
float[batch,128,1,1] "Add.15"
|
||||
float[batch,896,unk__88,unk__89] "Add.151"
|
||||
float[batch,896,unk__88,unk__89] "Add.153"
|
||||
float[batch,256,unk__50,unk__51] "Add.155"
|
||||
float[batch,256,unk__28,unk__29] "Add.157"
|
||||
float[batch,256,unk__8,unk__9] "Add.159"
|
||||
float[batch,256,unk__88,unk__89] "Add.161"
|
||||
float[batch,64,unk__88,unk__89] "Add.163"
|
||||
float[batch,256,unk__50,unk__51] "Add.165"
|
||||
float[batch,64,unk__50,unk__51] "Add.167"
|
||||
float[batch,256,unk__28,unk__29] "Add.169"
|
||||
float[batch,256,unk__8,unk__9] "Add.17"
|
||||
float[batch,64,unk__28,unk__29] "Add.171"
|
||||
float[batch,256,unk__8,unk__9] "Add.173"
|
||||
float[batch,64,unk__8,unk__9] "Add.175"
|
||||
float[batch,64,unk__28,unk__29] "Add.177"
|
||||
float[batch,64,unk__50,unk__51] "Add.179"
|
||||
float[batch,64,unk__88,unk__89] "Add.181"
|
||||
float[batch,64,unk__8,unk__9] "Add.183"
|
||||
float[batch,64,unk__8,unk__9] "Add.185"
|
||||
float[batch,64,unk__28,unk__29] "Add.187"
|
||||
float[batch,64,unk__28,unk__29] "Add.189"
|
||||
float[batch,64,unk__50,unk__51] "Add.191"
|
||||
float[batch,64,unk__50,unk__51] "Add.193"
|
||||
float[batch,64,unk__88,unk__89] "Add.195"
|
||||
float[batch,64,unk__88,unk__89] "Add.197"
|
||||
float[batch,32,unk__88,unk__89] "Add.199"
|
||||
float[batch,32,unk__88,unk__89] "Add.209"
|
||||
float[batch,128,unk__8,unk__9] "Add.21"
|
||||
float[batch,32,unk__88,unk__89] "Add.219"
|
||||
float[batch,32,unk__88,unk__89] "Add.229"
|
||||
float[batch,128,unk__8,unk__9] "Add.23"
|
||||
float[batch,64,unk__88,unk__89] "Add.233"
|
||||
float[batch,32,unk__50,unk__51] "Add.235"
|
||||
float[batch,32,unk__50,unk__51] "Add.245"
|
||||
float[batch,128,unk__8,unk__9] "Add.25"
|
||||
float[batch,32,unk__50,unk__51] "Add.255"
|
||||
float[batch,32,unk__50,unk__51] "Add.265"
|
||||
float[batch,64,unk__50,unk__51] "Add.269"
|
||||
float[batch,256,unk__8,unk__9] "Add.27"
|
||||
float[batch,32,unk__28,unk__29] "Add.271"
|
||||
float[batch,32,unk__28,unk__29] "Add.281"
|
||||
float[batch,32,unk__28,unk__29] "Add.291"
|
||||
float[batch,32,unk__0,unk__1] "Add.3"
|
||||
float[batch,32,unk__28,unk__29] "Add.301"
|
||||
float[batch,64,unk__28,unk__29] "Add.305"
|
||||
float[batch,32,unk__8,unk__9] "Add.307"
|
||||
float[batch,128,unk__8,unk__9] "Add.31"
|
||||
float[batch,32,unk__8,unk__9] "Add.317"
|
||||
float[batch,32,unk__8,unk__9] "Add.327"
|
||||
float[batch,128,unk__8,unk__9] "Add.33"
|
||||
float[batch,32,unk__8,unk__9] "Add.337"
|
||||
float[batch,64,unk__8,unk__9] "Add.341"
|
||||
float[batch,64,unk__8,unk__9] "Add.343"
|
||||
float[batch,64,unk__0,unk__1] "Add.345"
|
||||
float[batch,1,height,width] "Add.347"
|
||||
float[batch,128,unk__28,unk__29] "Add.35"
|
||||
float[batch,256,unk__28,unk__29] "Add.37"
|
||||
float[batch,256,unk__28,unk__29] "Add.41"
|
||||
float[batch,256,unk__28,unk__29] "Add.43"
|
||||
float[batch,64,1,1] "Add.45"
|
||||
float[batch,256,1,1] "Add.47"
|
||||
float[batch,512,unk__28,unk__29] "Add.49"
|
||||
float[batch,64,unk__0,unk__1] "Add.5"
|
||||
float[batch,256,unk__28,unk__29] "Add.53"
|
||||
float[batch,256,unk__28,unk__29] "Add.55"
|
||||
float[batch,256,unk__28,unk__29] "Add.57"
|
||||
float[batch,512,unk__28,unk__29] "Add.59"
|
||||
float[batch,256,unk__28,unk__29] "Add.63"
|
||||
float[batch,256,unk__28,unk__29] "Add.65"
|
||||
float[batch,256,unk__50,unk__51] "Add.67"
|
||||
float[batch,512,unk__50,unk__51] "Add.69"
|
||||
float[batch,64,unk__8,unk__9] "Add.7"
|
||||
float[batch,512,unk__50,unk__51] "Add.73"
|
||||
float[batch,512,unk__50,unk__51] "Add.75"
|
||||
float[batch,128,1,1] "Add.77"
|
||||
float[batch,512,1,1] "Add.79"
|
||||
float[batch,1024,unk__50,unk__51] "Add.81"
|
||||
float[batch,512,unk__50,unk__51] "Add.85"
|
||||
float[batch,512,unk__50,unk__51] "Add.87"
|
||||
float[batch,512,unk__50,unk__51] "Add.89"
|
||||
float[batch,128,unk__8,unk__9] "Add.9"
|
||||
float[batch,1024,unk__50,unk__51] "Add.91"
|
||||
float[batch,512,unk__50,unk__51] "Add.95"
|
||||
float[batch,512,unk__50,unk__51] "Add.97"
|
||||
float[batch,512,unk__50,unk__51] "Add.99"
|
||||
float[batch,128,unk__0,unk__1] "Concat.1"
|
||||
float[batch,256,unk__8,unk__9] "Concat.3"
|
||||
float[batch,128,unk__8,unk__9] "Mul.1"
|
||||
float[batch,256,unk__28,unk__29] "Mul.12"
|
||||
float[batch,512,unk__50,unk__51] "Mul.23"
|
||||
float[batch,512,unk__50,unk__51] "Mul.31"
|
||||
float[batch,896,unk__88,unk__89] "Mul.42"
|
||||
float[batch,128,1,1] "ReduceMean.1"
|
||||
float[batch,256,1,1] "ReduceMean.3"
|
||||
float[batch,512,1,1] "ReduceMean.5"
|
||||
float[batch,512,1,1] "ReduceMean.7"
|
||||
float[batch,896,1,1] "ReduceMean.9"
|
||||
float[batch,64,unk__88,unk__89] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,64,unk__50,unk__51] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.batch_norm_.3.0"
|
||||
float[batch,256,unk__88,unk__89] "p2o.pd_op.conv2d.41.0"
|
||||
float[batch,256,unk__50,unk__51] "p2o.pd_op.conv2d.42.0"
|
||||
float[batch,256,unk__28,unk__29] "p2o.pd_op.conv2d.43.0"
|
||||
float[batch,256,unk__8,unk__9] "p2o.pd_op.conv2d.44.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.conv2d.49.0"
|
||||
float[batch,64,unk__50,unk__51] "p2o.pd_op.conv2d.50.0"
|
||||
float[batch,64,unk__88,unk__89] "p2o.pd_op.conv2d.51.0"
|
||||
float[batch,256,unk__8,unk__9] "p2o.pd_op.gelu.0.0"
|
||||
float[batch,256,unk__8,unk__9] "p2o.pd_op.gelu.1.0"
|
||||
float[batch,1024,unk__88,unk__89] "p2o.pd_op.gelu.10.0"
|
||||
float[batch,1792,unk__88,unk__89] "p2o.pd_op.gelu.11.0"
|
||||
float[batch,1792,unk__88,unk__89] "p2o.pd_op.gelu.12.0"
|
||||
float[batch,256,unk__28,unk__29] "p2o.pd_op.gelu.2.0"
|
||||
float[batch,512,unk__28,unk__29] "p2o.pd_op.gelu.3.0"
|
||||
float[batch,512,unk__28,unk__29] "p2o.pd_op.gelu.4.0"
|
||||
float[batch,512,unk__50,unk__51] "p2o.pd_op.gelu.5.0"
|
||||
float[batch,1024,unk__50,unk__51] "p2o.pd_op.gelu.6.0"
|
||||
float[batch,1024,unk__50,unk__51] "p2o.pd_op.gelu.7.0"
|
||||
float[batch,1024,unk__50,unk__51] "p2o.pd_op.gelu.8.0"
|
||||
float[batch,1024,unk__50,unk__51] "p2o.pd_op.gelu.9.0"
|
||||
float[batch,128,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,256,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,512,1,1] "p2o.pd_op.hardsigmoid.2.0"
|
||||
float[batch,512,1,1] "p2o.pd_op.hardsigmoid.3.0"
|
||||
float[batch,896,1,1] "p2o.pd_op.hardsigmoid.4.0"
|
||||
float[batch,256,unk__50,unk__51] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,256,unk__28,unk__29] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,256,unk__8,unk__9] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,64,unk__0,unk__1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,64,unk__0,unk__1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,64,unk__88,unk__89] "p2o.pd_op.relu.10.0"
|
||||
float[batch,64,unk__50,unk__51] "p2o.pd_op.relu.11.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.relu.12.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.relu.13.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.relu.14.0"
|
||||
float[batch,64,unk__0,unk__1] "p2o.pd_op.relu.15.0"
|
||||
float[batch,64,unk__0,unk__1] "p2o.pd_op.relu.2.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.relu.3.0"
|
||||
float[batch,128,unk__8,unk__9] "p2o.pd_op.relu.4.0"
|
||||
float[batch,32,1,1] "p2o.pd_op.relu.5.0"
|
||||
float[batch,64,1,1] "p2o.pd_op.relu.6.0"
|
||||
float[batch,128,1,1] "p2o.pd_op.relu.7.0"
|
||||
float[batch,128,1,1] "p2o.pd_op.relu.8.0"
|
||||
float[batch,224,1,1] "p2o.pd_op.relu.9.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"Add.1" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_171.w_0", "p2o.pd_op.conv2d.0.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.1")
|
||||
"Add.3" = Conv <auto_pad: string = "SAME_UPPER", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_172.w_0", "p2o.pd_op.conv2d.1.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.3")
|
||||
"Add.5" = Conv <auto_pad: string = "SAME_UPPER", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_173.w_0", "p2o.pd_op.conv2d.2.0_bias")
|
||||
["Relu.2"] "p2o.pd_op.relu.2.0" = Relu ("Add.5")
|
||||
["MaxPool.0"] "p2o.pd_op.pool2d.0.0" = MaxPool <auto_pad: string = "SAME_UPPER", ceil_mode: int = 0, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.pool2d.0.0", "p2o.pd_op.relu.2.0")
|
||||
"Add.7" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Concat.1", "conv2d_174.w_0", "p2o.pd_op.conv2d.3.0_bias")
|
||||
["Relu.3"] "p2o.pd_op.relu.3.0" = Relu ("Add.7")
|
||||
"Add.9" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.3.0", "conv2d_175.w_0", "p2o.pd_op.conv2d.4.0_bias")
|
||||
["Relu.4"] "p2o.pd_op.relu.4.0" = Relu ("Add.9")
|
||||
"Add.11" = Conv <dilations: ints = [1, 1], group: int = 128, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.4.0", "conv2d_177.w_0", "p2o.pd_op.depthwise_conv2d.0.0_bias")
|
||||
["ReduceMean.0"] "ReduceMean.1" = ReduceMean <keepdims: int = 1> ("Add.11", _v_908)
|
||||
"Add.13" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.1", "conv2d_7.w_0", "p2o.pd_op.conv2d.5.0_bias")
|
||||
["Relu.5"] "p2o.pd_op.relu.5.0" = Relu ("Add.13")
|
||||
"Add.15" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.5.0", "conv2d_8.w_0", "p2o.pd_op.conv2d.6.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.15")
|
||||
["Mul.0"] "Mul.1" = Mul ("Add.11", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.17" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.1", "conv2d_178.w_0", "p2o.pd_op.conv2d.7.0_bias")
|
||||
"p2o.pd_op.gelu.0.0" = Gelu <approximate: string = "none"> ("Add.17")
|
||||
"Add.21" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.0.0", "conv2d_179.w_0", "p2o.pd_op.conv2d.8.0_bias")
|
||||
["Add.22"] "Add.23" = Add ("Mul.1", "Add.21")
|
||||
"Add.25" = Conv <dilations: ints = [1, 1], group: int = 128, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.23", "conv2d_181.w_0", "p2o.pd_op.depthwise_conv2d.1.0_bias")
|
||||
"Add.27" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.25", "conv2d_182.w_0", "p2o.pd_op.conv2d.9.0_bias")
|
||||
"p2o.pd_op.gelu.1.0" = Gelu <approximate: string = "none"> ("Add.27")
|
||||
"Add.31" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.1.0", "conv2d_183.w_0", "p2o.pd_op.conv2d.10.0_bias")
|
||||
["Add.32"] "Add.33" = Add ("Add.25", "Add.31")
|
||||
"Add.35" = Conv <dilations: ints = [1, 1], group: int = 128, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.33", "conv2d_184.w_0", "p2o.pd_op.depthwise_conv2d.2.0_bias")
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.35", "conv2d_185.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
"p2o.pd_op.gelu.2.0" = Gelu <approximate: string = "none"> ("Add.37")
|
||||
"Add.41" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.2.0", "conv2d_186.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
"Add.43" = Conv <dilations: ints = [1, 1], group: int = 256, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.41", "conv2d_188.w_0", "p2o.pd_op.depthwise_conv2d.3.0_bias")
|
||||
["ReduceMean.2"] "ReduceMean.3" = ReduceMean <keepdims: int = 1> ("Add.43", _v_908)
|
||||
"Add.45" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.3", "conv2d_20.w_0", "p2o.pd_op.conv2d.13.0_bias")
|
||||
["Relu.6"] "p2o.pd_op.relu.6.0" = Relu ("Add.45")
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.6.0", "conv2d_21.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.47")
|
||||
["Mul.11"] "Mul.12" = Mul ("Add.43", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.49" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.12", "conv2d_189.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
"p2o.pd_op.gelu.3.0" = Gelu <approximate: string = "none"> ("Add.49")
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.3.0", "conv2d_190.w_0", "p2o.pd_op.conv2d.16.0_bias")
|
||||
["Add.54"] "Add.55" = Add ("Mul.12", "Add.53")
|
||||
"Add.57" = Conv <dilations: ints = [1, 1], group: int = 256, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.55", "conv2d_192.w_0", "p2o.pd_op.depthwise_conv2d.4.0_bias")
|
||||
"Add.59" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.57", "conv2d_193.w_0", "p2o.pd_op.conv2d.17.0_bias")
|
||||
"p2o.pd_op.gelu.4.0" = Gelu <approximate: string = "none"> ("Add.59")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.4.0", "conv2d_194.w_0", "p2o.pd_op.conv2d.18.0_bias")
|
||||
["Add.64"] "Add.65" = Add ("Add.57", "Add.63")
|
||||
"Add.67" = Conv <dilations: ints = [1, 1], group: int = 256, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.65", "conv2d_195.w_0", "p2o.pd_op.depthwise_conv2d.5.0_bias")
|
||||
"Add.69" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.67", "conv2d_196.w_0", "p2o.pd_op.conv2d.19.0_bias")
|
||||
"p2o.pd_op.gelu.5.0" = Gelu <approximate: string = "none"> ("Add.69")
|
||||
"Add.73" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.5.0", "conv2d_197.w_0", "p2o.pd_op.conv2d.20.0_bias")
|
||||
"Add.75" = Conv <dilations: ints = [1, 1], group: int = 512, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.73", "conv2d_199.w_0", "p2o.pd_op.depthwise_conv2d.6.0_bias")
|
||||
["ReduceMean.4"] "ReduceMean.5" = ReduceMean <keepdims: int = 1> ("Add.75", _v_908)
|
||||
"Add.77" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.5", "conv2d_33.w_0", "p2o.pd_op.conv2d.21.0_bias")
|
||||
["Relu.7"] "p2o.pd_op.relu.7.0" = Relu ("Add.77")
|
||||
"Add.79" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.7.0", "conv2d_34.w_0", "p2o.pd_op.conv2d.22.0_bias")
|
||||
["HardSigmoid.2"] "p2o.pd_op.hardsigmoid.2.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.79")
|
||||
["Mul.22"] "Mul.23" = Mul ("Add.75", "p2o.pd_op.hardsigmoid.2.0")
|
||||
"Add.81" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.23", "conv2d_200.w_0", "p2o.pd_op.conv2d.23.0_bias")
|
||||
"p2o.pd_op.gelu.6.0" = Gelu <approximate: string = "none"> ("Add.81")
|
||||
"Add.85" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.6.0", "conv2d_201.w_0", "p2o.pd_op.conv2d.24.0_bias")
|
||||
["Add.86"] "Add.87" = Add ("Mul.23", "Add.85")
|
||||
"Add.89" = Conv <dilations: ints = [1, 1], group: int = 512, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.87", "conv2d_203.w_0", "p2o.pd_op.depthwise_conv2d.7.0_bias")
|
||||
"Add.91" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.89", "conv2d_204.w_0", "p2o.pd_op.conv2d.25.0_bias")
|
||||
"p2o.pd_op.gelu.7.0" = Gelu <approximate: string = "none"> ("Add.91")
|
||||
"Add.95" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.7.0", "conv2d_205.w_0", "p2o.pd_op.conv2d.26.0_bias")
|
||||
["Add.96"] "Add.97" = Add ("Add.89", "Add.95")
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 512, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.97", "conv2d_207.w_0", "p2o.pd_op.depthwise_conv2d.8.0_bias")
|
||||
["ReduceMean.6"] "ReduceMean.7" = ReduceMean <keepdims: int = 1> ("Add.99", _v_908)
|
||||
"Add.101" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.7", "conv2d_43.w_0", "p2o.pd_op.conv2d.27.0_bias")
|
||||
["Relu.8"] "p2o.pd_op.relu.8.0" = Relu ("Add.101")
|
||||
"Add.103" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.8.0", "conv2d_44.w_0", "p2o.pd_op.conv2d.28.0_bias")
|
||||
["HardSigmoid.3"] "p2o.pd_op.hardsigmoid.3.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.103")
|
||||
["Mul.30"] "Mul.31" = Mul ("Add.99", "p2o.pd_op.hardsigmoid.3.0")
|
||||
"Add.105" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.31", "conv2d_208.w_0", "p2o.pd_op.conv2d.29.0_bias")
|
||||
"p2o.pd_op.gelu.8.0" = Gelu <approximate: string = "none"> ("Add.105")
|
||||
"Add.109" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.8.0", "conv2d_209.w_0", "p2o.pd_op.conv2d.30.0_bias")
|
||||
["Add.110"] "Add.111" = Add ("Mul.31", "Add.109")
|
||||
"Add.113" = Conv <dilations: ints = [1, 1], group: int = 512, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.111", "conv2d_211.w_0", "p2o.pd_op.depthwise_conv2d.9.0_bias")
|
||||
"Add.115" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.113", "conv2d_212.w_0", "p2o.pd_op.conv2d.31.0_bias")
|
||||
"p2o.pd_op.gelu.9.0" = Gelu <approximate: string = "none"> ("Add.115")
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.9.0", "conv2d_213.w_0", "p2o.pd_op.conv2d.32.0_bias")
|
||||
["Add.120"] "Add.121" = Add ("Add.113", "Add.119")
|
||||
"Add.123" = Conv <dilations: ints = [1, 1], group: int = 512, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.121", "conv2d_214.w_0", "p2o.pd_op.depthwise_conv2d.10.0_bias")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.123", "conv2d_215.w_0", "p2o.pd_op.conv2d.33.0_bias")
|
||||
"p2o.pd_op.gelu.10.0" = Gelu <approximate: string = "none"> ("Add.125")
|
||||
"Add.129" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.10.0", "conv2d_216.w_0", "p2o.pd_op.conv2d.34.0_bias")
|
||||
"Add.131" = Conv <dilations: ints = [1, 1], group: int = 896, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.129", "conv2d_218.w_0", "p2o.pd_op.depthwise_conv2d.11.0_bias")
|
||||
["ReduceMean.8"] "ReduceMean.9" = ReduceMean <keepdims: int = 1> ("Add.131", _v_908)
|
||||
"Add.133" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.9", "conv2d_56.w_0", "p2o.pd_op.conv2d.35.0_bias")
|
||||
["Relu.9"] "p2o.pd_op.relu.9.0" = Relu ("Add.133")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.9.0", "conv2d_57.w_0", "p2o.pd_op.conv2d.36.0_bias")
|
||||
["HardSigmoid.4"] "p2o.pd_op.hardsigmoid.4.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.135")
|
||||
["Mul.41"] "Mul.42" = Mul ("Add.131", "p2o.pd_op.hardsigmoid.4.0")
|
||||
"Add.137" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.42", "conv2d_219.w_0", "p2o.pd_op.conv2d.37.0_bias")
|
||||
"p2o.pd_op.gelu.11.0" = Gelu <approximate: string = "none"> ("Add.137")
|
||||
"Add.141" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.11.0", "conv2d_220.w_0", "p2o.pd_op.conv2d.38.0_bias")
|
||||
["Add.142"] "Add.143" = Add ("Mul.42", "Add.141")
|
||||
"Add.145" = Conv <dilations: ints = [1, 1], group: int = 896, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.143", "conv2d_222.w_0", "p2o.pd_op.depthwise_conv2d.12.0_bias")
|
||||
"Add.147" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.145", "conv2d_223.w_0", "p2o.pd_op.conv2d.39.0_bias")
|
||||
"p2o.pd_op.gelu.12.0" = Gelu <approximate: string = "none"> ("Add.147")
|
||||
"Add.151" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.12.0", "conv2d_224.w_0", "p2o.pd_op.conv2d.40.0_bias")
|
||||
["Add.152"] "Add.153" = Add ("Add.145", "Add.151")
|
||||
["Conv.54"] "p2o.pd_op.conv2d.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.153", "conv2d_105.w_0")
|
||||
["Conv.55"] "p2o.pd_op.conv2d.42.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.121", "conv2d_91.w_0")
|
||||
["Conv.56"] "p2o.pd_op.conv2d.43.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.65", "conv2d_77.w_0")
|
||||
["Conv.57"] "p2o.pd_op.conv2d.44.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.33", "conv2d_64.w_0")
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("p2o.pd_op.conv2d.41.0", "helper.constant.40", "helper.constant.39")
|
||||
["Add.154"] "Add.155" = Add ("p2o.pd_op.conv2d.42.0", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.155", "helper.constant.40", "helper.constant.39")
|
||||
["Add.156"] "Add.157" = Add ("p2o.pd_op.conv2d.43.0", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.157", "helper.constant.40", "helper.constant.39")
|
||||
["Add.158"] "Add.159" = Add ("p2o.pd_op.conv2d.44.0", "p2o.pd_op.nearest_interp.2.0")
|
||||
"Add.161" = Conv <dilations: ints = [1, 1], group: int = 256, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("p2o.pd_op.conv2d.41.0", "conv2d_231.w_0", "p2o.pd_op.depthwise_conv2d.13.0_bias")
|
||||
"Add.163" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.161", "conv2d_232.w_0", "p2o.pd_op.conv2d.45.0_bias")
|
||||
"Add.165" = Conv <dilations: ints = [1, 1], group: int = 256, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.155", "conv2d_229.w_0", "p2o.pd_op.depthwise_conv2d.14.0_bias")
|
||||
"Add.167" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.165", "conv2d_230.w_0", "p2o.pd_op.conv2d.46.0_bias")
|
||||
"Add.169" = Conv <dilations: ints = [1, 1], group: int = 256, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.157", "conv2d_227.w_0", "p2o.pd_op.depthwise_conv2d.15.0_bias")
|
||||
"Add.171" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.169", "conv2d_228.w_0", "p2o.pd_op.conv2d.47.0_bias")
|
||||
"Add.173" = Conv <dilations: ints = [1, 1], group: int = 256, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.159", "conv2d_225.w_0", "p2o.pd_op.depthwise_conv2d.16.0_bias")
|
||||
"Add.175" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.173", "conv2d_226.w_0", "p2o.pd_op.conv2d.48.0_bias")
|
||||
["Conv.66"] "p2o.pd_op.conv2d.49.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.175", "conv2d_84.w_0")
|
||||
["Add.176"] "Add.177" = Add ("Add.171", "p2o.pd_op.conv2d.49.0")
|
||||
["Conv.67"] "p2o.pd_op.conv2d.50.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.177", "conv2d_98.w_0")
|
||||
["Add.178"] "Add.179" = Add ("Add.167", "p2o.pd_op.conv2d.50.0")
|
||||
["Conv.68"] "p2o.pd_op.conv2d.51.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.179", "conv2d_112.w_0")
|
||||
["Add.180"] "Add.181" = Add ("Add.163", "p2o.pd_op.conv2d.51.0")
|
||||
"Add.183" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.175", "conv2d_233.w_0", "p2o.pd_op.depthwise_conv2d.17.0_bias")
|
||||
"Add.185" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.183", "conv2d_234.w_0", "p2o.pd_op.conv2d.52.0_bias")
|
||||
"Add.187" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.177", "conv2d_235.w_0", "p2o.pd_op.depthwise_conv2d.18.0_bias")
|
||||
"Add.189" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.187", "conv2d_236.w_0", "p2o.pd_op.conv2d.53.0_bias")
|
||||
"Add.191" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.179", "conv2d_237.w_0", "p2o.pd_op.depthwise_conv2d.19.0_bias")
|
||||
"Add.193" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.191", "conv2d_238.w_0", "p2o.pd_op.conv2d.54.0_bias")
|
||||
"Add.195" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [9, 9], pads: ints = [4, 4, 4, 4], strides: ints = [1, 1]> ("Add.181", "conv2d_239.w_0", "p2o.pd_op.depthwise_conv2d.20.0_bias")
|
||||
"Add.197" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.195", "conv2d_240.w_0", "p2o.pd_op.conv2d.55.0_bias")
|
||||
"Add.199" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.197", "conv2d_152.w_0", "p2o.pd_op.conv2d.56.0_bias")
|
||||
"Add.209" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.199", node_Conv_71_asym_w, node_Conv_71_asym_b)
|
||||
"Add.219" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.209", node_Conv_74_asym_w, node_Conv_74_asym_b)
|
||||
"Add.229" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.219", node_Conv_77_asym_w, node_Conv_77_asym_b)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.229", "conv2d_153.w_0", "p2o.pd_op.conv2d.66.0_bias")
|
||||
["Relu.10"] "p2o.pd_op.relu.10.0" = Relu ("p2o.pd_op.batch_norm_.0.0")
|
||||
["Add.232"] "Add.233" = Add ("Add.197", "p2o.pd_op.relu.10.0")
|
||||
"Add.235" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.193", "conv2d_141.w_0", "p2o.pd_op.conv2d.67.0_bias")
|
||||
"Add.245" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.235", node_Conv_82_asym_w, node_Conv_82_asym_b)
|
||||
"Add.255" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.245", node_Conv_85_asym_w, node_Conv_85_asym_b)
|
||||
"Add.265" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.255", node_Conv_88_asym_w, node_Conv_88_asym_b)
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.265", "conv2d_142.w_0", "p2o.pd_op.conv2d.77.0_bias")
|
||||
["Relu.11"] "p2o.pd_op.relu.11.0" = Relu ("p2o.pd_op.batch_norm_.1.0")
|
||||
["Add.268"] "Add.269" = Add ("Add.193", "p2o.pd_op.relu.11.0")
|
||||
"Add.271" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.189", "conv2d_130.w_0", "p2o.pd_op.conv2d.78.0_bias")
|
||||
"Add.281" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.271", node_Conv_93_asym_w, node_Conv_93_asym_b)
|
||||
"Add.291" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.281", node_Conv_96_asym_w, node_Conv_96_asym_b)
|
||||
"Add.301" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.291", node_Conv_99_asym_w, node_Conv_99_asym_b)
|
||||
"p2o.pd_op.batch_norm_.2.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.301", "conv2d_131.w_0", "p2o.pd_op.conv2d.88.0_bias")
|
||||
["Relu.12"] "p2o.pd_op.relu.12.0" = Relu ("p2o.pd_op.batch_norm_.2.0")
|
||||
["Add.304"] "Add.305" = Add ("Add.189", "p2o.pd_op.relu.12.0")
|
||||
"Add.307" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.185", "conv2d_119.w_0", "p2o.pd_op.conv2d.89.0_bias")
|
||||
"Add.317" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.307", node_Conv_104_asym_w, node_Conv_104_asym_b)
|
||||
"Add.327" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.317", node_Conv_107_asym_w, node_Conv_107_asym_b)
|
||||
"Add.337" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.327", node_Conv_110_asym_w, node_Conv_110_asym_b)
|
||||
"p2o.pd_op.batch_norm_.3.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.337", "conv2d_120.w_0", "p2o.pd_op.conv2d.99.0_bias")
|
||||
["Relu.13"] "p2o.pd_op.relu.13.0" = Relu ("p2o.pd_op.batch_norm_.3.0")
|
||||
["Add.340"] "Add.341" = Add ("Add.185", "p2o.pd_op.relu.13.0")
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.233", "helper.constant.40", "helper.constant.45")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.269", "helper.constant.40", "helper.constant.47")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.305", "helper.constant.40", "helper.constant.39")
|
||||
["Concat.2"] "Concat.3" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.341")
|
||||
"Add.343" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.3", "conv2d_241.w_0", "p2o.pd_op.conv2d.100.0_bias")
|
||||
["Relu.14"] "p2o.pd_op.relu.14.0" = Relu ("Add.343")
|
||||
"Add.345" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.14.0", "auto.cast.135", "ConvTranspose.1_bias")
|
||||
["Relu.15"] "p2o.pd_op.relu.15.0" = Relu ("Add.345")
|
||||
"Add.347" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.15.0", "auto.cast.138", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] fetch_name_0 = Sigmoid ("Add.347")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
ConvTranspose.1_bias FLOAT[64] 5875abe02498
|
||||
ConvTranspose.3_bias FLOAT[1] 0359e3d836cd
|
||||
_v_908 INT64[2] fe6d3d3bb5dd
|
||||
auto.cast.135 FLOAT[64,64,2,2] f9801d3a1233
|
||||
auto.cast.138 FLOAT[64,1,2,2] fe07c2df5b5d
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_105.w_0 FLOAT[256,896,1,1] 1fcf8a0db85f
|
||||
conv2d_112.w_0 FLOAT[64,64,3,3] 43a574b29faa
|
||||
conv2d_119.w_0 FLOAT[32,64,1,1] 0df1d436aade
|
||||
conv2d_120.w_0 FLOAT[64,32,1,1] 9dd117ac5c7e
|
||||
conv2d_130.w_0 FLOAT[32,64,1,1] 1d66b21a629b
|
||||
conv2d_131.w_0 FLOAT[64,32,1,1] e9c94831f407
|
||||
conv2d_141.w_0 FLOAT[32,64,1,1] 223936a59fe7
|
||||
conv2d_142.w_0 FLOAT[64,32,1,1] 5037f27c72e9
|
||||
conv2d_152.w_0 FLOAT[32,64,1,1] 9f1dcbc35c35
|
||||
conv2d_153.w_0 FLOAT[64,32,1,1] c6a9fffd82ee
|
||||
conv2d_171.w_0 FLOAT[64,3,3,3] f82cbbf8b035
|
||||
conv2d_172.w_0 FLOAT[32,64,2,2] aec4cdc32d67
|
||||
conv2d_173.w_0 FLOAT[64,32,2,2] d01a705337d4
|
||||
conv2d_174.w_0 FLOAT[64,128,3,3] 293cfb98f372
|
||||
conv2d_175.w_0 FLOAT[128,64,1,1] fb741be174d3
|
||||
conv2d_177.w_0 FLOAT[128,1,3,3] 1a5c931a3b48
|
||||
conv2d_178.w_0 FLOAT[256,128,1,1] a19eaeb3d42d
|
||||
conv2d_179.w_0 FLOAT[128,256,1,1] c01c66ce56d8
|
||||
conv2d_181.w_0 FLOAT[128,1,3,3] c565be6bf925
|
||||
conv2d_182.w_0 FLOAT[256,128,1,1] 14594c892aa3
|
||||
conv2d_183.w_0 FLOAT[128,256,1,1] 3a41e06eb143
|
||||
conv2d_184.w_0 FLOAT[128,1,3,3] 96f66b4903a2
|
||||
conv2d_185.w_0 FLOAT[256,128,1,1] dc819364392f
|
||||
conv2d_186.w_0 FLOAT[256,256,1,1] 7047c39f304e
|
||||
conv2d_188.w_0 FLOAT[256,1,3,3] 25eb5e754b99
|
||||
conv2d_189.w_0 FLOAT[512,256,1,1] 604185eec32a
|
||||
conv2d_190.w_0 FLOAT[256,512,1,1] 54feef457f7f
|
||||
conv2d_192.w_0 FLOAT[256,1,3,3] 27f8da8c01cb
|
||||
conv2d_193.w_0 FLOAT[512,256,1,1] 55276217c012
|
||||
conv2d_194.w_0 FLOAT[256,512,1,1] b9a54a50b39b
|
||||
conv2d_195.w_0 FLOAT[256,1,3,3] d72100bce140
|
||||
conv2d_196.w_0 FLOAT[512,256,1,1] 85a49e884586
|
||||
conv2d_197.w_0 FLOAT[512,512,1,1] c3e55054a470
|
||||
conv2d_199.w_0 FLOAT[512,1,3,3] ffe3c1d2c936
|
||||
conv2d_20.w_0 FLOAT[64,256,1,1] 40a055d4c5ac
|
||||
conv2d_200.w_0 FLOAT[1024,512,1,1] 629ba6122c96
|
||||
conv2d_201.w_0 FLOAT[512,1024,1,1] 494f651a04d5
|
||||
conv2d_203.w_0 FLOAT[512,1,3,3] 63514165483b
|
||||
conv2d_204.w_0 FLOAT[1024,512,1,1] 2f1d92604f88
|
||||
conv2d_205.w_0 FLOAT[512,1024,1,1] 31c6bac43721
|
||||
conv2d_207.w_0 FLOAT[512,1,3,3] 24f89a4671a5
|
||||
conv2d_208.w_0 FLOAT[1024,512,1,1] 2a83ca87a34e
|
||||
conv2d_209.w_0 FLOAT[512,1024,1,1] bde609ce7e75
|
||||
conv2d_21.w_0 FLOAT[256,64,1,1] 76ae13a552c7
|
||||
conv2d_211.w_0 FLOAT[512,1,3,3] e2950080bbc1
|
||||
conv2d_212.w_0 FLOAT[1024,512,1,1] 58dc8f7d123b
|
||||
conv2d_213.w_0 FLOAT[512,1024,1,1] 093ebf4f6836
|
||||
conv2d_214.w_0 FLOAT[512,1,3,3] 07f65b6c4ddc
|
||||
conv2d_215.w_0 FLOAT[1024,512,1,1] 0208f870d301
|
||||
conv2d_216.w_0 FLOAT[896,1024,1,1] 51a52cb9177c
|
||||
conv2d_218.w_0 FLOAT[896,1,3,3] 42605ed32047
|
||||
conv2d_219.w_0 FLOAT[1792,896,1,1] 8639e8636539
|
||||
conv2d_220.w_0 FLOAT[896,1792,1,1] 4a02be643199
|
||||
conv2d_222.w_0 FLOAT[896,1,3,3] 323a26240671
|
||||
conv2d_223.w_0 FLOAT[1792,896,1,1] f926cc6dcff6
|
||||
conv2d_224.w_0 FLOAT[896,1792,1,1] 6cc78bdd1d3b
|
||||
conv2d_225.w_0 FLOAT[256,1,9,9] bff9535170a3
|
||||
conv2d_226.w_0 FLOAT[64,256,1,1] 1cc6714f807f
|
||||
conv2d_227.w_0 FLOAT[256,1,9,9] f5ea29045e2d
|
||||
conv2d_228.w_0 FLOAT[64,256,1,1] 8aa5a380b0b6
|
||||
conv2d_229.w_0 FLOAT[256,1,9,9] a38ccc62b522
|
||||
conv2d_230.w_0 FLOAT[64,256,1,1] 51edc0ffe242
|
||||
conv2d_231.w_0 FLOAT[256,1,9,9] 4c3dee65974e
|
||||
conv2d_232.w_0 FLOAT[64,256,1,1] a0044a50029d
|
||||
conv2d_233.w_0 FLOAT[64,1,9,9] e314de14acf2
|
||||
conv2d_234.w_0 FLOAT[64,64,1,1] 4eb47d09b2f7
|
||||
conv2d_235.w_0 FLOAT[64,1,9,9] 0c41e0b3c8eb
|
||||
conv2d_236.w_0 FLOAT[64,64,1,1] da9dadfede5b
|
||||
conv2d_237.w_0 FLOAT[64,1,9,9] 539094fd65ee
|
||||
conv2d_238.w_0 FLOAT[64,64,1,1] 2c1536835b07
|
||||
conv2d_239.w_0 FLOAT[64,1,9,9] c2da8a0eebc1
|
||||
conv2d_240.w_0 FLOAT[64,64,1,1] dc49e9d96921
|
||||
conv2d_241.w_0 FLOAT[64,256,3,3] 599975a644f9
|
||||
conv2d_33.w_0 FLOAT[128,512,1,1] bc11fda606e3
|
||||
conv2d_34.w_0 FLOAT[512,128,1,1] 47e4aa48ca3d
|
||||
conv2d_43.w_0 FLOAT[128,512,1,1] daa6796c4bcd
|
||||
conv2d_44.w_0 FLOAT[512,128,1,1] 38b5b8bdfc13
|
||||
conv2d_56.w_0 FLOAT[224,896,1,1] 34f3e6bccf56
|
||||
conv2d_57.w_0 FLOAT[896,224,1,1] 6b7061087525
|
||||
conv2d_64.w_0 FLOAT[256,128,1,1] 8176bc974073
|
||||
conv2d_7.w_0 FLOAT[32,128,1,1] 552c7f2818b1
|
||||
conv2d_77.w_0 FLOAT[256,256,1,1] a235f9e665f6
|
||||
conv2d_8.w_0 FLOAT[128,32,1,1] 0e2b086d509b
|
||||
conv2d_84.w_0 FLOAT[64,64,3,3] f93dda94272d
|
||||
conv2d_91.w_0 FLOAT[256,512,1,1] ee8579bdcd98
|
||||
conv2d_98.w_0 FLOAT[64,64,3,3] c94233ecce16
|
||||
helper.constant.39 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.40 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.45 FLOAT[4] cf5451a623be
|
||||
helper.constant.47 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
node_Conv_104_asym_b FLOAT[32] 5546f5f2f45b
|
||||
node_Conv_104_asym_w FLOAT[32,32,7,7] ce4ead7bcb66
|
||||
node_Conv_107_asym_b FLOAT[32] d98492f9794e
|
||||
node_Conv_107_asym_w FLOAT[32,32,5,5] b6490010db62
|
||||
node_Conv_110_asym_b FLOAT[32] 006aaad24eb6
|
||||
node_Conv_110_asym_w FLOAT[32,32,3,3] 98cfc278f0a0
|
||||
node_Conv_71_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_71_asym_w FLOAT[32,32,7,7] ba0ee4b797b9
|
||||
node_Conv_74_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_74_asym_w FLOAT[32,32,5,5] f627ca4c2c32
|
||||
node_Conv_77_asym_b FLOAT[32] 38723a2e5e8a
|
||||
node_Conv_77_asym_w FLOAT[32,32,3,3] 1c0273095382
|
||||
node_Conv_82_asym_b FLOAT[32] b5e58a7f40bd
|
||||
node_Conv_82_asym_w FLOAT[32,32,7,7] 35f1f4446612
|
||||
node_Conv_85_asym_b FLOAT[32] fc64d25a2a7d
|
||||
node_Conv_85_asym_w FLOAT[32,32,5,5] 5724784963a5
|
||||
node_Conv_88_asym_b FLOAT[32] 0eec468c5222
|
||||
node_Conv_88_asym_w FLOAT[32,32,3,3] 48387653a4b5
|
||||
node_Conv_93_asym_b FLOAT[32] b2f32c8579a5
|
||||
node_Conv_93_asym_w FLOAT[32,32,7,7] a85a1838c35f
|
||||
node_Conv_96_asym_b FLOAT[32] 8346d7f3140e
|
||||
node_Conv_96_asym_w FLOAT[32,32,5,5] ac981dda3cc5
|
||||
node_Conv_99_asym_b FLOAT[32] 72791a813869
|
||||
node_Conv_99_asym_w FLOAT[32,32,3,3] e1382b557b4e
|
||||
p2o.pd_op.conv2d.0.0_bias FLOAT[64] ecf86942b06c
|
||||
p2o.pd_op.conv2d.1.0_bias FLOAT[32] 21684e43449b
|
||||
p2o.pd_op.conv2d.10.0_bias FLOAT[128] 254c720c1e4f
|
||||
p2o.pd_op.conv2d.100.0_bias FLOAT[64] 182e9177fb4f
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[256] 3a08517885d5
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[256] 6c41987ea8c1
|
||||
p2o.pd_op.conv2d.13.0_bias FLOAT[64] f1598330c3e7
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[256] facb0ee60ec4
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[512] 28e69b1b8929
|
||||
p2o.pd_op.conv2d.16.0_bias FLOAT[256] 431fa34d1ac4
|
||||
p2o.pd_op.conv2d.17.0_bias FLOAT[512] 75ed19f915f8
|
||||
p2o.pd_op.conv2d.18.0_bias FLOAT[256] d55ad87d5f49
|
||||
p2o.pd_op.conv2d.19.0_bias FLOAT[512] 319fef1ab99b
|
||||
p2o.pd_op.conv2d.2.0_bias FLOAT[64] d688034fe16b
|
||||
p2o.pd_op.conv2d.20.0_bias FLOAT[512] 86e0e5717ddd
|
||||
p2o.pd_op.conv2d.21.0_bias FLOAT[128] 2b0313234cd8
|
||||
p2o.pd_op.conv2d.22.0_bias FLOAT[512] cfa440444ca8
|
||||
p2o.pd_op.conv2d.23.0_bias FLOAT[1024] e82efd3472b4
|
||||
p2o.pd_op.conv2d.24.0_bias FLOAT[512] 7400b8a2f06e
|
||||
p2o.pd_op.conv2d.25.0_bias FLOAT[1024] 61e9aa77d935
|
||||
p2o.pd_op.conv2d.26.0_bias FLOAT[512] 8aee6c7c1b94
|
||||
p2o.pd_op.conv2d.27.0_bias FLOAT[128] 1ff01b1b0bce
|
||||
p2o.pd_op.conv2d.28.0_bias FLOAT[512] a090150bf239
|
||||
p2o.pd_op.conv2d.29.0_bias FLOAT[1024] 0745f89aecbd
|
||||
p2o.pd_op.conv2d.3.0_bias FLOAT[64] 0a8ab1fbd9c3
|
||||
p2o.pd_op.conv2d.30.0_bias FLOAT[512] be2e78d86e5f
|
||||
p2o.pd_op.conv2d.31.0_bias FLOAT[1024] c850c2f4c785
|
||||
p2o.pd_op.conv2d.32.0_bias FLOAT[512] 476601082ec7
|
||||
p2o.pd_op.conv2d.33.0_bias FLOAT[1024] a984298137db
|
||||
p2o.pd_op.conv2d.34.0_bias FLOAT[896] f82539031abf
|
||||
p2o.pd_op.conv2d.35.0_bias FLOAT[224] c8dfa1414bd2
|
||||
p2o.pd_op.conv2d.36.0_bias FLOAT[896] e4b663c75da0
|
||||
p2o.pd_op.conv2d.37.0_bias FLOAT[1792] 6a40f6c9189c
|
||||
p2o.pd_op.conv2d.38.0_bias FLOAT[896] 6da9f6968062
|
||||
p2o.pd_op.conv2d.39.0_bias FLOAT[1792] 65802f7f4ed8
|
||||
p2o.pd_op.conv2d.4.0_bias FLOAT[128] abe6ae469122
|
||||
p2o.pd_op.conv2d.40.0_bias FLOAT[896] 20572c12419d
|
||||
p2o.pd_op.conv2d.45.0_bias FLOAT[64] b6afcd3bd7f4
|
||||
p2o.pd_op.conv2d.46.0_bias FLOAT[64] 7d9d6dcce879
|
||||
p2o.pd_op.conv2d.47.0_bias FLOAT[64] aaa3e5faf886
|
||||
p2o.pd_op.conv2d.48.0_bias FLOAT[64] 707a0ee35ee1
|
||||
p2o.pd_op.conv2d.5.0_bias FLOAT[32] e00d0c98eabb
|
||||
p2o.pd_op.conv2d.52.0_bias FLOAT[64] 83d248445b23
|
||||
p2o.pd_op.conv2d.53.0_bias FLOAT[64] 68eab0573648
|
||||
p2o.pd_op.conv2d.54.0_bias FLOAT[64] 41db5ddc3645
|
||||
p2o.pd_op.conv2d.55.0_bias FLOAT[64] e3f0c5fb247f
|
||||
p2o.pd_op.conv2d.56.0_bias FLOAT[32] 38723a2e5e8a
|
||||
p2o.pd_op.conv2d.6.0_bias FLOAT[128] 73a1abbab7f4
|
||||
p2o.pd_op.conv2d.66.0_bias FLOAT[64] adaef9153bd3
|
||||
p2o.pd_op.conv2d.67.0_bias FLOAT[32] daa8ebee99a5
|
||||
p2o.pd_op.conv2d.7.0_bias FLOAT[256] 0ab81f1b64fc
|
||||
p2o.pd_op.conv2d.77.0_bias FLOAT[64] fbf949cef5a3
|
||||
p2o.pd_op.conv2d.78.0_bias FLOAT[32] 9482a9e1d728
|
||||
p2o.pd_op.conv2d.8.0_bias FLOAT[128] 110dc2f60f3b
|
||||
p2o.pd_op.conv2d.88.0_bias FLOAT[64] 4184716a7e92
|
||||
p2o.pd_op.conv2d.89.0_bias FLOAT[32] 4c8820b6c841
|
||||
p2o.pd_op.conv2d.9.0_bias FLOAT[256] f66b0a251104
|
||||
p2o.pd_op.conv2d.99.0_bias FLOAT[64] 57604a9a5943
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias FLOAT[128] a14e8c99ecb5
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias FLOAT[128] a2deebc0c88e
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias FLOAT[512] ffe653aa4a95
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias FLOAT[896] cb7ac826d387
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias FLOAT[896] 282a8c7f7b1a
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias FLOAT[256] fd7061c439ae
|
||||
p2o.pd_op.depthwise_conv2d.14.0_bias FLOAT[256] 626426da44df
|
||||
p2o.pd_op.depthwise_conv2d.15.0_bias FLOAT[256] 6e890e555d0a
|
||||
p2o.pd_op.depthwise_conv2d.16.0_bias FLOAT[256] 5e95245fe31d
|
||||
p2o.pd_op.depthwise_conv2d.17.0_bias FLOAT[64] f38a12c3f7f7
|
||||
p2o.pd_op.depthwise_conv2d.18.0_bias FLOAT[64] 7154897770a2
|
||||
p2o.pd_op.depthwise_conv2d.19.0_bias FLOAT[64] 7deab9ca4017
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias FLOAT[128] aae16e9b8e79
|
||||
p2o.pd_op.depthwise_conv2d.20.0_bias FLOAT[64] 103ab07bf238
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias FLOAT[256] 8be520e4dafe
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias FLOAT[256] b7aae420b9a5
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias FLOAT[256] fd0d27be92c5
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias FLOAT[512] eedb63ccdf6b
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias FLOAT[512] b4ae12d2b4b3
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias FLOAT[512] 370d34549cb2
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias FLOAT[512] 65aff6cd440e
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,508 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,24,unk__0,unk__1] "Add.1"
|
||||
float[batch,48,1,1] "Add.101"
|
||||
float[batch,192,1,1] "Add.103"
|
||||
float[batch,384,unk__50,unk__51] "Add.105"
|
||||
float[batch,192,unk__50,unk__51] "Add.109"
|
||||
float[batch,48,unk__8,unk__9] "Add.11"
|
||||
float[batch,192,unk__50,unk__51] "Add.111"
|
||||
float[batch,192,unk__50,unk__51] "Add.113"
|
||||
float[batch,384,unk__50,unk__51] "Add.115"
|
||||
float[batch,192,unk__50,unk__51] "Add.119"
|
||||
float[batch,192,unk__50,unk__51] "Add.121"
|
||||
float[batch,192,unk__88,unk__89] "Add.123"
|
||||
float[batch,384,unk__88,unk__89] "Add.125"
|
||||
float[batch,384,unk__88,unk__89] "Add.129"
|
||||
float[batch,12,1,1] "Add.13"
|
||||
float[batch,384,unk__88,unk__89] "Add.131"
|
||||
float[batch,96,1,1] "Add.133"
|
||||
float[batch,384,1,1] "Add.135"
|
||||
float[batch,768,unk__88,unk__89] "Add.137"
|
||||
float[batch,384,unk__88,unk__89] "Add.141"
|
||||
float[batch,384,unk__88,unk__89] "Add.143"
|
||||
float[batch,384,unk__88,unk__89] "Add.145"
|
||||
float[batch,768,unk__88,unk__89] "Add.147"
|
||||
float[batch,48,1,1] "Add.15"
|
||||
float[batch,384,unk__88,unk__89] "Add.151"
|
||||
float[batch,384,unk__88,unk__89] "Add.153"
|
||||
float[batch,96,unk__88,unk__89] "Add.159"
|
||||
float[batch,96,unk__50,unk__51] "Add.165"
|
||||
float[batch,96,unk__8,unk__9] "Add.17"
|
||||
float[batch,96,unk__28,unk__29] "Add.171"
|
||||
float[batch,96,unk__8,unk__9] "Add.177"
|
||||
float[batch,96,unk__50,unk__51] "Add.179"
|
||||
float[batch,96,unk__28,unk__29] "Add.181"
|
||||
float[batch,96,unk__8,unk__9] "Add.183"
|
||||
float[batch,96,unk__88,unk__89] "Add.185"
|
||||
float[batch,24,unk__88,unk__89] "Add.191"
|
||||
float[batch,96,unk__50,unk__51] "Add.193"
|
||||
float[batch,24,unk__50,unk__51] "Add.199"
|
||||
float[batch,96,unk__28,unk__29] "Add.201"
|
||||
float[batch,24,unk__28,unk__29] "Add.207"
|
||||
float[batch,96,unk__8,unk__9] "Add.209"
|
||||
float[batch,48,unk__8,unk__9] "Add.21"
|
||||
float[batch,24,unk__8,unk__9] "Add.215"
|
||||
float[batch,24,unk__8,unk__9] "Add.217"
|
||||
float[batch,24,unk__0,unk__1] "Add.219"
|
||||
float[batch,1,height,width] "Add.221"
|
||||
float[batch,48,unk__8,unk__9] "Add.23"
|
||||
float[batch,48,unk__8,unk__9] "Add.25"
|
||||
float[batch,96,unk__8,unk__9] "Add.27"
|
||||
float[batch,12,unk__0,unk__1] "Add.3"
|
||||
float[batch,48,unk__8,unk__9] "Add.31"
|
||||
float[batch,48,unk__8,unk__9] "Add.33"
|
||||
float[batch,48,unk__28,unk__29] "Add.35"
|
||||
float[batch,96,unk__28,unk__29] "Add.37"
|
||||
float[batch,96,unk__28,unk__29] "Add.41"
|
||||
float[batch,96,unk__28,unk__29] "Add.43"
|
||||
float[batch,24,1,1] "Add.45"
|
||||
float[batch,96,1,1] "Add.47"
|
||||
float[batch,192,unk__28,unk__29] "Add.49"
|
||||
float[batch,24,unk__0,unk__1] "Add.5"
|
||||
float[batch,96,unk__28,unk__29] "Add.53"
|
||||
float[batch,96,unk__28,unk__29] "Add.55"
|
||||
float[batch,96,unk__28,unk__29] "Add.57"
|
||||
float[batch,192,unk__28,unk__29] "Add.59"
|
||||
float[batch,96,unk__28,unk__29] "Add.63"
|
||||
float[batch,96,unk__28,unk__29] "Add.65"
|
||||
float[batch,96,unk__50,unk__51] "Add.67"
|
||||
float[batch,192,unk__50,unk__51] "Add.69"
|
||||
float[batch,24,unk__8,unk__9] "Add.7"
|
||||
float[batch,192,unk__50,unk__51] "Add.73"
|
||||
float[batch,192,unk__50,unk__51] "Add.75"
|
||||
float[batch,48,1,1] "Add.77"
|
||||
float[batch,192,1,1] "Add.79"
|
||||
float[batch,384,unk__50,unk__51] "Add.81"
|
||||
float[batch,192,unk__50,unk__51] "Add.85"
|
||||
float[batch,192,unk__50,unk__51] "Add.87"
|
||||
float[batch,192,unk__50,unk__51] "Add.89"
|
||||
float[batch,48,unk__8,unk__9] "Add.9"
|
||||
float[batch,384,unk__50,unk__51] "Add.91"
|
||||
float[batch,192,unk__50,unk__51] "Add.95"
|
||||
float[batch,192,unk__50,unk__51] "Add.97"
|
||||
float[batch,192,unk__50,unk__51] "Add.99"
|
||||
float[batch,48,unk__0,unk__1] "Concat.1"
|
||||
float[batch,96,unk__8,unk__9] "Concat.3"
|
||||
float[batch,48,unk__8,unk__9] "Mul.1"
|
||||
float[batch,96,unk__28,unk__29] "Mul.12"
|
||||
float[batch,192,unk__50,unk__51] "Mul.23"
|
||||
float[batch,192,unk__50,unk__51] "Mul.31"
|
||||
float[batch,384,unk__88,unk__89] "Mul.42"
|
||||
float[batch,48,1,1] "ReduceMean.1"
|
||||
float[batch,96,1,1] "ReduceMean.3"
|
||||
float[batch,192,1,1] "ReduceMean.5"
|
||||
float[batch,192,1,1] "ReduceMean.7"
|
||||
float[batch,384,1,1] "ReduceMean.9"
|
||||
float[batch,96,unk__88,unk__89] "p2o.pd_op.conv2d.41.0"
|
||||
float[batch,96,unk__50,unk__51] "p2o.pd_op.conv2d.44.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.conv2d.47.0"
|
||||
float[batch,96,unk__8,unk__9] "p2o.pd_op.conv2d.50.0"
|
||||
float[batch,24,unk__88,unk__89] "p2o.pd_op.conv2d.53.0"
|
||||
float[batch,24,unk__50,unk__51] "p2o.pd_op.conv2d.56.0"
|
||||
float[batch,24,unk__28,unk__29] "p2o.pd_op.conv2d.59.0"
|
||||
float[batch,24,unk__8,unk__9] "p2o.pd_op.conv2d.62.0"
|
||||
float[batch,96,unk__8,unk__9] "p2o.pd_op.gelu.0.0"
|
||||
float[batch,96,unk__8,unk__9] "p2o.pd_op.gelu.1.0"
|
||||
float[batch,384,unk__88,unk__89] "p2o.pd_op.gelu.10.0"
|
||||
float[batch,768,unk__88,unk__89] "p2o.pd_op.gelu.11.0"
|
||||
float[batch,768,unk__88,unk__89] "p2o.pd_op.gelu.12.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.gelu.2.0"
|
||||
float[batch,192,unk__28,unk__29] "p2o.pd_op.gelu.3.0"
|
||||
float[batch,192,unk__28,unk__29] "p2o.pd_op.gelu.4.0"
|
||||
float[batch,192,unk__50,unk__51] "p2o.pd_op.gelu.5.0"
|
||||
float[batch,384,unk__50,unk__51] "p2o.pd_op.gelu.6.0"
|
||||
float[batch,384,unk__50,unk__51] "p2o.pd_op.gelu.7.0"
|
||||
float[batch,384,unk__50,unk__51] "p2o.pd_op.gelu.8.0"
|
||||
float[batch,384,unk__50,unk__51] "p2o.pd_op.gelu.9.0"
|
||||
float[batch,48,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.hardsigmoid.2.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.hardsigmoid.3.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.hardsigmoid.4.0"
|
||||
float[batch,96,unk__50,unk__51] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,96,unk__8,unk__9] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,24,unk__8,unk__9] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,24,unk__8,unk__9] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,24,unk__8,unk__9] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.1.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.2.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.3.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.4.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.5.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.6.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.7.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.8.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,12,unk__0,unk__1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,24,unk__8,unk__9] "p2o.pd_op.relu.18.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.relu.19.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.relu.2.0"
|
||||
float[batch,24,unk__8,unk__9] "p2o.pd_op.relu.3.0"
|
||||
float[batch,48,unk__8,unk__9] "p2o.pd_op.relu.4.0"
|
||||
float[batch,12,1,1] "p2o.pd_op.relu.5.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.relu.6.0"
|
||||
float[batch,48,1,1] "p2o.pd_op.relu.7.0"
|
||||
float[batch,48,1,1] "p2o.pd_op.relu.8.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.relu.9.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.5.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.6.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.7.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.8.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.10.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.11.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.12.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.9.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,96,1,1] se_group0_down
|
||||
float[batch,384,1,1] se_group0_gates
|
||||
float[batch,384,1,1] se_group0_pooled
|
||||
float[batch,96,1,1] se_group0_relu
|
||||
float[batch,384,1,1] se_group0_up
|
||||
float[batch,24,1,1] se_group1_down
|
||||
float[batch,96,1,1] se_group1_gates
|
||||
float[batch,96,1,1] se_group1_pooled
|
||||
float[batch,24,1,1] se_group1_relu
|
||||
float[batch,96,1,1] se_group1_up
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,96,1,1] val_0
|
||||
float[batch,96,1,1] val_1
|
||||
float[batch,96,1,1] val_2
|
||||
float[batch,96,1,1] val_3
|
||||
float[batch,24,1,1] val_4
|
||||
float[batch,24,1,1] val_5
|
||||
float[batch,24,1,1] val_6
|
||||
float[batch,24,1,1] val_7
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"Add.1" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_112.w_0", "p2o.pd_op.conv2d.0.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.1")
|
||||
"Add.3" = Conv <auto_pad: string = "SAME_UPPER", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_113.w_0", "p2o.pd_op.conv2d.1.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.3")
|
||||
"Add.5" = Conv <auto_pad: string = "SAME_UPPER", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_114.w_0", "p2o.pd_op.conv2d.2.0_bias")
|
||||
["Relu.2"] "p2o.pd_op.relu.2.0" = Relu ("Add.5")
|
||||
["MaxPool.0"] "p2o.pd_op.pool2d.0.0" = MaxPool <auto_pad: string = "SAME_UPPER", ceil_mode: int = 0, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.pool2d.0.0", "p2o.pd_op.relu.2.0")
|
||||
"Add.7" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Concat.1", "conv2d_115.w_0", "p2o.pd_op.conv2d.3.0_bias")
|
||||
["Relu.3"] "p2o.pd_op.relu.3.0" = Relu ("Add.7")
|
||||
"Add.9" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.3.0", "conv2d_116.w_0", "p2o.pd_op.conv2d.4.0_bias")
|
||||
["Relu.4"] "p2o.pd_op.relu.4.0" = Relu ("Add.9")
|
||||
"Add.11" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.4.0", "conv2d_118.w_0", "p2o.pd_op.depthwise_conv2d.0.0_bias")
|
||||
["ReduceMean.0"] "ReduceMean.1" = ReduceMean <keepdims: int = 1> ("Add.11", _v_680)
|
||||
"Add.13" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.1", "conv2d_7.w_0", "p2o.pd_op.conv2d.5.0_bias")
|
||||
["Relu.5"] "p2o.pd_op.relu.5.0" = Relu ("Add.13")
|
||||
"Add.15" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.5.0", "conv2d_8.w_0", "p2o.pd_op.conv2d.6.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.15")
|
||||
["Mul.0"] "Mul.1" = Mul ("Add.11", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.17" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.1", "conv2d_119.w_0", "p2o.pd_op.conv2d.7.0_bias")
|
||||
"p2o.pd_op.gelu.0.0" = Gelu <approximate: string = "none"> ("Add.17")
|
||||
"Add.21" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.0.0", "conv2d_120.w_0", "p2o.pd_op.conv2d.8.0_bias")
|
||||
["Add.22"] "Add.23" = Add ("Mul.1", "Add.21")
|
||||
"Add.25" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.23", "conv2d_122.w_0", "p2o.pd_op.depthwise_conv2d.1.0_bias")
|
||||
"Add.27" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.25", "conv2d_123.w_0", "p2o.pd_op.conv2d.9.0_bias")
|
||||
"p2o.pd_op.gelu.1.0" = Gelu <approximate: string = "none"> ("Add.27")
|
||||
"Add.31" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.1.0", "conv2d_124.w_0", "p2o.pd_op.conv2d.10.0_bias")
|
||||
["Add.32"] "Add.33" = Add ("Add.25", "Add.31")
|
||||
"Add.35" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.33", "conv2d_125.w_0", "p2o.pd_op.depthwise_conv2d.2.0_bias")
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.35", "conv2d_126.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
"p2o.pd_op.gelu.2.0" = Gelu <approximate: string = "none"> ("Add.37")
|
||||
"Add.41" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.2.0", "conv2d_127.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
"Add.43" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.41", "conv2d_129.w_0", "p2o.pd_op.depthwise_conv2d.3.0_bias")
|
||||
["ReduceMean.2"] "ReduceMean.3" = ReduceMean <keepdims: int = 1> ("Add.43", _v_680)
|
||||
"Add.45" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.3", "conv2d_20.w_0", "p2o.pd_op.conv2d.13.0_bias")
|
||||
["Relu.6"] "p2o.pd_op.relu.6.0" = Relu ("Add.45")
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.6.0", "conv2d_21.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.47")
|
||||
["Mul.11"] "Mul.12" = Mul ("Add.43", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.49" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.12", "conv2d_130.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
"p2o.pd_op.gelu.3.0" = Gelu <approximate: string = "none"> ("Add.49")
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.3.0", "conv2d_131.w_0", "p2o.pd_op.conv2d.16.0_bias")
|
||||
["Add.54"] "Add.55" = Add ("Mul.12", "Add.53")
|
||||
"Add.57" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.55", "conv2d_133.w_0", "p2o.pd_op.depthwise_conv2d.4.0_bias")
|
||||
"Add.59" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.57", "conv2d_134.w_0", "p2o.pd_op.conv2d.17.0_bias")
|
||||
"p2o.pd_op.gelu.4.0" = Gelu <approximate: string = "none"> ("Add.59")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.4.0", "conv2d_135.w_0", "p2o.pd_op.conv2d.18.0_bias")
|
||||
["Add.64"] "Add.65" = Add ("Add.57", "Add.63")
|
||||
"Add.67" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.65", "conv2d_136.w_0", "p2o.pd_op.depthwise_conv2d.5.0_bias")
|
||||
"Add.69" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.67", "conv2d_137.w_0", "p2o.pd_op.conv2d.19.0_bias")
|
||||
"p2o.pd_op.gelu.5.0" = Gelu <approximate: string = "none"> ("Add.69")
|
||||
"Add.73" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.5.0", "conv2d_138.w_0", "p2o.pd_op.conv2d.20.0_bias")
|
||||
"Add.75" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.73", "conv2d_140.w_0", "p2o.pd_op.depthwise_conv2d.6.0_bias")
|
||||
["ReduceMean.4"] "ReduceMean.5" = ReduceMean <keepdims: int = 1> ("Add.75", _v_680)
|
||||
"Add.77" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.5", "conv2d_33.w_0", "p2o.pd_op.conv2d.21.0_bias")
|
||||
["Relu.7"] "p2o.pd_op.relu.7.0" = Relu ("Add.77")
|
||||
"Add.79" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.7.0", "conv2d_34.w_0", "p2o.pd_op.conv2d.22.0_bias")
|
||||
["HardSigmoid.2"] "p2o.pd_op.hardsigmoid.2.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.79")
|
||||
["Mul.22"] "Mul.23" = Mul ("Add.75", "p2o.pd_op.hardsigmoid.2.0")
|
||||
"Add.81" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.23", "conv2d_141.w_0", "p2o.pd_op.conv2d.23.0_bias")
|
||||
"p2o.pd_op.gelu.6.0" = Gelu <approximate: string = "none"> ("Add.81")
|
||||
"Add.85" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.6.0", "conv2d_142.w_0", "p2o.pd_op.conv2d.24.0_bias")
|
||||
["Add.86"] "Add.87" = Add ("Mul.23", "Add.85")
|
||||
"Add.89" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.87", "conv2d_144.w_0", "p2o.pd_op.depthwise_conv2d.7.0_bias")
|
||||
"Add.91" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.89", "conv2d_145.w_0", "p2o.pd_op.conv2d.25.0_bias")
|
||||
"p2o.pd_op.gelu.7.0" = Gelu <approximate: string = "none"> ("Add.91")
|
||||
"Add.95" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.7.0", "conv2d_146.w_0", "p2o.pd_op.conv2d.26.0_bias")
|
||||
["Add.96"] "Add.97" = Add ("Add.89", "Add.95")
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.97", "conv2d_148.w_0", "p2o.pd_op.depthwise_conv2d.8.0_bias")
|
||||
["ReduceMean.6"] "ReduceMean.7" = ReduceMean <keepdims: int = 1> ("Add.99", _v_680)
|
||||
"Add.101" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.7", "conv2d_43.w_0", "p2o.pd_op.conv2d.27.0_bias")
|
||||
["Relu.8"] "p2o.pd_op.relu.8.0" = Relu ("Add.101")
|
||||
"Add.103" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.8.0", "conv2d_44.w_0", "p2o.pd_op.conv2d.28.0_bias")
|
||||
["HardSigmoid.3"] "p2o.pd_op.hardsigmoid.3.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.103")
|
||||
["Mul.30"] "Mul.31" = Mul ("Add.99", "p2o.pd_op.hardsigmoid.3.0")
|
||||
"Add.105" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.31", "conv2d_149.w_0", "p2o.pd_op.conv2d.29.0_bias")
|
||||
"p2o.pd_op.gelu.8.0" = Gelu <approximate: string = "none"> ("Add.105")
|
||||
"Add.109" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.8.0", "conv2d_150.w_0", "p2o.pd_op.conv2d.30.0_bias")
|
||||
["Add.110"] "Add.111" = Add ("Mul.31", "Add.109")
|
||||
"Add.113" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.111", "conv2d_152.w_0", "p2o.pd_op.depthwise_conv2d.9.0_bias")
|
||||
"Add.115" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.113", "conv2d_153.w_0", "p2o.pd_op.conv2d.31.0_bias")
|
||||
"p2o.pd_op.gelu.9.0" = Gelu <approximate: string = "none"> ("Add.115")
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.9.0", "conv2d_154.w_0", "p2o.pd_op.conv2d.32.0_bias")
|
||||
["Add.120"] "Add.121" = Add ("Add.113", "Add.119")
|
||||
"Add.123" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.121", "conv2d_155.w_0", "p2o.pd_op.depthwise_conv2d.10.0_bias")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.123", "conv2d_156.w_0", "p2o.pd_op.conv2d.33.0_bias")
|
||||
"p2o.pd_op.gelu.10.0" = Gelu <approximate: string = "none"> ("Add.125")
|
||||
"Add.129" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.10.0", "conv2d_157.w_0", "p2o.pd_op.conv2d.34.0_bias")
|
||||
"Add.131" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.129", "conv2d_159.w_0", "p2o.pd_op.depthwise_conv2d.11.0_bias")
|
||||
["ReduceMean.8"] "ReduceMean.9" = ReduceMean <keepdims: int = 1> ("Add.131", _v_680)
|
||||
"Add.133" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.9", "conv2d_56.w_0", "p2o.pd_op.conv2d.35.0_bias")
|
||||
["Relu.9"] "p2o.pd_op.relu.9.0" = Relu ("Add.133")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.9.0", "conv2d_57.w_0", "p2o.pd_op.conv2d.36.0_bias")
|
||||
["HardSigmoid.4"] "p2o.pd_op.hardsigmoid.4.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.135")
|
||||
["Mul.41"] "Mul.42" = Mul ("Add.131", "p2o.pd_op.hardsigmoid.4.0")
|
||||
"Add.137" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.42", "conv2d_160.w_0", "p2o.pd_op.conv2d.37.0_bias")
|
||||
"p2o.pd_op.gelu.11.0" = Gelu <approximate: string = "none"> ("Add.137")
|
||||
"Add.141" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.11.0", "conv2d_161.w_0", "p2o.pd_op.conv2d.38.0_bias")
|
||||
["Add.142"] "Add.143" = Add ("Mul.42", "Add.141")
|
||||
"Add.145" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.143", "conv2d_163.w_0", "p2o.pd_op.depthwise_conv2d.12.0_bias")
|
||||
"Add.147" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.145", "conv2d_164.w_0", "p2o.pd_op.conv2d.39.0_bias")
|
||||
"p2o.pd_op.gelu.12.0" = Gelu <approximate: string = "none"> ("Add.147")
|
||||
"Add.151" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.12.0", "conv2d_165.w_0", "p2o.pd_op.conv2d.40.0_bias")
|
||||
["Add.152"] "Add.153" = Add ("Add.145", "Add.151")
|
||||
["Conv.54"] "p2o.pd_op.conv2d.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.153", "conv2d_94.w_0")
|
||||
["GlobalAveragePool.0"] "p2o.pd_op.pool2d.1.0" = GlobalAveragePool ("p2o.pd_op.conv2d.41.0")
|
||||
["Conv.57"] "p2o.pd_op.conv2d.44.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.121", "conv2d_84.w_0")
|
||||
["GlobalAveragePool.1"] "p2o.pd_op.pool2d.2.0" = GlobalAveragePool ("p2o.pd_op.conv2d.44.0")
|
||||
["Conv.60"] "p2o.pd_op.conv2d.47.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.65", "conv2d_74.w_0")
|
||||
["GlobalAveragePool.2"] "p2o.pd_op.pool2d.3.0" = GlobalAveragePool ("p2o.pd_op.conv2d.47.0")
|
||||
["Conv.63"] "p2o.pd_op.conv2d.50.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.33", "conv2d_64.w_0")
|
||||
["GlobalAveragePool.3"] "p2o.pd_op.pool2d.4.0" = GlobalAveragePool ("p2o.pd_op.conv2d.50.0")
|
||||
se_group0_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.1.0", "p2o.pd_op.pool2d.2.0", "p2o.pd_op.pool2d.3.0", "p2o.pd_op.pool2d.4.0")
|
||||
se_group0_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_pooled, se_group0_down1, se_group0_down2)
|
||||
se_group0_relu = Relu (se_group0_down)
|
||||
se_group0_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_relu, se_group0_up1, se_group0_up2)
|
||||
se_group0_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group0_up)
|
||||
"se_group0_p2o.pd_op.hardsigmoid.5.0", "se_group0_p2o.pd_op.hardsigmoid.6.0", "se_group0_p2o.pd_op.hardsigmoid.7.0", "se_group0_p2o.pd_op.hardsigmoid.8.0" = Split <axis: int = 1> (se_group0_gates, se_group0_sizes)
|
||||
val_0 = Add ("se_group0_p2o.pd_op.hardsigmoid.5.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.159" = Mul ("p2o.pd_op.conv2d.41.0", val_0)
|
||||
val_1 = Add ("se_group0_p2o.pd_op.hardsigmoid.6.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.165" = Mul ("p2o.pd_op.conv2d.44.0", val_1)
|
||||
val_2 = Add ("se_group0_p2o.pd_op.hardsigmoid.7.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.171" = Mul ("p2o.pd_op.conv2d.47.0", val_2)
|
||||
val_3 = Add ("se_group0_p2o.pd_op.hardsigmoid.8.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.177" = Mul ("p2o.pd_op.conv2d.50.0", val_3)
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.159", "helper.constant.40", "helper.constant.39")
|
||||
["Add.178"] "Add.179" = Add ("Add.165", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.179", "helper.constant.40", "helper.constant.39")
|
||||
["Add.180"] "Add.181" = Add ("Add.171", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.181", "helper.constant.40", "helper.constant.39")
|
||||
["Add.182"] "Add.183" = Add ("Add.177", "p2o.pd_op.nearest_interp.2.0")
|
||||
"Add.185" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.159", "conv2d_169.w_0", "p2o.pd_op.depthwise_conv2d.13.0_bias")
|
||||
["Conv.67"] "p2o.pd_op.conv2d.53.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.185", "conv2d_101.w_0")
|
||||
["GlobalAveragePool.4"] "p2o.pd_op.pool2d.5.0" = GlobalAveragePool ("p2o.pd_op.conv2d.53.0")
|
||||
"Add.193" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.179", "conv2d_168.w_0", "p2o.pd_op.depthwise_conv2d.14.0_bias")
|
||||
["Conv.71"] "p2o.pd_op.conv2d.56.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.193", "conv2d_91.w_0")
|
||||
["GlobalAveragePool.5"] "p2o.pd_op.pool2d.6.0" = GlobalAveragePool ("p2o.pd_op.conv2d.56.0")
|
||||
"Add.201" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.181", "conv2d_167.w_0", "p2o.pd_op.depthwise_conv2d.15.0_bias")
|
||||
["Conv.75"] "p2o.pd_op.conv2d.59.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.201", "conv2d_81.w_0")
|
||||
["GlobalAveragePool.6"] "p2o.pd_op.pool2d.7.0" = GlobalAveragePool ("p2o.pd_op.conv2d.59.0")
|
||||
"Add.209" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [7, 7], pads: ints = [3, 3, 3, 3], strides: ints = [1, 1]> ("Add.183", "conv2d_166.w_0", "p2o.pd_op.depthwise_conv2d.16.0_bias")
|
||||
["Conv.79"] "p2o.pd_op.conv2d.62.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.209", "conv2d_71.w_0")
|
||||
["GlobalAveragePool.7"] "p2o.pd_op.pool2d.8.0" = GlobalAveragePool ("p2o.pd_op.conv2d.62.0")
|
||||
se_group1_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.5.0", "p2o.pd_op.pool2d.6.0", "p2o.pd_op.pool2d.7.0", "p2o.pd_op.pool2d.8.0")
|
||||
se_group1_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_pooled, se_group1_down1, se_group1_down2)
|
||||
se_group1_relu = Relu (se_group1_down)
|
||||
se_group1_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_relu, se_group1_up1, se_group1_up2)
|
||||
se_group1_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group1_up)
|
||||
"se_group1_p2o.pd_op.hardsigmoid.9.0", "se_group1_p2o.pd_op.hardsigmoid.10.0", "se_group1_p2o.pd_op.hardsigmoid.11.0", "se_group1_p2o.pd_op.hardsigmoid.12.0" = Split <axis: int = 1> (se_group1_gates, se_group1_sizes)
|
||||
val_4 = Add ("se_group1_p2o.pd_op.hardsigmoid.9.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.191" = Mul ("p2o.pd_op.conv2d.53.0", val_4)
|
||||
val_5 = Add ("se_group1_p2o.pd_op.hardsigmoid.10.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.199" = Mul ("p2o.pd_op.conv2d.56.0", val_5)
|
||||
val_6 = Add ("se_group1_p2o.pd_op.hardsigmoid.11.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.207" = Mul ("p2o.pd_op.conv2d.59.0", val_6)
|
||||
val_7 = Add ("se_group1_p2o.pd_op.hardsigmoid.12.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.215" = Mul ("p2o.pd_op.conv2d.62.0", val_7)
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.191", "helper.constant.40", "helper.constant.45")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.199", "helper.constant.40", "helper.constant.47")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.207", "helper.constant.40", "helper.constant.39")
|
||||
["Concat.2"] "Concat.3" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.215")
|
||||
"Add.217" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.3", "conv2d_170.w_0", "p2o.pd_op.conv2d.65.0_bias")
|
||||
["Relu.18"] "p2o.pd_op.relu.18.0" = Relu ("Add.217")
|
||||
"Add.219" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.18.0", "auto.cast.95", "ConvTranspose.1_bias")
|
||||
["Relu.19"] "p2o.pd_op.relu.19.0" = Relu ("Add.219")
|
||||
"Add.221" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.19.0", "auto.cast.98", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] fetch_name_0 = Sigmoid ("Add.221")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
ConvTranspose.1_bias FLOAT[24] bb27bed0521e
|
||||
ConvTranspose.3_bias FLOAT[1] 24a801dd7a74
|
||||
_v_680 INT64[2] fe6d3d3bb5dd
|
||||
auto.cast.95 FLOAT[24,24,2,2] a1ba09ff931c
|
||||
auto.cast.98 FLOAT[24,1,2,2] 70fd5d859bf3
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_101.w_0 FLOAT[24,96,1,1] ff50c2a77482
|
||||
conv2d_112.w_0 FLOAT[24,3,3,3] 7ab66000d821
|
||||
conv2d_113.w_0 FLOAT[12,24,2,2] 409f7b590cdb
|
||||
conv2d_114.w_0 FLOAT[24,12,2,2] 3b8d53915569
|
||||
conv2d_115.w_0 FLOAT[24,48,3,3] 699a14b3a672
|
||||
conv2d_116.w_0 FLOAT[48,24,1,1] 18f9782fec66
|
||||
conv2d_118.w_0 FLOAT[48,1,3,3] 14caca75eccb
|
||||
conv2d_119.w_0 FLOAT[96,48,1,1] 25c2c00f5320
|
||||
conv2d_120.w_0 FLOAT[48,96,1,1] a75cc3f79592
|
||||
conv2d_122.w_0 FLOAT[48,1,3,3] ea65c8c5f547
|
||||
conv2d_123.w_0 FLOAT[96,48,1,1] d2af3cf57510
|
||||
conv2d_124.w_0 FLOAT[48,96,1,1] 1fa028e4834e
|
||||
conv2d_125.w_0 FLOAT[48,1,3,3] 6ad656e70cd1
|
||||
conv2d_126.w_0 FLOAT[96,48,1,1] 49c9091e1a21
|
||||
conv2d_127.w_0 FLOAT[96,96,1,1] d53510264579
|
||||
conv2d_129.w_0 FLOAT[96,1,3,3] c95c2e93cc9d
|
||||
conv2d_130.w_0 FLOAT[192,96,1,1] c045f2fb0e83
|
||||
conv2d_131.w_0 FLOAT[96,192,1,1] e8cda567ae96
|
||||
conv2d_133.w_0 FLOAT[96,1,3,3] 82261f0aae85
|
||||
conv2d_134.w_0 FLOAT[192,96,1,1] c0d1a950593f
|
||||
conv2d_135.w_0 FLOAT[96,192,1,1] 149ec1202e77
|
||||
conv2d_136.w_0 FLOAT[96,1,3,3] 79fa22938743
|
||||
conv2d_137.w_0 FLOAT[192,96,1,1] e9ce0320b439
|
||||
conv2d_138.w_0 FLOAT[192,192,1,1] 029941e4fa35
|
||||
conv2d_140.w_0 FLOAT[192,1,3,3] 0dd3656caf60
|
||||
conv2d_141.w_0 FLOAT[384,192,1,1] 2615ae625e80
|
||||
conv2d_142.w_0 FLOAT[192,384,1,1] d8b832788bc6
|
||||
conv2d_144.w_0 FLOAT[192,1,3,3] d0c9831a2e02
|
||||
conv2d_145.w_0 FLOAT[384,192,1,1] ce7b1b88d243
|
||||
conv2d_146.w_0 FLOAT[192,384,1,1] 44bbd068c954
|
||||
conv2d_148.w_0 FLOAT[192,1,3,3] 0a0cbeec90cd
|
||||
conv2d_149.w_0 FLOAT[384,192,1,1] d981ac094ea4
|
||||
conv2d_150.w_0 FLOAT[192,384,1,1] bb435884b12f
|
||||
conv2d_152.w_0 FLOAT[192,1,3,3] 0d6586c94498
|
||||
conv2d_153.w_0 FLOAT[384,192,1,1] bf8dad61e8a7
|
||||
conv2d_154.w_0 FLOAT[192,384,1,1] f42675b37d3c
|
||||
conv2d_155.w_0 FLOAT[192,1,3,3] 701f163f38d5
|
||||
conv2d_156.w_0 FLOAT[384,192,1,1] 66d4ccfc0880
|
||||
conv2d_157.w_0 FLOAT[384,384,1,1] 3a6b8fea1944
|
||||
conv2d_159.w_0 FLOAT[384,1,3,3] 10e6a66b2b48
|
||||
conv2d_160.w_0 FLOAT[768,384,1,1] 084b1182bae5
|
||||
conv2d_161.w_0 FLOAT[384,768,1,1] ec7a23a264a1
|
||||
conv2d_163.w_0 FLOAT[384,1,3,3] 61d410320a15
|
||||
conv2d_164.w_0 FLOAT[768,384,1,1] 2ae146ddf99e
|
||||
conv2d_165.w_0 FLOAT[384,768,1,1] be7968dd5732
|
||||
conv2d_166.w_0 FLOAT[96,1,7,7] e7ad3d975d57
|
||||
conv2d_167.w_0 FLOAT[96,1,7,7] 99dfc040a6f8
|
||||
conv2d_168.w_0 FLOAT[96,1,7,7] 271ea890b28a
|
||||
conv2d_169.w_0 FLOAT[96,1,7,7] f097d3d79e11
|
||||
conv2d_170.w_0 FLOAT[24,96,3,3] 0065a3f984c6
|
||||
conv2d_20.w_0 FLOAT[24,96,1,1] a4f89b61bef6
|
||||
conv2d_21.w_0 FLOAT[96,24,1,1] cf404c262872
|
||||
conv2d_33.w_0 FLOAT[48,192,1,1] f30b28999f13
|
||||
conv2d_34.w_0 FLOAT[192,48,1,1] ba16586b29d2
|
||||
conv2d_43.w_0 FLOAT[48,192,1,1] 3a90e66ffc7a
|
||||
conv2d_44.w_0 FLOAT[192,48,1,1] a5416b2a84aa
|
||||
conv2d_56.w_0 FLOAT[96,384,1,1] 5593f987bb53
|
||||
conv2d_57.w_0 FLOAT[384,96,1,1] c82a00253076
|
||||
conv2d_64.w_0 FLOAT[96,48,1,1] ecd5a4ddcea7
|
||||
conv2d_7.w_0 FLOAT[12,48,1,1] 9ea7335d0b78
|
||||
conv2d_71.w_0 FLOAT[24,96,1,1] 9c60636dd501
|
||||
conv2d_74.w_0 FLOAT[96,96,1,1] 0612ef7d2a72
|
||||
conv2d_8.w_0 FLOAT[48,12,1,1] 28ee9876167c
|
||||
conv2d_81.w_0 FLOAT[24,96,1,1] a82b6ac75f28
|
||||
conv2d_84.w_0 FLOAT[96,192,1,1] 8449e9496fd9
|
||||
conv2d_91.w_0 FLOAT[24,96,1,1] 8db11eb4074b
|
||||
conv2d_94.w_0 FLOAT[96,384,1,1] df47d9bef3e2
|
||||
helper.constant.39 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.40 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.45 FLOAT[4] cf5451a623be
|
||||
helper.constant.47 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
p2o.pd_op.conv2d.0.0_bias FLOAT[24] 080ff131f1b4
|
||||
p2o.pd_op.conv2d.1.0_bias FLOAT[12] fb44a3dbcec3
|
||||
p2o.pd_op.conv2d.10.0_bias FLOAT[48] f03f5544013b
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[96] e8fc8842fce1
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[96] fafc821c2deb
|
||||
p2o.pd_op.conv2d.13.0_bias FLOAT[24] 542b37776115
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[96] 43bf1d4f2934
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[192] e75d4c5dd209
|
||||
p2o.pd_op.conv2d.16.0_bias FLOAT[96] b90f5f02ea7d
|
||||
p2o.pd_op.conv2d.17.0_bias FLOAT[192] 970f74a8465e
|
||||
p2o.pd_op.conv2d.18.0_bias FLOAT[96] 74b51174478c
|
||||
p2o.pd_op.conv2d.19.0_bias FLOAT[192] d93512b7341b
|
||||
p2o.pd_op.conv2d.2.0_bias FLOAT[24] ace178c37ca9
|
||||
p2o.pd_op.conv2d.20.0_bias FLOAT[192] 46ead826ff45
|
||||
p2o.pd_op.conv2d.21.0_bias FLOAT[48] dbb2745138ae
|
||||
p2o.pd_op.conv2d.22.0_bias FLOAT[192] f685dfdc1cb0
|
||||
p2o.pd_op.conv2d.23.0_bias FLOAT[384] fc93cf357922
|
||||
p2o.pd_op.conv2d.24.0_bias FLOAT[192] 789a74fa92a8
|
||||
p2o.pd_op.conv2d.25.0_bias FLOAT[384] f7da5c7e92ad
|
||||
p2o.pd_op.conv2d.26.0_bias FLOAT[192] 80e854616b1d
|
||||
p2o.pd_op.conv2d.27.0_bias FLOAT[48] 06050b48ae86
|
||||
p2o.pd_op.conv2d.28.0_bias FLOAT[192] 1e6b6f3fa5d7
|
||||
p2o.pd_op.conv2d.29.0_bias FLOAT[384] e22e1c63c711
|
||||
p2o.pd_op.conv2d.3.0_bias FLOAT[24] 5e76358415dd
|
||||
p2o.pd_op.conv2d.30.0_bias FLOAT[192] aba7f93b697e
|
||||
p2o.pd_op.conv2d.31.0_bias FLOAT[384] aa359f729e08
|
||||
p2o.pd_op.conv2d.32.0_bias FLOAT[192] 6152ba83d44a
|
||||
p2o.pd_op.conv2d.33.0_bias FLOAT[384] 642e07251477
|
||||
p2o.pd_op.conv2d.34.0_bias FLOAT[384] 8f2a7f18d892
|
||||
p2o.pd_op.conv2d.35.0_bias FLOAT[96] 2dfacf20434a
|
||||
p2o.pd_op.conv2d.36.0_bias FLOAT[384] 00cf8a271ea5
|
||||
p2o.pd_op.conv2d.37.0_bias FLOAT[768] 8941b5e8768f
|
||||
p2o.pd_op.conv2d.38.0_bias FLOAT[384] 13d024f6018e
|
||||
p2o.pd_op.conv2d.39.0_bias FLOAT[768] e2a65643caf4
|
||||
p2o.pd_op.conv2d.4.0_bias FLOAT[48] 6a5e84e06010
|
||||
p2o.pd_op.conv2d.40.0_bias FLOAT[384] 11630665d435
|
||||
p2o.pd_op.conv2d.5.0_bias FLOAT[12] 072bcd13597b
|
||||
p2o.pd_op.conv2d.6.0_bias FLOAT[48] 27746617c6c0
|
||||
p2o.pd_op.conv2d.65.0_bias FLOAT[24] 66ae74136e7d
|
||||
p2o.pd_op.conv2d.7.0_bias FLOAT[96] 240e170586e4
|
||||
p2o.pd_op.conv2d.8.0_bias FLOAT[48] 69179daadcc4
|
||||
p2o.pd_op.conv2d.9.0_bias FLOAT[96] 5ba255267b85
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias FLOAT[48] c7c2ddf18b26
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias FLOAT[48] 875330127b20
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias FLOAT[192] dc9604ab84cb
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias FLOAT[384] 6519852ced86
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias FLOAT[384] 8eaa2604be84
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias FLOAT[96] d21bee60e6c4
|
||||
p2o.pd_op.depthwise_conv2d.14.0_bias FLOAT[96] d0e2be8bf9d4
|
||||
p2o.pd_op.depthwise_conv2d.15.0_bias FLOAT[96] dc764011e68e
|
||||
p2o.pd_op.depthwise_conv2d.16.0_bias FLOAT[96] 020d5df9f122
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias FLOAT[48] 6432a104355b
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias FLOAT[96] f0247c5d388e
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias FLOAT[96] e015265be367
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias FLOAT[96] 698eaf9d5bd4
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias FLOAT[192] 7a1a2157ce33
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias FLOAT[192] 0f62183d7b8e
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias FLOAT[192] 29bf164403a9
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias FLOAT[192] 8c35a49e1a9a
|
||||
p2o.pd_op.hardsigmoid.5.0_one FLOAT[] e00e5eb94441
|
||||
se_group0_down1 FLOAT[96,96,1,1] 6fad60f053f8
|
||||
se_group0_down2 FLOAT[96] b78e6150eaaa
|
||||
se_group0_sizes INT64[4] 4bb249469bee
|
||||
se_group0_up1 FLOAT[384,24,1,1] 932850ac08d0
|
||||
se_group0_up2 FLOAT[384] f69393803114
|
||||
se_group1_down1 FLOAT[24,24,1,1] 24ff7d4b4dac
|
||||
se_group1_down2 FLOAT[24] 3844f028fb3e
|
||||
se_group1_sizes INT64[4] 5c995dc6a0ef
|
||||
se_group1_up1 FLOAT[96,6,1,1] d5eeb48adccd
|
||||
se_group1_up2 FLOAT[96] 265ea2dc4538
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,508 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,16,unk__0,unk__1] "Add.1"
|
||||
float[batch,16,1,1] "Add.101"
|
||||
float[batch,64,1,1] "Add.103"
|
||||
float[batch,128,unk__50,unk__51] "Add.105"
|
||||
float[batch,64,unk__50,unk__51] "Add.109"
|
||||
float[batch,32,unk__8,unk__9] "Add.11"
|
||||
float[batch,64,unk__50,unk__51] "Add.111"
|
||||
float[batch,64,unk__50,unk__51] "Add.113"
|
||||
float[batch,128,unk__50,unk__51] "Add.115"
|
||||
float[batch,64,unk__50,unk__51] "Add.119"
|
||||
float[batch,64,unk__50,unk__51] "Add.121"
|
||||
float[batch,64,unk__88,unk__89] "Add.123"
|
||||
float[batch,128,unk__88,unk__89] "Add.125"
|
||||
float[batch,160,unk__88,unk__89] "Add.129"
|
||||
float[batch,8,1,1] "Add.13"
|
||||
float[batch,160,unk__88,unk__89] "Add.131"
|
||||
float[batch,40,1,1] "Add.133"
|
||||
float[batch,160,1,1] "Add.135"
|
||||
float[batch,320,unk__88,unk__89] "Add.137"
|
||||
float[batch,160,unk__88,unk__89] "Add.141"
|
||||
float[batch,160,unk__88,unk__89] "Add.143"
|
||||
float[batch,160,unk__88,unk__89] "Add.145"
|
||||
float[batch,320,unk__88,unk__89] "Add.147"
|
||||
float[batch,32,1,1] "Add.15"
|
||||
float[batch,160,unk__88,unk__89] "Add.151"
|
||||
float[batch,160,unk__88,unk__89] "Add.153"
|
||||
float[batch,64,unk__88,unk__89] "Add.159"
|
||||
float[batch,64,unk__50,unk__51] "Add.165"
|
||||
float[batch,64,unk__8,unk__9] "Add.17"
|
||||
float[batch,64,unk__28,unk__29] "Add.171"
|
||||
float[batch,64,unk__8,unk__9] "Add.177"
|
||||
float[batch,64,unk__50,unk__51] "Add.179"
|
||||
float[batch,64,unk__28,unk__29] "Add.181"
|
||||
float[batch,64,unk__8,unk__9] "Add.183"
|
||||
float[batch,64,unk__88,unk__89] "Add.185"
|
||||
float[batch,16,unk__88,unk__89] "Add.191"
|
||||
float[batch,64,unk__50,unk__51] "Add.193"
|
||||
float[batch,16,unk__50,unk__51] "Add.199"
|
||||
float[batch,64,unk__28,unk__29] "Add.201"
|
||||
float[batch,16,unk__28,unk__29] "Add.207"
|
||||
float[batch,64,unk__8,unk__9] "Add.209"
|
||||
float[batch,32,unk__8,unk__9] "Add.21"
|
||||
float[batch,16,unk__8,unk__9] "Add.215"
|
||||
float[batch,16,unk__8,unk__9] "Add.217"
|
||||
float[batch,16,unk__0,unk__1] "Add.219"
|
||||
float[batch,1,height,width] "Add.221"
|
||||
float[batch,32,unk__8,unk__9] "Add.23"
|
||||
float[batch,32,unk__8,unk__9] "Add.25"
|
||||
float[batch,64,unk__8,unk__9] "Add.27"
|
||||
float[batch,8,unk__0,unk__1] "Add.3"
|
||||
float[batch,32,unk__8,unk__9] "Add.31"
|
||||
float[batch,32,unk__8,unk__9] "Add.33"
|
||||
float[batch,32,unk__28,unk__29] "Add.35"
|
||||
float[batch,64,unk__28,unk__29] "Add.37"
|
||||
float[batch,48,unk__28,unk__29] "Add.41"
|
||||
float[batch,48,unk__28,unk__29] "Add.43"
|
||||
float[batch,12,1,1] "Add.45"
|
||||
float[batch,48,1,1] "Add.47"
|
||||
float[batch,96,unk__28,unk__29] "Add.49"
|
||||
float[batch,16,unk__0,unk__1] "Add.5"
|
||||
float[batch,48,unk__28,unk__29] "Add.53"
|
||||
float[batch,48,unk__28,unk__29] "Add.55"
|
||||
float[batch,48,unk__28,unk__29] "Add.57"
|
||||
float[batch,96,unk__28,unk__29] "Add.59"
|
||||
float[batch,48,unk__28,unk__29] "Add.63"
|
||||
float[batch,48,unk__28,unk__29] "Add.65"
|
||||
float[batch,48,unk__50,unk__51] "Add.67"
|
||||
float[batch,96,unk__50,unk__51] "Add.69"
|
||||
float[batch,16,unk__8,unk__9] "Add.7"
|
||||
float[batch,64,unk__50,unk__51] "Add.73"
|
||||
float[batch,64,unk__50,unk__51] "Add.75"
|
||||
float[batch,16,1,1] "Add.77"
|
||||
float[batch,64,1,1] "Add.79"
|
||||
float[batch,128,unk__50,unk__51] "Add.81"
|
||||
float[batch,64,unk__50,unk__51] "Add.85"
|
||||
float[batch,64,unk__50,unk__51] "Add.87"
|
||||
float[batch,64,unk__50,unk__51] "Add.89"
|
||||
float[batch,32,unk__8,unk__9] "Add.9"
|
||||
float[batch,128,unk__50,unk__51] "Add.91"
|
||||
float[batch,64,unk__50,unk__51] "Add.95"
|
||||
float[batch,64,unk__50,unk__51] "Add.97"
|
||||
float[batch,64,unk__50,unk__51] "Add.99"
|
||||
float[batch,32,unk__0,unk__1] "Concat.1"
|
||||
float[batch,64,unk__8,unk__9] "Concat.3"
|
||||
float[batch,32,unk__8,unk__9] "Mul.1"
|
||||
float[batch,48,unk__28,unk__29] "Mul.12"
|
||||
float[batch,64,unk__50,unk__51] "Mul.23"
|
||||
float[batch,64,unk__50,unk__51] "Mul.31"
|
||||
float[batch,160,unk__88,unk__89] "Mul.42"
|
||||
float[batch,32,1,1] "ReduceMean.1"
|
||||
float[batch,48,1,1] "ReduceMean.3"
|
||||
float[batch,64,1,1] "ReduceMean.5"
|
||||
float[batch,64,1,1] "ReduceMean.7"
|
||||
float[batch,160,1,1] "ReduceMean.9"
|
||||
float[batch,64,unk__88,unk__89] "p2o.pd_op.conv2d.41.0"
|
||||
float[batch,64,unk__50,unk__51] "p2o.pd_op.conv2d.44.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.conv2d.47.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.conv2d.50.0"
|
||||
float[batch,16,unk__88,unk__89] "p2o.pd_op.conv2d.53.0"
|
||||
float[batch,16,unk__50,unk__51] "p2o.pd_op.conv2d.56.0"
|
||||
float[batch,16,unk__28,unk__29] "p2o.pd_op.conv2d.59.0"
|
||||
float[batch,16,unk__8,unk__9] "p2o.pd_op.conv2d.62.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.gelu.0.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.gelu.1.0"
|
||||
float[batch,128,unk__88,unk__89] "p2o.pd_op.gelu.10.0"
|
||||
float[batch,320,unk__88,unk__89] "p2o.pd_op.gelu.11.0"
|
||||
float[batch,320,unk__88,unk__89] "p2o.pd_op.gelu.12.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.gelu.2.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.gelu.3.0"
|
||||
float[batch,96,unk__28,unk__29] "p2o.pd_op.gelu.4.0"
|
||||
float[batch,96,unk__50,unk__51] "p2o.pd_op.gelu.5.0"
|
||||
float[batch,128,unk__50,unk__51] "p2o.pd_op.gelu.6.0"
|
||||
float[batch,128,unk__50,unk__51] "p2o.pd_op.gelu.7.0"
|
||||
float[batch,128,unk__50,unk__51] "p2o.pd_op.gelu.8.0"
|
||||
float[batch,128,unk__50,unk__51] "p2o.pd_op.gelu.9.0"
|
||||
float[batch,32,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,48,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,64,1,1] "p2o.pd_op.hardsigmoid.2.0"
|
||||
float[batch,64,1,1] "p2o.pd_op.hardsigmoid.3.0"
|
||||
float[batch,160,1,1] "p2o.pd_op.hardsigmoid.4.0"
|
||||
float[batch,64,unk__50,unk__51] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,64,unk__28,unk__29] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,64,unk__8,unk__9] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,16,unk__8,unk__9] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,16,unk__8,unk__9] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,16,unk__8,unk__9] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,64,1,1] "p2o.pd_op.pool2d.1.0"
|
||||
float[batch,64,1,1] "p2o.pd_op.pool2d.2.0"
|
||||
float[batch,64,1,1] "p2o.pd_op.pool2d.3.0"
|
||||
float[batch,64,1,1] "p2o.pd_op.pool2d.4.0"
|
||||
float[batch,16,1,1] "p2o.pd_op.pool2d.5.0"
|
||||
float[batch,16,1,1] "p2o.pd_op.pool2d.6.0"
|
||||
float[batch,16,1,1] "p2o.pd_op.pool2d.7.0"
|
||||
float[batch,16,1,1] "p2o.pd_op.pool2d.8.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,8,unk__0,unk__1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,16,unk__8,unk__9] "p2o.pd_op.relu.18.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.relu.19.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.relu.2.0"
|
||||
float[batch,16,unk__8,unk__9] "p2o.pd_op.relu.3.0"
|
||||
float[batch,32,unk__8,unk__9] "p2o.pd_op.relu.4.0"
|
||||
float[batch,8,1,1] "p2o.pd_op.relu.5.0"
|
||||
float[batch,12,1,1] "p2o.pd_op.relu.6.0"
|
||||
float[batch,16,1,1] "p2o.pd_op.relu.7.0"
|
||||
float[batch,16,1,1] "p2o.pd_op.relu.8.0"
|
||||
float[batch,40,1,1] "p2o.pd_op.relu.9.0"
|
||||
float[batch,64,1,1] "se_group0_p2o.pd_op.hardsigmoid.5.0"
|
||||
float[batch,64,1,1] "se_group0_p2o.pd_op.hardsigmoid.6.0"
|
||||
float[batch,64,1,1] "se_group0_p2o.pd_op.hardsigmoid.7.0"
|
||||
float[batch,64,1,1] "se_group0_p2o.pd_op.hardsigmoid.8.0"
|
||||
float[batch,16,1,1] "se_group1_p2o.pd_op.hardsigmoid.10.0"
|
||||
float[batch,16,1,1] "se_group1_p2o.pd_op.hardsigmoid.11.0"
|
||||
float[batch,16,1,1] "se_group1_p2o.pd_op.hardsigmoid.12.0"
|
||||
float[batch,16,1,1] "se_group1_p2o.pd_op.hardsigmoid.9.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,64,1,1] se_group0_down
|
||||
float[batch,256,1,1] se_group0_gates
|
||||
float[batch,256,1,1] se_group0_pooled
|
||||
float[batch,64,1,1] se_group0_relu
|
||||
float[batch,256,1,1] se_group0_up
|
||||
float[batch,16,1,1] se_group1_down
|
||||
float[batch,64,1,1] se_group1_gates
|
||||
float[batch,64,1,1] se_group1_pooled
|
||||
float[batch,16,1,1] se_group1_relu
|
||||
float[batch,64,1,1] se_group1_up
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,64,1,1] val_0
|
||||
float[batch,64,1,1] val_1
|
||||
float[batch,64,1,1] val_2
|
||||
float[batch,64,1,1] val_3
|
||||
float[batch,16,1,1] val_4
|
||||
float[batch,16,1,1] val_5
|
||||
float[batch,16,1,1] val_6
|
||||
float[batch,16,1,1] val_7
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"Add.1" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_108.w_0", "p2o.pd_op.conv2d.0.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.1")
|
||||
"Add.3" = Conv <auto_pad: string = "SAME_UPPER", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_109.w_0", "p2o.pd_op.conv2d.1.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.3")
|
||||
"Add.5" = Conv <auto_pad: string = "SAME_UPPER", dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_110.w_0", "p2o.pd_op.conv2d.2.0_bias")
|
||||
["Relu.2"] "p2o.pd_op.relu.2.0" = Relu ("Add.5")
|
||||
["MaxPool.0"] "p2o.pd_op.pool2d.0.0" = MaxPool <auto_pad: string = "SAME_UPPER", ceil_mode: int = 0, kernel_shape: ints = [2, 2], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.pool2d.0.0", "p2o.pd_op.relu.2.0")
|
||||
"Add.7" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Concat.1", "conv2d_111.w_0", "p2o.pd_op.conv2d.3.0_bias")
|
||||
["Relu.3"] "p2o.pd_op.relu.3.0" = Relu ("Add.7")
|
||||
"Add.9" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.3.0", "conv2d_112.w_0", "p2o.pd_op.conv2d.4.0_bias")
|
||||
["Relu.4"] "p2o.pd_op.relu.4.0" = Relu ("Add.9")
|
||||
"Add.11" = Conv <dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.relu.4.0", "conv2d_114.w_0", "p2o.pd_op.depthwise_conv2d.0.0_bias")
|
||||
["ReduceMean.0"] "ReduceMean.1" = ReduceMean <keepdims: int = 1> ("Add.11", _v_680)
|
||||
"Add.13" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.1", "conv2d_7.w_0", "p2o.pd_op.conv2d.5.0_bias")
|
||||
["Relu.5"] "p2o.pd_op.relu.5.0" = Relu ("Add.13")
|
||||
"Add.15" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.5.0", "conv2d_8.w_0", "p2o.pd_op.conv2d.6.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.15")
|
||||
["Mul.0"] "Mul.1" = Mul ("Add.11", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.17" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.1", "conv2d_115.w_0", "p2o.pd_op.conv2d.7.0_bias")
|
||||
"p2o.pd_op.gelu.0.0" = Gelu <approximate: string = "none"> ("Add.17")
|
||||
"Add.21" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.0.0", "conv2d_116.w_0", "p2o.pd_op.conv2d.8.0_bias")
|
||||
["Add.22"] "Add.23" = Add ("Mul.1", "Add.21")
|
||||
"Add.25" = Conv <dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.23", "conv2d_118.w_0", "p2o.pd_op.depthwise_conv2d.1.0_bias")
|
||||
"Add.27" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.25", "conv2d_119.w_0", "p2o.pd_op.conv2d.9.0_bias")
|
||||
"p2o.pd_op.gelu.1.0" = Gelu <approximate: string = "none"> ("Add.27")
|
||||
"Add.31" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.1.0", "conv2d_120.w_0", "p2o.pd_op.conv2d.10.0_bias")
|
||||
["Add.32"] "Add.33" = Add ("Add.25", "Add.31")
|
||||
"Add.35" = Conv <dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.33", "conv2d_121.w_0", "p2o.pd_op.depthwise_conv2d.2.0_bias")
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.35", "conv2d_122.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
"p2o.pd_op.gelu.2.0" = Gelu <approximate: string = "none"> ("Add.37")
|
||||
"Add.41" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.2.0", "conv2d_123.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
"Add.43" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.41", "conv2d_125.w_0", "p2o.pd_op.depthwise_conv2d.3.0_bias")
|
||||
["ReduceMean.2"] "ReduceMean.3" = ReduceMean <keepdims: int = 1> ("Add.43", _v_680)
|
||||
"Add.45" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.3", "conv2d_20.w_0", "p2o.pd_op.conv2d.13.0_bias")
|
||||
["Relu.6"] "p2o.pd_op.relu.6.0" = Relu ("Add.45")
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.6.0", "conv2d_21.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.47")
|
||||
["Mul.11"] "Mul.12" = Mul ("Add.43", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.49" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.12", "conv2d_126.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
"p2o.pd_op.gelu.3.0" = Gelu <approximate: string = "none"> ("Add.49")
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.3.0", "conv2d_127.w_0", "p2o.pd_op.conv2d.16.0_bias")
|
||||
["Add.54"] "Add.55" = Add ("Mul.12", "Add.53")
|
||||
"Add.57" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.55", "conv2d_129.w_0", "p2o.pd_op.depthwise_conv2d.4.0_bias")
|
||||
"Add.59" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.57", "conv2d_130.w_0", "p2o.pd_op.conv2d.17.0_bias")
|
||||
"p2o.pd_op.gelu.4.0" = Gelu <approximate: string = "none"> ("Add.59")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.4.0", "conv2d_131.w_0", "p2o.pd_op.conv2d.18.0_bias")
|
||||
["Add.64"] "Add.65" = Add ("Add.57", "Add.63")
|
||||
"Add.67" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.65", "conv2d_132.w_0", "p2o.pd_op.depthwise_conv2d.5.0_bias")
|
||||
"Add.69" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.67", "conv2d_133.w_0", "p2o.pd_op.conv2d.19.0_bias")
|
||||
"p2o.pd_op.gelu.5.0" = Gelu <approximate: string = "none"> ("Add.69")
|
||||
"Add.73" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.5.0", "conv2d_134.w_0", "p2o.pd_op.conv2d.20.0_bias")
|
||||
"Add.75" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.73", "conv2d_136.w_0", "p2o.pd_op.depthwise_conv2d.6.0_bias")
|
||||
["ReduceMean.4"] "ReduceMean.5" = ReduceMean <keepdims: int = 1> ("Add.75", _v_680)
|
||||
"Add.77" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.5", "conv2d_33.w_0", "p2o.pd_op.conv2d.21.0_bias")
|
||||
["Relu.7"] "p2o.pd_op.relu.7.0" = Relu ("Add.77")
|
||||
"Add.79" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.7.0", "conv2d_34.w_0", "p2o.pd_op.conv2d.22.0_bias")
|
||||
["HardSigmoid.2"] "p2o.pd_op.hardsigmoid.2.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.79")
|
||||
["Mul.22"] "Mul.23" = Mul ("Add.75", "p2o.pd_op.hardsigmoid.2.0")
|
||||
"Add.81" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.23", "conv2d_137.w_0", "p2o.pd_op.conv2d.23.0_bias")
|
||||
"p2o.pd_op.gelu.6.0" = Gelu <approximate: string = "none"> ("Add.81")
|
||||
"Add.85" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.6.0", "conv2d_138.w_0", "p2o.pd_op.conv2d.24.0_bias")
|
||||
["Add.86"] "Add.87" = Add ("Mul.23", "Add.85")
|
||||
"Add.89" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.87", "conv2d_140.w_0", "p2o.pd_op.depthwise_conv2d.7.0_bias")
|
||||
"Add.91" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.89", "conv2d_141.w_0", "p2o.pd_op.conv2d.25.0_bias")
|
||||
"p2o.pd_op.gelu.7.0" = Gelu <approximate: string = "none"> ("Add.91")
|
||||
"Add.95" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.7.0", "conv2d_142.w_0", "p2o.pd_op.conv2d.26.0_bias")
|
||||
["Add.96"] "Add.97" = Add ("Add.89", "Add.95")
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.97", "conv2d_144.w_0", "p2o.pd_op.depthwise_conv2d.8.0_bias")
|
||||
["ReduceMean.6"] "ReduceMean.7" = ReduceMean <keepdims: int = 1> ("Add.99", _v_680)
|
||||
"Add.101" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.7", "conv2d_43.w_0", "p2o.pd_op.conv2d.27.0_bias")
|
||||
["Relu.8"] "p2o.pd_op.relu.8.0" = Relu ("Add.101")
|
||||
"Add.103" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.8.0", "conv2d_44.w_0", "p2o.pd_op.conv2d.28.0_bias")
|
||||
["HardSigmoid.3"] "p2o.pd_op.hardsigmoid.3.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.103")
|
||||
["Mul.30"] "Mul.31" = Mul ("Add.99", "p2o.pd_op.hardsigmoid.3.0")
|
||||
"Add.105" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.31", "conv2d_145.w_0", "p2o.pd_op.conv2d.29.0_bias")
|
||||
"p2o.pd_op.gelu.8.0" = Gelu <approximate: string = "none"> ("Add.105")
|
||||
"Add.109" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.8.0", "conv2d_146.w_0", "p2o.pd_op.conv2d.30.0_bias")
|
||||
["Add.110"] "Add.111" = Add ("Mul.31", "Add.109")
|
||||
"Add.113" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.111", "conv2d_148.w_0", "p2o.pd_op.depthwise_conv2d.9.0_bias")
|
||||
"Add.115" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.113", "conv2d_149.w_0", "p2o.pd_op.conv2d.31.0_bias")
|
||||
"p2o.pd_op.gelu.9.0" = Gelu <approximate: string = "none"> ("Add.115")
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.9.0", "conv2d_150.w_0", "p2o.pd_op.conv2d.32.0_bias")
|
||||
["Add.120"] "Add.121" = Add ("Add.113", "Add.119")
|
||||
"Add.123" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> ("Add.121", "conv2d_151.w_0", "p2o.pd_op.depthwise_conv2d.10.0_bias")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.123", "conv2d_152.w_0", "p2o.pd_op.conv2d.33.0_bias")
|
||||
"p2o.pd_op.gelu.10.0" = Gelu <approximate: string = "none"> ("Add.125")
|
||||
"Add.129" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.10.0", "conv2d_153.w_0", "p2o.pd_op.conv2d.34.0_bias")
|
||||
"Add.131" = Conv <dilations: ints = [1, 1], group: int = 160, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.129", "conv2d_155.w_0", "p2o.pd_op.depthwise_conv2d.11.0_bias")
|
||||
["ReduceMean.8"] "ReduceMean.9" = ReduceMean <keepdims: int = 1> ("Add.131", _v_680)
|
||||
"Add.133" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("ReduceMean.9", "conv2d_56.w_0", "p2o.pd_op.conv2d.35.0_bias")
|
||||
["Relu.9"] "p2o.pd_op.relu.9.0" = Relu ("Add.133")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.9.0", "conv2d_57.w_0", "p2o.pd_op.conv2d.36.0_bias")
|
||||
["HardSigmoid.4"] "p2o.pd_op.hardsigmoid.4.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.135")
|
||||
["Mul.41"] "Mul.42" = Mul ("Add.131", "p2o.pd_op.hardsigmoid.4.0")
|
||||
"Add.137" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.42", "conv2d_156.w_0", "p2o.pd_op.conv2d.37.0_bias")
|
||||
"p2o.pd_op.gelu.11.0" = Gelu <approximate: string = "none"> ("Add.137")
|
||||
"Add.141" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.11.0", "conv2d_157.w_0", "p2o.pd_op.conv2d.38.0_bias")
|
||||
["Add.142"] "Add.143" = Add ("Mul.42", "Add.141")
|
||||
"Add.145" = Conv <dilations: ints = [1, 1], group: int = 160, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.143", "conv2d_159.w_0", "p2o.pd_op.depthwise_conv2d.12.0_bias")
|
||||
"Add.147" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.145", "conv2d_160.w_0", "p2o.pd_op.conv2d.39.0_bias")
|
||||
"p2o.pd_op.gelu.12.0" = Gelu <approximate: string = "none"> ("Add.147")
|
||||
"Add.151" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.gelu.12.0", "conv2d_161.w_0", "p2o.pd_op.conv2d.40.0_bias")
|
||||
["Add.152"] "Add.153" = Add ("Add.145", "Add.151")
|
||||
["Conv.54"] "p2o.pd_op.conv2d.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.153", "conv2d_91.w_0")
|
||||
["GlobalAveragePool.0"] "p2o.pd_op.pool2d.1.0" = GlobalAveragePool ("p2o.pd_op.conv2d.41.0")
|
||||
["Conv.57"] "p2o.pd_op.conv2d.44.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.121", "conv2d_82.w_0")
|
||||
["GlobalAveragePool.1"] "p2o.pd_op.pool2d.2.0" = GlobalAveragePool ("p2o.pd_op.conv2d.44.0")
|
||||
["Conv.60"] "p2o.pd_op.conv2d.47.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.65", "conv2d_73.w_0")
|
||||
["GlobalAveragePool.2"] "p2o.pd_op.pool2d.3.0" = GlobalAveragePool ("p2o.pd_op.conv2d.47.0")
|
||||
["Conv.63"] "p2o.pd_op.conv2d.50.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.33", "conv2d_64.w_0")
|
||||
["GlobalAveragePool.3"] "p2o.pd_op.pool2d.4.0" = GlobalAveragePool ("p2o.pd_op.conv2d.50.0")
|
||||
se_group0_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.1.0", "p2o.pd_op.pool2d.2.0", "p2o.pd_op.pool2d.3.0", "p2o.pd_op.pool2d.4.0")
|
||||
se_group0_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_pooled, se_group0_down1, se_group0_down2)
|
||||
se_group0_relu = Relu (se_group0_down)
|
||||
se_group0_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_relu, se_group0_up1, se_group0_up2)
|
||||
se_group0_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group0_up)
|
||||
"se_group0_p2o.pd_op.hardsigmoid.5.0", "se_group0_p2o.pd_op.hardsigmoid.6.0", "se_group0_p2o.pd_op.hardsigmoid.7.0", "se_group0_p2o.pd_op.hardsigmoid.8.0" = Split <axis: int = 1> (se_group0_gates, se_group0_sizes)
|
||||
val_0 = Add ("se_group0_p2o.pd_op.hardsigmoid.5.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.159" = Mul ("p2o.pd_op.conv2d.41.0", val_0)
|
||||
val_1 = Add ("se_group0_p2o.pd_op.hardsigmoid.6.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.165" = Mul ("p2o.pd_op.conv2d.44.0", val_1)
|
||||
val_2 = Add ("se_group0_p2o.pd_op.hardsigmoid.7.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.171" = Mul ("p2o.pd_op.conv2d.47.0", val_2)
|
||||
val_3 = Add ("se_group0_p2o.pd_op.hardsigmoid.8.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.177" = Mul ("p2o.pd_op.conv2d.50.0", val_3)
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.159", "helper.constant.40", "helper.constant.39")
|
||||
["Add.178"] "Add.179" = Add ("Add.165", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.179", "helper.constant.40", "helper.constant.39")
|
||||
["Add.180"] "Add.181" = Add ("Add.171", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.181", "helper.constant.40", "helper.constant.39")
|
||||
["Add.182"] "Add.183" = Add ("Add.177", "p2o.pd_op.nearest_interp.2.0")
|
||||
"Add.185" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.159", "conv2d_165.w_0", "p2o.pd_op.depthwise_conv2d.13.0_bias")
|
||||
["Conv.67"] "p2o.pd_op.conv2d.53.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.185", "conv2d_97.w_0")
|
||||
["GlobalAveragePool.4"] "p2o.pd_op.pool2d.5.0" = GlobalAveragePool ("p2o.pd_op.conv2d.53.0")
|
||||
"Add.193" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.179", "conv2d_164.w_0", "p2o.pd_op.depthwise_conv2d.14.0_bias")
|
||||
["Conv.71"] "p2o.pd_op.conv2d.56.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.193", "conv2d_88.w_0")
|
||||
["GlobalAveragePool.5"] "p2o.pd_op.pool2d.6.0" = GlobalAveragePool ("p2o.pd_op.conv2d.56.0")
|
||||
"Add.201" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.181", "conv2d_163.w_0", "p2o.pd_op.depthwise_conv2d.15.0_bias")
|
||||
["Conv.75"] "p2o.pd_op.conv2d.59.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.201", "conv2d_79.w_0")
|
||||
["GlobalAveragePool.6"] "p2o.pd_op.pool2d.7.0" = GlobalAveragePool ("p2o.pd_op.conv2d.59.0")
|
||||
"Add.209" = Conv <dilations: ints = [1, 1], group: int = 64, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> ("Add.183", "conv2d_162.w_0", "p2o.pd_op.depthwise_conv2d.16.0_bias")
|
||||
["Conv.79"] "p2o.pd_op.conv2d.62.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.209", "conv2d_70.w_0")
|
||||
["GlobalAveragePool.7"] "p2o.pd_op.pool2d.8.0" = GlobalAveragePool ("p2o.pd_op.conv2d.62.0")
|
||||
se_group1_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.5.0", "p2o.pd_op.pool2d.6.0", "p2o.pd_op.pool2d.7.0", "p2o.pd_op.pool2d.8.0")
|
||||
se_group1_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_pooled, se_group1_down1, se_group1_down2)
|
||||
se_group1_relu = Relu (se_group1_down)
|
||||
se_group1_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_relu, se_group1_up1, se_group1_up2)
|
||||
se_group1_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group1_up)
|
||||
"se_group1_p2o.pd_op.hardsigmoid.9.0", "se_group1_p2o.pd_op.hardsigmoid.10.0", "se_group1_p2o.pd_op.hardsigmoid.11.0", "se_group1_p2o.pd_op.hardsigmoid.12.0" = Split <axis: int = 1> (se_group1_gates, se_group1_sizes)
|
||||
val_4 = Add ("se_group1_p2o.pd_op.hardsigmoid.9.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.191" = Mul ("p2o.pd_op.conv2d.53.0", val_4)
|
||||
val_5 = Add ("se_group1_p2o.pd_op.hardsigmoid.10.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.199" = Mul ("p2o.pd_op.conv2d.56.0", val_5)
|
||||
val_6 = Add ("se_group1_p2o.pd_op.hardsigmoid.11.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.207" = Mul ("p2o.pd_op.conv2d.59.0", val_6)
|
||||
val_7 = Add ("se_group1_p2o.pd_op.hardsigmoid.12.0", "p2o.pd_op.hardsigmoid.5.0_one")
|
||||
"Add.215" = Mul ("p2o.pd_op.conv2d.62.0", val_7)
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.191", "helper.constant.40", "helper.constant.45")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.199", "helper.constant.40", "helper.constant.47")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.207", "helper.constant.40", "helper.constant.39")
|
||||
["Concat.2"] "Concat.3" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.215")
|
||||
"Add.217" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.3", "conv2d_166.w_0", "p2o.pd_op.conv2d.65.0_bias")
|
||||
["Relu.18"] "p2o.pd_op.relu.18.0" = Relu ("Add.217")
|
||||
"Add.219" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.18.0", "auto.cast.95", "ConvTranspose.1_bias")
|
||||
["Relu.19"] "p2o.pd_op.relu.19.0" = Relu ("Add.219")
|
||||
"Add.221" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.19.0", "auto.cast.98", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] fetch_name_0 = Sigmoid ("Add.221")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
ConvTranspose.1_bias FLOAT[16] fa6f4fb2ec85
|
||||
ConvTranspose.3_bias FLOAT[1] 6edac2444100
|
||||
_v_680 INT64[2] fe6d3d3bb5dd
|
||||
auto.cast.95 FLOAT[16,16,2,2] c97358cda6e5
|
||||
auto.cast.98 FLOAT[16,1,2,2] e18e857e713d
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_108.w_0 FLOAT[16,3,3,3] eca6bf608f40
|
||||
conv2d_109.w_0 FLOAT[8,16,2,2] 2083cd36be60
|
||||
conv2d_110.w_0 FLOAT[16,8,2,2] db900c44ceba
|
||||
conv2d_111.w_0 FLOAT[16,32,3,3] eb38ba84477d
|
||||
conv2d_112.w_0 FLOAT[32,16,1,1] d480b6f88844
|
||||
conv2d_114.w_0 FLOAT[32,1,3,3] ab6e48db4ebf
|
||||
conv2d_115.w_0 FLOAT[64,32,1,1] 0b5d48d6b13c
|
||||
conv2d_116.w_0 FLOAT[32,64,1,1] 9ee3037a3cd0
|
||||
conv2d_118.w_0 FLOAT[32,1,3,3] 0b88520f422e
|
||||
conv2d_119.w_0 FLOAT[64,32,1,1] a46019199a8f
|
||||
conv2d_120.w_0 FLOAT[32,64,1,1] bfd7f158744f
|
||||
conv2d_121.w_0 FLOAT[32,1,3,3] 52d5bdf97624
|
||||
conv2d_122.w_0 FLOAT[64,32,1,1] 1cb27d4764f2
|
||||
conv2d_123.w_0 FLOAT[48,64,1,1] ccae30d997cd
|
||||
conv2d_125.w_0 FLOAT[48,1,3,3] a05b9d30e5b4
|
||||
conv2d_126.w_0 FLOAT[96,48,1,1] ddde9cd2543f
|
||||
conv2d_127.w_0 FLOAT[48,96,1,1] de849d67ba5d
|
||||
conv2d_129.w_0 FLOAT[48,1,3,3] ffc69f35fd87
|
||||
conv2d_130.w_0 FLOAT[96,48,1,1] 8a86771fff04
|
||||
conv2d_131.w_0 FLOAT[48,96,1,1] 300fab1cad2f
|
||||
conv2d_132.w_0 FLOAT[48,1,3,3] fc43247061b4
|
||||
conv2d_133.w_0 FLOAT[96,48,1,1] 4ecc016ed32b
|
||||
conv2d_134.w_0 FLOAT[64,96,1,1] 93aa8e5ba8c8
|
||||
conv2d_136.w_0 FLOAT[64,1,3,3] d14dba93abf4
|
||||
conv2d_137.w_0 FLOAT[128,64,1,1] dc90436c2a58
|
||||
conv2d_138.w_0 FLOAT[64,128,1,1] f92b801f5a9f
|
||||
conv2d_140.w_0 FLOAT[64,1,3,3] e91cac584bb8
|
||||
conv2d_141.w_0 FLOAT[128,64,1,1] db52fdef4928
|
||||
conv2d_142.w_0 FLOAT[64,128,1,1] 679df347ff7c
|
||||
conv2d_144.w_0 FLOAT[64,1,3,3] 4173e18958e7
|
||||
conv2d_145.w_0 FLOAT[128,64,1,1] 181e051139cd
|
||||
conv2d_146.w_0 FLOAT[64,128,1,1] 1bd501bc333e
|
||||
conv2d_148.w_0 FLOAT[64,1,3,3] 2861c6252910
|
||||
conv2d_149.w_0 FLOAT[128,64,1,1] 46f13d0783d8
|
||||
conv2d_150.w_0 FLOAT[64,128,1,1] 715c7efba840
|
||||
conv2d_151.w_0 FLOAT[64,1,3,3] 22aa996618f5
|
||||
conv2d_152.w_0 FLOAT[128,64,1,1] b97536d07185
|
||||
conv2d_153.w_0 FLOAT[160,128,1,1] 03c443c4ca69
|
||||
conv2d_155.w_0 FLOAT[160,1,3,3] d355bd60d3bc
|
||||
conv2d_156.w_0 FLOAT[320,160,1,1] 4509f7bc858f
|
||||
conv2d_157.w_0 FLOAT[160,320,1,1] 9a078e80d99a
|
||||
conv2d_159.w_0 FLOAT[160,1,3,3] d65c9cf29ebc
|
||||
conv2d_160.w_0 FLOAT[320,160,1,1] f20e93714a3d
|
||||
conv2d_161.w_0 FLOAT[160,320,1,1] d4c175ef2c46
|
||||
conv2d_162.w_0 FLOAT[64,1,5,5] 419ff221d3ff
|
||||
conv2d_163.w_0 FLOAT[64,1,5,5] 8551dfd1125e
|
||||
conv2d_164.w_0 FLOAT[64,1,5,5] aa87a36a2bc9
|
||||
conv2d_165.w_0 FLOAT[64,1,5,5] 683f86e55d75
|
||||
conv2d_166.w_0 FLOAT[16,64,3,3] eba0e2b06e25
|
||||
conv2d_20.w_0 FLOAT[12,48,1,1] c172ef315b52
|
||||
conv2d_21.w_0 FLOAT[48,12,1,1] 0bec50c81a7d
|
||||
conv2d_33.w_0 FLOAT[16,64,1,1] de6f88273b1f
|
||||
conv2d_34.w_0 FLOAT[64,16,1,1] 19f7c45f3643
|
||||
conv2d_43.w_0 FLOAT[16,64,1,1] 6015deeb1470
|
||||
conv2d_44.w_0 FLOAT[64,16,1,1] 2d323e6997c3
|
||||
conv2d_56.w_0 FLOAT[40,160,1,1] ff8b4e16d2ac
|
||||
conv2d_57.w_0 FLOAT[160,40,1,1] 89be3d11a3f0
|
||||
conv2d_64.w_0 FLOAT[64,32,1,1] 3c7991e6ebf0
|
||||
conv2d_7.w_0 FLOAT[8,32,1,1] 389a0e48098c
|
||||
conv2d_70.w_0 FLOAT[16,64,1,1] 51aededda8ae
|
||||
conv2d_73.w_0 FLOAT[64,48,1,1] 29c45465492e
|
||||
conv2d_79.w_0 FLOAT[16,64,1,1] 3d08013c7b14
|
||||
conv2d_8.w_0 FLOAT[32,8,1,1] 7a82f452482e
|
||||
conv2d_82.w_0 FLOAT[64,64,1,1] 9cc6f348bcb8
|
||||
conv2d_88.w_0 FLOAT[16,64,1,1] 20cee3bcbdda
|
||||
conv2d_91.w_0 FLOAT[64,160,1,1] d3a225cd37b3
|
||||
conv2d_97.w_0 FLOAT[16,64,1,1] 079a9b743a67
|
||||
helper.constant.39 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.40 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.45 FLOAT[4] cf5451a623be
|
||||
helper.constant.47 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
p2o.pd_op.conv2d.0.0_bias FLOAT[16] 9bde77526852
|
||||
p2o.pd_op.conv2d.1.0_bias FLOAT[8] d272a0ec353a
|
||||
p2o.pd_op.conv2d.10.0_bias FLOAT[32] 5a7b77819f9e
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[64] c4421e173923
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[48] 3a389169023d
|
||||
p2o.pd_op.conv2d.13.0_bias FLOAT[12] b652db43914a
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[48] b5cc87932810
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[96] 291e429e0ccc
|
||||
p2o.pd_op.conv2d.16.0_bias FLOAT[48] bee04f62f122
|
||||
p2o.pd_op.conv2d.17.0_bias FLOAT[96] 3efd4e52177f
|
||||
p2o.pd_op.conv2d.18.0_bias FLOAT[48] 5806bf41085d
|
||||
p2o.pd_op.conv2d.19.0_bias FLOAT[96] 2f2d0d47ebf4
|
||||
p2o.pd_op.conv2d.2.0_bias FLOAT[16] d6fb0e93d477
|
||||
p2o.pd_op.conv2d.20.0_bias FLOAT[64] ee26db728ec7
|
||||
p2o.pd_op.conv2d.21.0_bias FLOAT[16] a51bf723c20f
|
||||
p2o.pd_op.conv2d.22.0_bias FLOAT[64] de5c18479c76
|
||||
p2o.pd_op.conv2d.23.0_bias FLOAT[128] 543b50b3fe29
|
||||
p2o.pd_op.conv2d.24.0_bias FLOAT[64] baa2b0a0d3de
|
||||
p2o.pd_op.conv2d.25.0_bias FLOAT[128] 2b762a2a7f04
|
||||
p2o.pd_op.conv2d.26.0_bias FLOAT[64] 98b33e508703
|
||||
p2o.pd_op.conv2d.27.0_bias FLOAT[16] f8c5aefd9d84
|
||||
p2o.pd_op.conv2d.28.0_bias FLOAT[64] 4632187aec2b
|
||||
p2o.pd_op.conv2d.29.0_bias FLOAT[128] fc8d030351ed
|
||||
p2o.pd_op.conv2d.3.0_bias FLOAT[16] 4b7a38f01b6f
|
||||
p2o.pd_op.conv2d.30.0_bias FLOAT[64] c3068963b57d
|
||||
p2o.pd_op.conv2d.31.0_bias FLOAT[128] a6bce21463b5
|
||||
p2o.pd_op.conv2d.32.0_bias FLOAT[64] 37e82172169d
|
||||
p2o.pd_op.conv2d.33.0_bias FLOAT[128] 50940d0a89d1
|
||||
p2o.pd_op.conv2d.34.0_bias FLOAT[160] 40c5f8f73609
|
||||
p2o.pd_op.conv2d.35.0_bias FLOAT[40] b159877e0014
|
||||
p2o.pd_op.conv2d.36.0_bias FLOAT[160] 6bfc4f77200b
|
||||
p2o.pd_op.conv2d.37.0_bias FLOAT[320] 46d815b9a626
|
||||
p2o.pd_op.conv2d.38.0_bias FLOAT[160] 1ab963606d6b
|
||||
p2o.pd_op.conv2d.39.0_bias FLOAT[320] a21e752d674b
|
||||
p2o.pd_op.conv2d.4.0_bias FLOAT[32] 75b1d940808d
|
||||
p2o.pd_op.conv2d.40.0_bias FLOAT[160] 361eb4803ed3
|
||||
p2o.pd_op.conv2d.5.0_bias FLOAT[8] cb4ff71a710c
|
||||
p2o.pd_op.conv2d.6.0_bias FLOAT[32] 85cf04200053
|
||||
p2o.pd_op.conv2d.65.0_bias FLOAT[16] 0e9d95585f8d
|
||||
p2o.pd_op.conv2d.7.0_bias FLOAT[64] 81997938d61e
|
||||
p2o.pd_op.conv2d.8.0_bias FLOAT[32] ed024219d4e3
|
||||
p2o.pd_op.conv2d.9.0_bias FLOAT[64] 86c8e9b964d3
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias FLOAT[32] 2ca546acac26
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias FLOAT[32] eedb2a36ef65
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias FLOAT[64] df8082fa8199
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias FLOAT[160] 9eeb408b79ff
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias FLOAT[160] 65a9c885e6c1
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias FLOAT[64] 8034bb3714d6
|
||||
p2o.pd_op.depthwise_conv2d.14.0_bias FLOAT[64] cf6f0cdf562e
|
||||
p2o.pd_op.depthwise_conv2d.15.0_bias FLOAT[64] e173f2e86531
|
||||
p2o.pd_op.depthwise_conv2d.16.0_bias FLOAT[64] 18c536514a78
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias FLOAT[32] 94341ce3ec68
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias FLOAT[48] 449bc5ac1e4e
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias FLOAT[48] 195d66f64a1c
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias FLOAT[48] 45799033ff4e
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias FLOAT[64] 9c450889f59c
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias FLOAT[64] 5a768734f883
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias FLOAT[64] e1bca67a058a
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias FLOAT[64] 817061d53e3f
|
||||
p2o.pd_op.hardsigmoid.5.0_one FLOAT[] e00e5eb94441
|
||||
se_group0_down1 FLOAT[64,64,1,1] 9930a75ab080
|
||||
se_group0_down2 FLOAT[64] 785e4ae48595
|
||||
se_group0_sizes INT64[4] 998b63595acf
|
||||
se_group0_up1 FLOAT[256,16,1,1] 1349cad1bd0e
|
||||
se_group0_up2 FLOAT[256] 1ac4a47e1d28
|
||||
se_group1_down1 FLOAT[16,16,1,1] 9fde90527970
|
||||
se_group1_down2 FLOAT[16] c7da74659570
|
||||
se_group1_sizes INT64[4] b8eccb1655c4
|
||||
se_group1_up1 FLOAT[64,4,1,1] b397dad6e4a9
|
||||
se_group1_up2 FLOAT[64] a021fcd66bc1
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,468 @@
|
||||
<
|
||||
ir_version: 10,
|
||||
opset_import: ["" : 20]
|
||||
>
|
||||
"PaddlePaddle Graph in PIR mode" (uint8[batch,height,width,3] image) => (float[batch,height,width] dbnet_probs)
|
||||
<
|
||||
float[batch,192,unk__22,unk__23] "Add.105"
|
||||
float[batch,192,unk__22,unk__23] "Add.111"
|
||||
float[batch,192,unk__42,unk__43] "Add.117"
|
||||
float[batch,48,1,1] "Add.119"
|
||||
float[batch,192,1,1] "Add.121"
|
||||
float[batch,384,unk__42,unk__43] "Add.125"
|
||||
float[batch,384,unk__42,unk__43] "Add.131"
|
||||
float[batch,384,unk__42,unk__43] "Add.133"
|
||||
float[batch,96,1,1] "Add.135"
|
||||
float[batch,384,1,1] "Add.137"
|
||||
float[batch,384,unk__42,unk__43] "Add.141"
|
||||
float[batch,384,unk__42,unk__43] "Add.147"
|
||||
float[batch,32,unk__6,unk__7] "Add.15"
|
||||
float[batch,384,unk__42,unk__43] "Add.153"
|
||||
float[batch,384,unk__42,unk__43] "Add.159"
|
||||
float[batch,384,unk__42,unk__43] "Add.165"
|
||||
float[batch,96,unk__42,unk__43] "Add.181"
|
||||
float[batch,96,unk__22,unk__23] "Add.187"
|
||||
float[batch,48,unk__6,unk__7] "Add.19"
|
||||
float[batch,96,unk__14,unk__15] "Add.193"
|
||||
float[batch,96,unk__6,unk__7] "Add.199"
|
||||
float[batch,96,unk__22,unk__23] "Add.201"
|
||||
float[batch,96,unk__14,unk__15] "Add.203"
|
||||
float[batch,96,unk__6,unk__7] "Add.205"
|
||||
float[batch,24,unk__42,unk__43] "Add.211"
|
||||
float[batch,24,unk__22,unk__23] "Add.217"
|
||||
float[batch,24,unk__14,unk__15] "Add.223"
|
||||
float[batch,24,unk__6,unk__7] "Add.229"
|
||||
float[batch,1,height,width] "Add.233"
|
||||
float[batch,48,unk__6,unk__7] "Add.25"
|
||||
float[batch,16,unk__0,unk__1] "Add.3"
|
||||
float[batch,48,unk__6,unk__7] "Add.31"
|
||||
float[batch,48,unk__14,unk__15] "Add.37"
|
||||
float[batch,96,unk__14,unk__15] "Add.41"
|
||||
float[batch,96,unk__14,unk__15] "Add.47"
|
||||
float[batch,96,unk__14,unk__15] "Add.53"
|
||||
float[batch,96,unk__22,unk__23] "Add.59"
|
||||
float[batch,192,unk__22,unk__23] "Add.63"
|
||||
float[batch,192,unk__22,unk__23] "Add.69"
|
||||
float[batch,192,unk__22,unk__23] "Add.75"
|
||||
float[batch,192,unk__22,unk__23] "Add.81"
|
||||
float[batch,192,unk__22,unk__23] "Add.87"
|
||||
float[batch,32,unk__0,unk__1] "Add.9"
|
||||
float[batch,192,unk__22,unk__23] "Add.93"
|
||||
float[batch,192,unk__22,unk__23] "Add.99"
|
||||
float[batch,96,unk__6,unk__7] "Concat.1"
|
||||
float[batch,192,unk__42,unk__43] "Mul.77"
|
||||
float[batch,384,unk__42,unk__43] "Mul.85"
|
||||
float[batch,384,unk__42,unk__43] "Mul.87"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.batch_norm_.0.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.batch_norm_.1.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.batch_norm_.2.0"
|
||||
float[batch,96,unk__42,unk__43] "p2o.pd_op.conv2d.23.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.conv2d.26.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.conv2d.29.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.conv2d.32.0"
|
||||
float[batch,24,unk__42,unk__43] "p2o.pd_op.conv2d.35.0"
|
||||
float[batch,24,unk__22,unk__23] "p2o.pd_op.conv2d.38.0"
|
||||
float[batch,24,unk__14,unk__15] "p2o.pd_op.conv2d.41.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.conv2d.44.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.hardsigmoid.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.hardsigmoid.1.0"
|
||||
float[batch,16,unk__0,unk__1] "p2o.pd_op.hardswish.0.0"
|
||||
float[batch,32,unk__0,unk__1] "p2o.pd_op.hardswish.1.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.10.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.11.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.12.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.13.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.14.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.15.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.16.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.17.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.18.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.19.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.2.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.20.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.21.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.22.0"
|
||||
float[batch,384,unk__42,unk__43] "p2o.pd_op.hardswish.23.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.3.0"
|
||||
float[batch,48,unk__6,unk__7] "p2o.pd_op.hardswish.4.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.5.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.6.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.hardswish.7.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.8.0"
|
||||
float[batch,192,unk__22,unk__23] "p2o.pd_op.hardswish.9.0"
|
||||
float[batch,96,unk__22,unk__23] "p2o.pd_op.nearest_interp.0.0"
|
||||
float[batch,96,unk__14,unk__15] "p2o.pd_op.nearest_interp.1.0"
|
||||
float[batch,96,unk__6,unk__7] "p2o.pd_op.nearest_interp.2.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.3.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.4.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.nearest_interp.5.0"
|
||||
float[batch,192,1,1] "p2o.pd_op.pool2d.0.0"
|
||||
float[batch,384,1,1] "p2o.pd_op.pool2d.1.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.2.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.3.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.4.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.pool2d.5.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.6.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.7.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.8.0"
|
||||
float[batch,24,1,1] "p2o.pd_op.pool2d.9.0"
|
||||
float[batch,48,1,1] "p2o.pd_op.relu.0.0"
|
||||
float[batch,96,1,1] "p2o.pd_op.relu.1.0"
|
||||
float[batch,24,unk__6,unk__7] "p2o.pd_op.relu.10.0"
|
||||
float[batch,24,unk__0,unk__1] "p2o.pd_op.relu.11.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.2.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.3.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.4.0"
|
||||
float[batch,96,1,1] "se_group0_p2o.pd_op.hardsigmoid.5.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.6.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.7.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.8.0"
|
||||
float[batch,24,1,1] "se_group1_p2o.pd_op.hardsigmoid.9.0"
|
||||
float[batch,1,height,width] fetch_name_0
|
||||
float[batch,96,1,1] se_group0_down
|
||||
float[batch,384,1,1] se_group0_gates
|
||||
float[batch,384,1,1] se_group0_pooled
|
||||
float[batch,96,1,1] se_group0_relu
|
||||
float[batch,384,1,1] se_group0_up
|
||||
float[batch,24,1,1] se_group1_down
|
||||
float[batch,96,1,1] se_group1_gates
|
||||
float[batch,96,1,1] se_group1_pooled
|
||||
float[batch,24,1,1] se_group1_relu
|
||||
float[batch,96,1,1] se_group1_up
|
||||
float[batch,height,width,3] tmp
|
||||
float[batch,3,height,width] tmp_0
|
||||
float[batch,16,unk__0,unk__1] val_0
|
||||
float[batch,32,unk__0,unk__1] val_1
|
||||
float[batch,96,unk__14,unk__15] val_10
|
||||
float[batch,96,unk__14,unk__15] val_11
|
||||
float[batch,96,unk__14,unk__15] val_12
|
||||
float[batch,192,unk__22,unk__23] val_13
|
||||
float[batch,192,unk__22,unk__23] val_14
|
||||
float[batch,192,unk__22,unk__23] val_15
|
||||
float[batch,192,unk__22,unk__23] val_16
|
||||
float[batch,192,unk__22,unk__23] val_17
|
||||
float[batch,192,unk__22,unk__23] val_18
|
||||
float[batch,192,unk__22,unk__23] val_19
|
||||
float[batch,32,unk__0,unk__1] val_2
|
||||
float[batch,192,unk__22,unk__23] val_20
|
||||
float[batch,192,unk__22,unk__23] val_21
|
||||
float[batch,192,unk__22,unk__23] val_22
|
||||
float[batch,192,unk__22,unk__23] val_23
|
||||
float[batch,192,unk__22,unk__23] val_24
|
||||
float[batch,192,unk__22,unk__23] val_25
|
||||
float[batch,192,unk__22,unk__23] val_26
|
||||
float[batch,384,unk__42,unk__43] val_27
|
||||
float[batch,384,unk__42,unk__43] val_28
|
||||
float[batch,384,unk__42,unk__43] val_29
|
||||
float[batch,48,unk__6,unk__7] val_3
|
||||
float[batch,384,unk__42,unk__43] val_30
|
||||
float[batch,384,unk__42,unk__43] val_31
|
||||
float[batch,384,unk__42,unk__43] val_32
|
||||
float[batch,384,unk__42,unk__43] val_33
|
||||
float[batch,384,unk__42,unk__43] val_34
|
||||
float[batch,384,unk__42,unk__43] val_35
|
||||
float[batch,384,unk__42,unk__43] val_36
|
||||
float[batch,96,1,1] val_37
|
||||
float[batch,96,1,1] val_38
|
||||
float[batch,96,1,1] val_39
|
||||
float[batch,48,unk__6,unk__7] val_4
|
||||
float[batch,96,1,1] val_40
|
||||
float[batch,24,1,1] val_41
|
||||
float[batch,24,1,1] val_42
|
||||
float[batch,24,1,1] val_43
|
||||
float[batch,24,1,1] val_44
|
||||
float[batch,48,unk__6,unk__7] val_5
|
||||
float[batch,48,unk__6,unk__7] val_6
|
||||
float[batch,48,unk__6,unk__7] val_7
|
||||
float[batch,96,unk__14,unk__15] val_8
|
||||
float[batch,96,unk__14,unk__15] val_9
|
||||
float[batch,3,height,width] x
|
||||
>
|
||||
{
|
||||
[n0] tmp = Cast <to: int = 1> (image)
|
||||
[n1] tmp_0 = Transpose <perm: ints = [0, 3, 1, 2]> (tmp)
|
||||
[n4] x = Sub (tmp_0, const_cast)
|
||||
"p2o.pd_op.batch_norm_.0.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (x, "conv2d_0.w_0", "conv2d_0.w_0_bias")
|
||||
"Add.3" = Conv <dilations: ints = [1, 1], group: int = 16, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("p2o.pd_op.batch_norm_.0.0", "conv2d_161.w_0_lab", "p2o.pd_op.depthwise_conv2d.0.0_bias_lab")
|
||||
val_0 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.3")
|
||||
"p2o.pd_op.hardswish.0.0" = Mul ("Add.3", val_0)
|
||||
"Add.9" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.0.0", "conv2d_162.w_0_lab_lab", "p2o.pd_op.conv2d.1.0_bias_lab_lab")
|
||||
val_1 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.9")
|
||||
"p2o.pd_op.hardswish.1.0" = Mul ("Add.9", val_1)
|
||||
val_2 = Add ("p2o.pd_op.hardswish.1.0", "conv2d_163.w_0_lab_laboffset")
|
||||
"Add.15" = Conv <dilations: ints = [1, 1], group: int = 32, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_2, "conv2d_163.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.1.0_bias_lab")
|
||||
"Add.19" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.15", "conv2d_164.w_0_lab", "p2o.pd_op.conv2d.2.0_bias_lab")
|
||||
val_3 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.19")
|
||||
"p2o.pd_op.hardswish.2.0" = Mul ("Add.19", val_3)
|
||||
val_4 = Add ("p2o.pd_op.hardswish.2.0", "conv2d_165.w_0_lab_laboffset")
|
||||
"Add.25" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_4, "conv2d_165.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.2.0_bias_lab")
|
||||
val_5 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.25")
|
||||
"p2o.pd_op.hardswish.3.0" = Mul ("Add.25", val_5)
|
||||
"Add.31" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.3.0", "conv2d_166.w_0_lab_lab", "p2o.pd_op.conv2d.3.0_bias_lab_lab")
|
||||
val_6 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.31")
|
||||
"p2o.pd_op.hardswish.4.0" = Mul ("Add.31", val_6)
|
||||
val_7 = Add ("p2o.pd_op.hardswish.4.0", "conv2d_167.w_0_lab_laboffset")
|
||||
"Add.37" = Conv <dilations: ints = [1, 1], group: int = 48, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_7, "conv2d_167.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.3.0_bias_lab")
|
||||
"Add.41" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.37", "conv2d_168.w_0_lab", "p2o.pd_op.conv2d.4.0_bias_lab")
|
||||
val_8 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.41")
|
||||
"p2o.pd_op.hardswish.5.0" = Mul ("Add.41", val_8)
|
||||
val_9 = Add ("p2o.pd_op.hardswish.5.0", "conv2d_169.w_0_lab_laboffset")
|
||||
"Add.47" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> (val_9, "conv2d_169.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.4.0_bias_lab")
|
||||
val_10 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.47")
|
||||
"p2o.pd_op.hardswish.6.0" = Mul ("Add.47", val_10)
|
||||
"Add.53" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.6.0", "conv2d_170.w_0_lab_lab", "p2o.pd_op.conv2d.5.0_bias_lab_lab")
|
||||
val_11 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.53")
|
||||
"p2o.pd_op.hardswish.7.0" = Mul ("Add.53", val_11)
|
||||
val_12 = Add ("p2o.pd_op.hardswish.7.0", "conv2d_171.w_0_lab_laboffset")
|
||||
"Add.59" = Conv <dilations: ints = [1, 1], group: int = 96, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [2, 2]> (val_12, "conv2d_171.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.5.0_bias_lab")
|
||||
"Add.63" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Add.59", "conv2d_172.w_0_lab", "p2o.pd_op.conv2d.6.0_bias_lab")
|
||||
val_13 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.63")
|
||||
"p2o.pd_op.hardswish.8.0" = Mul ("Add.63", val_13)
|
||||
val_14 = Add ("p2o.pd_op.hardswish.8.0", "conv2d_173.w_0_lab_laboffset")
|
||||
"Add.69" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_14, "conv2d_173.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.6.0_bias_lab")
|
||||
val_15 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.69")
|
||||
"p2o.pd_op.hardswish.9.0" = Mul ("Add.69", val_15)
|
||||
"Add.75" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.9.0", "conv2d_174.w_0_lab_lab", "p2o.pd_op.conv2d.7.0_bias_lab_lab")
|
||||
val_16 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.75")
|
||||
"p2o.pd_op.hardswish.10.0" = Mul ("Add.75", val_16)
|
||||
val_17 = Add ("p2o.pd_op.hardswish.10.0", "conv2d_175.w_0_lab_laboffset")
|
||||
"Add.81" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_17, "conv2d_175.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.7.0_bias_lab")
|
||||
val_18 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.81")
|
||||
"p2o.pd_op.hardswish.11.0" = Mul ("Add.81", val_18)
|
||||
"Add.87" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.11.0", "conv2d_176.w_0_lab_lab", "p2o.pd_op.conv2d.8.0_bias_lab_lab")
|
||||
val_19 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.87")
|
||||
"p2o.pd_op.hardswish.12.0" = Mul ("Add.87", val_19)
|
||||
val_20 = Add ("p2o.pd_op.hardswish.12.0", "conv2d_177.w_0_lab_laboffset")
|
||||
"Add.93" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_20, "conv2d_177.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.8.0_bias_lab")
|
||||
val_21 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.93")
|
||||
"p2o.pd_op.hardswish.13.0" = Mul ("Add.93", val_21)
|
||||
"Add.99" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.13.0", "conv2d_178.w_0_lab_lab", "p2o.pd_op.conv2d.9.0_bias_lab_lab")
|
||||
val_22 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.99")
|
||||
"p2o.pd_op.hardswish.14.0" = Mul ("Add.99", val_22)
|
||||
val_23 = Add ("p2o.pd_op.hardswish.14.0", "conv2d_179.w_0_lab_laboffset")
|
||||
"Add.105" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_23, "conv2d_179.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.9.0_bias_lab")
|
||||
val_24 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.105")
|
||||
"p2o.pd_op.hardswish.15.0" = Mul ("Add.105", val_24)
|
||||
"Add.111" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.15.0", "conv2d_180.w_0_lab_lab", "p2o.pd_op.conv2d.10.0_bias_lab_lab")
|
||||
val_25 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.111")
|
||||
"p2o.pd_op.hardswish.16.0" = Mul ("Add.111", val_25)
|
||||
val_26 = Add ("p2o.pd_op.hardswish.16.0", "conv2d_181.w_0_lab_laboffset")
|
||||
"Add.117" = Conv <dilations: ints = [1, 1], group: int = 192, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [2, 2]> (val_26, "conv2d_181.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.10.0_bias_lab")
|
||||
["GlobalAveragePool.0"] "p2o.pd_op.pool2d.0.0" = GlobalAveragePool ("Add.117")
|
||||
"Add.119" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.0.0", "conv2d_96.w_0", "p2o.pd_op.conv2d.11.0_bias")
|
||||
["Relu.0"] "p2o.pd_op.relu.0.0" = Relu ("Add.119")
|
||||
"Add.121" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.0.0", "conv2d_97.w_0", "p2o.pd_op.conv2d.12.0_bias")
|
||||
["HardSigmoid.0"] "p2o.pd_op.hardsigmoid.0.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.121")
|
||||
["Mul.76"] "Mul.77" = Mul ("Add.117", "p2o.pd_op.hardsigmoid.0.0")
|
||||
"Add.125" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.77", "conv2d_182.w_0_lab", "p2o.pd_op.conv2d.13.0_bias_lab")
|
||||
val_27 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.125")
|
||||
"p2o.pd_op.hardswish.17.0" = Mul ("Add.125", val_27)
|
||||
val_28 = Add ("p2o.pd_op.hardswish.17.0", "conv2d_183.w_0_lab_laboffset")
|
||||
"Add.131" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_28, "conv2d_183.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.11.0_bias_lab")
|
||||
val_29 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.131")
|
||||
"p2o.pd_op.hardswish.18.0" = Mul ("Add.131", val_29)
|
||||
["Mul.84"] "Mul.85" = Mul ("learnable_affine_block_45.w_0", "p2o.pd_op.hardswish.18.0")
|
||||
["Add.132"] "Add.133" = Add ("Mul.85", "learnable_affine_block_45.w_1")
|
||||
["GlobalAveragePool.1"] "p2o.pd_op.pool2d.1.0" = GlobalAveragePool ("Add.133")
|
||||
"Add.135" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.pool2d.1.0", "conv2d_107.w_0", "p2o.pd_op.conv2d.14.0_bias")
|
||||
["Relu.1"] "p2o.pd_op.relu.1.0" = Relu ("Add.135")
|
||||
"Add.137" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.relu.1.0", "conv2d_108.w_0", "p2o.pd_op.conv2d.15.0_bias")
|
||||
["HardSigmoid.1"] "p2o.pd_op.hardsigmoid.1.0" = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.137")
|
||||
["Mul.86"] "Mul.87" = Mul ("Add.133", "p2o.pd_op.hardsigmoid.1.0")
|
||||
"Add.141" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("Mul.87", "conv2d_184.w_0_lab", "p2o.pd_op.conv2d.16.0_bias_lab")
|
||||
val_30 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.141")
|
||||
"p2o.pd_op.hardswish.19.0" = Mul ("Add.141", val_30)
|
||||
val_31 = Add ("p2o.pd_op.hardswish.19.0", "conv2d_185.w_0_lab_laboffset")
|
||||
"Add.147" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_31, "conv2d_185.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.12.0_bias_lab")
|
||||
val_32 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.147")
|
||||
"p2o.pd_op.hardswish.20.0" = Mul ("Add.147", val_32)
|
||||
"Add.153" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.20.0", "conv2d_186.w_0_lab_lab", "p2o.pd_op.conv2d.17.0_bias_lab_lab")
|
||||
val_33 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.153")
|
||||
"p2o.pd_op.hardswish.21.0" = Mul ("Add.153", val_33)
|
||||
val_34 = Add ("p2o.pd_op.hardswish.21.0", "conv2d_187.w_0_lab_laboffset")
|
||||
"Add.159" = Conv <dilations: ints = [1, 1], group: int = 384, kernel_shape: ints = [5, 5], pads: ints = [2, 2, 2, 2], strides: ints = [1, 1]> (val_34, "conv2d_187.w_0_lab_labscale", "p2o.pd_op.depthwise_conv2d.13.0_bias_lab")
|
||||
val_35 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.159")
|
||||
"p2o.pd_op.hardswish.22.0" = Mul ("Add.159", val_35)
|
||||
"Add.165" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.22.0", "conv2d_188.w_0_lab_lab", "p2o.pd_op.conv2d.18.0_bias_lab_lab")
|
||||
val_36 = HardSigmoid <alpha: float = 0.166667, beta: float = 0.5> ("Add.165")
|
||||
"p2o.pd_op.hardswish.23.0" = Mul ("Add.165", val_36)
|
||||
"p2o.pd_op.conv2d.23.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> ("p2o.pd_op.hardswish.23.0", "Conv.37_folded_w_lab", "Conv.37_folded_b_lab")
|
||||
["GlobalAveragePool.2"] "p2o.pd_op.pool2d.2.0" = GlobalAveragePool ("p2o.pd_op.conv2d.23.0")
|
||||
"p2o.pd_op.conv2d.26.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_26, "Conv.40_folded_w_labscale", "Conv.40_folded_b")
|
||||
["GlobalAveragePool.3"] "p2o.pd_op.pool2d.3.0" = GlobalAveragePool ("p2o.pd_op.conv2d.26.0")
|
||||
"p2o.pd_op.conv2d.29.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_12, "Conv.43_folded_w_labscale", "Conv.43_folded_b")
|
||||
["GlobalAveragePool.4"] "p2o.pd_op.pool2d.4.0" = GlobalAveragePool ("p2o.pd_op.conv2d.29.0")
|
||||
"p2o.pd_op.conv2d.32.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (val_7, "Conv.46_folded_w_labscale", "Conv.46_folded_b")
|
||||
["GlobalAveragePool.5"] "p2o.pd_op.pool2d.5.0" = GlobalAveragePool ("p2o.pd_op.conv2d.32.0")
|
||||
se_group0_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.2.0", "p2o.pd_op.pool2d.3.0", "p2o.pd_op.pool2d.4.0", "p2o.pd_op.pool2d.5.0")
|
||||
se_group0_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_pooled, se_group0_down1, se_group0_down2)
|
||||
se_group0_relu = Relu (se_group0_down)
|
||||
se_group0_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group0_relu, se_group0_up1, se_group0_up2)
|
||||
se_group0_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group0_up)
|
||||
"se_group0_p2o.pd_op.hardsigmoid.2.0", "se_group0_p2o.pd_op.hardsigmoid.3.0", "se_group0_p2o.pd_op.hardsigmoid.4.0", "se_group0_p2o.pd_op.hardsigmoid.5.0" = Split <axis: int = 1> (se_group0_gates, se_group0_sizes)
|
||||
val_37 = Add ("se_group0_p2o.pd_op.hardsigmoid.2.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.181" = Mul ("p2o.pd_op.conv2d.23.0", val_37)
|
||||
val_38 = Add ("se_group0_p2o.pd_op.hardsigmoid.3.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.187" = Mul ("p2o.pd_op.conv2d.26.0", val_38)
|
||||
val_39 = Add ("se_group0_p2o.pd_op.hardsigmoid.4.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.193" = Mul ("p2o.pd_op.conv2d.29.0", val_39)
|
||||
val_40 = Add ("se_group0_p2o.pd_op.hardsigmoid.5.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.199" = Mul ("p2o.pd_op.conv2d.32.0", val_40)
|
||||
["Resize.0"] "p2o.pd_op.nearest_interp.0.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.181", "helper.constant.1", "helper.constant.0")
|
||||
["Add.200"] "Add.201" = Add ("Add.187", "p2o.pd_op.nearest_interp.0.0")
|
||||
["Resize.1"] "p2o.pd_op.nearest_interp.1.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.201", "helper.constant.1", "helper.constant.0")
|
||||
["Add.202"] "Add.203" = Add ("Add.193", "p2o.pd_op.nearest_interp.1.0")
|
||||
["Resize.2"] "p2o.pd_op.nearest_interp.2.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.203", "helper.constant.1", "helper.constant.0")
|
||||
["Add.204"] "Add.205" = Add ("Add.199", "p2o.pd_op.nearest_interp.2.0")
|
||||
["Conv.49"] "p2o.pd_op.conv2d.35.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.181", "conv2d_156.w_0")
|
||||
["GlobalAveragePool.6"] "p2o.pd_op.pool2d.6.0" = GlobalAveragePool ("p2o.pd_op.conv2d.35.0")
|
||||
["Conv.52"] "p2o.pd_op.conv2d.38.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.201", "conv2d_150.w_0")
|
||||
["GlobalAveragePool.7"] "p2o.pd_op.pool2d.7.0" = GlobalAveragePool ("p2o.pd_op.conv2d.38.0")
|
||||
["Conv.55"] "p2o.pd_op.conv2d.41.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.203", "conv2d_144.w_0")
|
||||
["GlobalAveragePool.8"] "p2o.pd_op.pool2d.8.0" = GlobalAveragePool ("p2o.pd_op.conv2d.41.0")
|
||||
["Conv.58"] "p2o.pd_op.conv2d.44.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Add.205", "conv2d_138.w_0")
|
||||
["GlobalAveragePool.9"] "p2o.pd_op.pool2d.9.0" = GlobalAveragePool ("p2o.pd_op.conv2d.44.0")
|
||||
se_group1_pooled = Concat <axis: int = 1> ("p2o.pd_op.pool2d.6.0", "p2o.pd_op.pool2d.7.0", "p2o.pd_op.pool2d.8.0", "p2o.pd_op.pool2d.9.0")
|
||||
se_group1_down = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_pooled, se_group1_down1, se_group1_down2)
|
||||
se_group1_relu = Relu (se_group1_down)
|
||||
se_group1_up = Conv <dilations: ints = [1, 1], group: int = 4, kernel_shape: ints = [1, 1], pads: ints = [0, 0, 0, 0], strides: ints = [1, 1]> (se_group1_relu, se_group1_up1, se_group1_up2)
|
||||
se_group1_gates = HardSigmoid <alpha: float = 0.2, beta: float = 0.5> (se_group1_up)
|
||||
"se_group1_p2o.pd_op.hardsigmoid.6.0", "se_group1_p2o.pd_op.hardsigmoid.7.0", "se_group1_p2o.pd_op.hardsigmoid.8.0", "se_group1_p2o.pd_op.hardsigmoid.9.0" = Split <axis: int = 1> (se_group1_gates, se_group1_sizes)
|
||||
val_41 = Add ("se_group1_p2o.pd_op.hardsigmoid.6.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.211" = Mul ("p2o.pd_op.conv2d.35.0", val_41)
|
||||
val_42 = Add ("se_group1_p2o.pd_op.hardsigmoid.7.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.217" = Mul ("p2o.pd_op.conv2d.38.0", val_42)
|
||||
val_43 = Add ("se_group1_p2o.pd_op.hardsigmoid.8.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.223" = Mul ("p2o.pd_op.conv2d.41.0", val_43)
|
||||
val_44 = Add ("se_group1_p2o.pd_op.hardsigmoid.9.0", "p2o.pd_op.hardsigmoid.2.0_one")
|
||||
"Add.229" = Mul ("p2o.pd_op.conv2d.44.0", val_44)
|
||||
["Resize.3"] "p2o.pd_op.nearest_interp.3.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.211", "helper.constant.1", "helper.constant.6")
|
||||
["Resize.4"] "p2o.pd_op.nearest_interp.4.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.217", "helper.constant.1", "helper.constant.8")
|
||||
["Resize.5"] "p2o.pd_op.nearest_interp.5.0" = Resize <coordinate_transformation_mode: string = "asymmetric", mode: string = "nearest", nearest_mode: string = "floor"> ("Add.223", "helper.constant.1", "helper.constant.0")
|
||||
["Concat.0"] "Concat.1" = Concat <axis: int = 1> ("p2o.pd_op.nearest_interp.3.0", "p2o.pd_op.nearest_interp.4.0", "p2o.pd_op.nearest_interp.5.0", "Add.229")
|
||||
"p2o.pd_op.batch_norm_.1.0" = Conv <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [3, 3], pads: ints = [1, 1, 1, 1], strides: ints = [1, 1]> ("Concat.1", "conv2d_159.w_0", "conv2d_159.w_0_bias")
|
||||
["Relu.10"] "p2o.pd_op.relu.10.0" = Relu ("p2o.pd_op.batch_norm_.1.0")
|
||||
"p2o.pd_op.batch_norm_.2.0" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.10.0", "auto.cast.57", "ConvTranspose.1_bias")
|
||||
["Relu.11"] "p2o.pd_op.relu.11.0" = Relu ("p2o.pd_op.batch_norm_.2.0")
|
||||
"Add.233" = ConvTranspose <dilations: ints = [1, 1], group: int = 1, kernel_shape: ints = [2, 2], pads: ints = [0, 0, 0, 0], strides: ints = [2, 2]> ("p2o.pd_op.relu.11.0", "auto.cast.60", "ConvTranspose.3_bias")
|
||||
["Sigmoid.0"] fetch_name_0 = Sigmoid ("Add.233")
|
||||
[n1_2] dbnet_probs = Squeeze (fetch_name_0, int64_1_1d)
|
||||
}
|
||||
|
||||
weights:
|
||||
Conv.37_folded_b_lab FLOAT[96] 0d571951a1e0
|
||||
Conv.37_folded_w_lab FLOAT[96,384,1,1] 1d0305563ea7
|
||||
Conv.40_folded_b FLOAT[96] dcfdd514912d
|
||||
Conv.40_folded_w_labscale FLOAT[96,192,1,1] bacc8274202e
|
||||
Conv.43_folded_b FLOAT[96] ee902cf71aad
|
||||
Conv.43_folded_w_labscale FLOAT[96,96,1,1] b17e08485dc5
|
||||
Conv.46_folded_b FLOAT[96] 6541e510a35d
|
||||
Conv.46_folded_w_labscale FLOAT[96,48,1,1] 9423b2c0951a
|
||||
ConvTranspose.1_bias FLOAT[24] 64cabf62980d
|
||||
ConvTranspose.3_bias FLOAT[1] 55c86fee1edb
|
||||
auto.cast.57 FLOAT[24,24,2,2] 1dc864bec64f
|
||||
auto.cast.60 FLOAT[24,1,2,2] c9862b3a19bc
|
||||
const_cast FLOAT[] 9fd754fbfd83
|
||||
conv2d_0.w_0 FLOAT[16,3,3,3] 7841f2f3efae
|
||||
conv2d_0.w_0_bias FLOAT[16] 2713bf453fd1
|
||||
conv2d_107.w_0 FLOAT[96,384,1,1] 2fc401aa1ec6
|
||||
conv2d_108.w_0 FLOAT[384,96,1,1] f2a9a9261c07
|
||||
conv2d_138.w_0 FLOAT[24,96,3,3] 47aa8ba1db50
|
||||
conv2d_144.w_0 FLOAT[24,96,3,3] cd85b03c436c
|
||||
conv2d_150.w_0 FLOAT[24,96,3,3] 591f14004ce0
|
||||
conv2d_156.w_0 FLOAT[24,96,3,3] 5e0bc4bf821e
|
||||
conv2d_159.w_0 FLOAT[24,96,3,3] 43b6b1b17bef
|
||||
conv2d_159.w_0_bias FLOAT[24] c98267f8273d
|
||||
conv2d_161.w_0_lab FLOAT[16,1,3,3] 22528d709d37
|
||||
conv2d_162.w_0_lab_lab FLOAT[32,16,1,1] 051645505e21
|
||||
conv2d_163.w_0_lab_laboffset FLOAT[] 92a142f7dc41
|
||||
conv2d_163.w_0_lab_labscale FLOAT[32,1,3,3] 8694842bd3fb
|
||||
conv2d_164.w_0_lab FLOAT[48,32,1,1] 0c937f040d0e
|
||||
conv2d_165.w_0_lab_laboffset FLOAT[] 012179917694
|
||||
conv2d_165.w_0_lab_labscale FLOAT[48,1,3,3] 7d779e5616fa
|
||||
conv2d_166.w_0_lab_lab FLOAT[48,48,1,1] d70c86b2d1ec
|
||||
conv2d_167.w_0_lab_laboffset FLOAT[] 9741b37d98e3
|
||||
conv2d_167.w_0_lab_labscale FLOAT[48,1,3,3] fa2e1db2eb62
|
||||
conv2d_168.w_0_lab FLOAT[96,48,1,1] 81e13e0bd382
|
||||
conv2d_169.w_0_lab_laboffset FLOAT[] f3e015d53e9a
|
||||
conv2d_169.w_0_lab_labscale FLOAT[96,1,3,3] 75bbb69deb68
|
||||
conv2d_170.w_0_lab_lab FLOAT[96,96,1,1] 59b22a69e345
|
||||
conv2d_171.w_0_lab_laboffset FLOAT[] f42328163f40
|
||||
conv2d_171.w_0_lab_labscale FLOAT[96,1,3,3] 65cbca6287a2
|
||||
conv2d_172.w_0_lab FLOAT[192,96,1,1] ff93ca701d2f
|
||||
conv2d_173.w_0_lab_laboffset FLOAT[] b76450d3656f
|
||||
conv2d_173.w_0_lab_labscale FLOAT[192,1,5,5] 28d7de00679c
|
||||
conv2d_174.w_0_lab_lab FLOAT[192,192,1,1] 53cf6f343ec2
|
||||
conv2d_175.w_0_lab_laboffset FLOAT[] e665434a5d2d
|
||||
conv2d_175.w_0_lab_labscale FLOAT[192,1,5,5] 3c0aa815839d
|
||||
conv2d_176.w_0_lab_lab FLOAT[192,192,1,1] cb45f031f07b
|
||||
conv2d_177.w_0_lab_laboffset FLOAT[] e095ffc76247
|
||||
conv2d_177.w_0_lab_labscale FLOAT[192,1,5,5] 22fe03b75591
|
||||
conv2d_178.w_0_lab_lab FLOAT[192,192,1,1] c259022f5c3d
|
||||
conv2d_179.w_0_lab_laboffset FLOAT[] 5842420f0e64
|
||||
conv2d_179.w_0_lab_labscale FLOAT[192,1,5,5] 408bbab0d507
|
||||
conv2d_180.w_0_lab_lab FLOAT[192,192,1,1] 85871ea30bf1
|
||||
conv2d_181.w_0_lab_laboffset FLOAT[] 9e0407355f14
|
||||
conv2d_181.w_0_lab_labscale FLOAT[192,1,5,5] 75764b0f5265
|
||||
conv2d_182.w_0_lab FLOAT[384,192,1,1] 81235d1a972f
|
||||
conv2d_183.w_0_lab_laboffset FLOAT[] e648d792317a
|
||||
conv2d_183.w_0_lab_labscale FLOAT[384,1,5,5] f5341adaad28
|
||||
conv2d_184.w_0_lab FLOAT[384,384,1,1] c37a7cec640b
|
||||
conv2d_185.w_0_lab_laboffset FLOAT[] 768fa13da14b
|
||||
conv2d_185.w_0_lab_labscale FLOAT[384,1,5,5] 6bacb713155c
|
||||
conv2d_186.w_0_lab_lab FLOAT[384,384,1,1] 2fa80ae1b18f
|
||||
conv2d_187.w_0_lab_laboffset FLOAT[] ad505dafbd90
|
||||
conv2d_187.w_0_lab_labscale FLOAT[384,1,5,5] a221bd8406f2
|
||||
conv2d_188.w_0_lab_lab FLOAT[384,384,1,1] 9ea062b2f1b4
|
||||
conv2d_96.w_0 FLOAT[48,192,1,1] 6d73ce1fb738
|
||||
conv2d_97.w_0 FLOAT[192,48,1,1] 8098a00a81f0
|
||||
helper.constant.0 FLOAT[4] aa5b3e0ef3e8
|
||||
helper.constant.1 FLOAT[0] e3b0c44298fc
|
||||
helper.constant.6 FLOAT[4] cf5451a623be
|
||||
helper.constant.8 FLOAT[4] 1811eb557cd7
|
||||
int64_1_1d INT64[1] 7c9fa136d441
|
||||
learnable_affine_block_45.w_0 FLOAT[1] 65444e550b77
|
||||
learnable_affine_block_45.w_1 FLOAT[1] f2ee18a061af
|
||||
p2o.pd_op.conv2d.1.0_bias_lab_lab FLOAT[32] 3f4be24e33b8
|
||||
p2o.pd_op.conv2d.10.0_bias_lab_lab FLOAT[192] e32536500417
|
||||
p2o.pd_op.conv2d.11.0_bias FLOAT[48] 961ec85108cb
|
||||
p2o.pd_op.conv2d.12.0_bias FLOAT[192] c348751cbed0
|
||||
p2o.pd_op.conv2d.13.0_bias_lab FLOAT[384] 1b6d0aa0e977
|
||||
p2o.pd_op.conv2d.14.0_bias FLOAT[96] 7876208c6fb1
|
||||
p2o.pd_op.conv2d.15.0_bias FLOAT[384] 871907fff11d
|
||||
p2o.pd_op.conv2d.16.0_bias_lab FLOAT[384] fd15d67f1e85
|
||||
p2o.pd_op.conv2d.17.0_bias_lab_lab FLOAT[384] 097f0d068f05
|
||||
p2o.pd_op.conv2d.18.0_bias_lab_lab FLOAT[384] b8e228cae698
|
||||
p2o.pd_op.conv2d.2.0_bias_lab FLOAT[48] 8138a593f8f2
|
||||
p2o.pd_op.conv2d.3.0_bias_lab_lab FLOAT[48] 57128b896e31
|
||||
p2o.pd_op.conv2d.4.0_bias_lab FLOAT[96] d2230ff7a27e
|
||||
p2o.pd_op.conv2d.5.0_bias_lab_lab FLOAT[96] 05b9a5f236b6
|
||||
p2o.pd_op.conv2d.6.0_bias_lab FLOAT[192] a990b3fed4dd
|
||||
p2o.pd_op.conv2d.7.0_bias_lab_lab FLOAT[192] 74df3e4f22b6
|
||||
p2o.pd_op.conv2d.8.0_bias_lab_lab FLOAT[192] 9c072f4b4032
|
||||
p2o.pd_op.conv2d.9.0_bias_lab_lab FLOAT[192] 8f6e7021fe63
|
||||
p2o.pd_op.depthwise_conv2d.0.0_bias_lab FLOAT[16] 5b3de9e3f7c2
|
||||
p2o.pd_op.depthwise_conv2d.1.0_bias_lab FLOAT[32] bb4239a962eb
|
||||
p2o.pd_op.depthwise_conv2d.10.0_bias_lab FLOAT[192] 81ac3c08eae1
|
||||
p2o.pd_op.depthwise_conv2d.11.0_bias_lab FLOAT[384] 2236a6b52e38
|
||||
p2o.pd_op.depthwise_conv2d.12.0_bias_lab FLOAT[384] 14c22d416e3b
|
||||
p2o.pd_op.depthwise_conv2d.13.0_bias_lab FLOAT[384] 4eebd04fbeb4
|
||||
p2o.pd_op.depthwise_conv2d.2.0_bias_lab FLOAT[48] aaee6f6db9c1
|
||||
p2o.pd_op.depthwise_conv2d.3.0_bias_lab FLOAT[48] dcc78f972645
|
||||
p2o.pd_op.depthwise_conv2d.4.0_bias_lab FLOAT[96] dbd763cef105
|
||||
p2o.pd_op.depthwise_conv2d.5.0_bias_lab FLOAT[96] 5849d6801824
|
||||
p2o.pd_op.depthwise_conv2d.6.0_bias_lab FLOAT[192] 01e9219938aa
|
||||
p2o.pd_op.depthwise_conv2d.7.0_bias_lab FLOAT[192] e35d55fdac89
|
||||
p2o.pd_op.depthwise_conv2d.8.0_bias_lab FLOAT[192] fd7c6cc0a8fb
|
||||
p2o.pd_op.depthwise_conv2d.9.0_bias_lab FLOAT[192] aedc2ab77e2b
|
||||
p2o.pd_op.hardsigmoid.2.0_one FLOAT[] e00e5eb94441
|
||||
se_group0_down1 FLOAT[96,96,1,1] 4c8c888b01f2
|
||||
se_group0_down2 FLOAT[96] b99146f86442
|
||||
se_group0_sizes INT64[4] 4bb249469bee
|
||||
se_group0_up1 FLOAT[384,24,1,1] 1446892243f3
|
||||
se_group0_up2 FLOAT[384] 8538540d9317
|
||||
se_group1_down1 FLOAT[24,24,1,1] 01a670ee8021
|
||||
se_group1_down2 FLOAT[24] 7f8067be0db7
|
||||
se_group1_sizes INT64[4] 5c995dc6a0ef
|
||||
se_group1_up1 FLOAT[96,6,1,1] 3e47b305535b
|
||||
se_group1_up2 FLOAT[96] ed3a93d396c3
|
||||
File diff suppressed because it is too large
Load Diff
@@ -12,7 +12,9 @@ CUDAExecutionProvider
|
||||
CoreMLExecutionProvider
|
||||
decompose_attention
|
||||
decompose_reduce_l2
|
||||
unpack_scrfd_heads
|
||||
nchw_image_input
|
||||
split_deep_reduction
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
decompose_attention
|
||||
@@ -35,6 +37,7 @@ OpenVINOExecutionProvider
|
||||
RKNPU
|
||||
floatify_pad_mask
|
||||
decompose_attention
|
||||
unpack_scrfd_heads
|
||||
im2col_patchify_batch1
|
||||
uint8_image_input
|
||||
float_image_input
|
||||
@@ -45,6 +48,8 @@ RKNPU
|
||||
fold_gather_elements
|
||||
decompose_gelu
|
||||
split_large_reduction
|
||||
fold_concat_into_conv
|
||||
split_large_conv_reduction
|
||||
pin_opset
|
||||
reinfer_shapes
|
||||
|
||||
@@ -52,3 +57,8 @@ TensorrtExecutionProvider
|
||||
decompose_attention
|
||||
greedy_ctc_topk
|
||||
im2col_patchify
|
||||
|
||||
RKNPU compile
|
||||
config {'disable_rules': [], 'enable_flash_attention': False, 'model_pruning': False}
|
||||
do_quantization False
|
||||
socs rk3566 rk3568 rk3576 rk3588
|
||||
|
||||
@@ -0,0 +1,132 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
167 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x50 06530e5e
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,163 @@
|
||||
CPUExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
194 nodes, weights c701fdf571c7
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x77 07b210e0
|
||||
|
||||
CUDAExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
166 nodes, weights c701fdf571c7
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x75 b10bd6c0
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
197 nodes, weights c701fdf571c7
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x80 247ec9fe
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights c701fdf571c7
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
164 nodes, weights c701fdf571c7
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 5772e2e9
|
||||
|
||||
RKNPU width=2048
|
||||
+9 Transpose perm=(0, 3, 2, 1)
|
||||
-2 Sub
|
||||
+1 Add
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
-1 Concat axis=1
|
||||
+1 Concat axis=3
|
||||
+1 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(1, 3) pads=(0, 1, 0, 1) strides=(1, 1)
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Unsqueeze
|
||||
202 nodes, weights bf24b5f54ecf
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x3 f950ecb9
|
||||
FuseBatchNormIntoConv x5 5453ec31
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x83 249adb8f
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights c701fdf571c7
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
@@ -0,0 +1,108 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
unchanged
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
216 nodes, weights 9baeda5351d0
|
||||
FuseBatchNormIntoConv x82 e269b1c6
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 b91a3035
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 1790608a
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 4a5f8b7f
|
||||
_FoldBiasAdd x6 fff058bc
|
||||
unstamped x111 714b42e5
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
-2 Conv auto_pad=SAME_UPPER dilations=(1, 1) group=1 kernel_shape=(2, 2) strides=(1, 1)
|
||||
+2 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
217 nodes, weights 76826f1f1013
|
||||
FuseBatchNormIntoConv x80 f811511a
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 b91a3035
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 1790608a
|
||||
SymmetrizeConvPads, FuseBatchNormIntoConv x2 0681b679
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 4a5f8b7f
|
||||
_FoldBiasAdd x6 fff058bc
|
||||
unstamped x112 823f9e9e
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
unchanged
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+72 Add
|
||||
+40 Slice
|
||||
+36 Conv dilations=(1, 1) group=1 kernel_shape=(1, 1) pads=(0, 0, 0, 0) strides=(1, 1)
|
||||
+32 Conv dilations=(1, 1) group=1 kernel_shape=(9, 9) pads=(4, 4, 4, 4) strides=(1, 1)
|
||||
-8 Concat axis=1
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
390 nodes, weights be31199e4857
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x88 18ed6894
|
||||
FuseBatchNormIntoConv x74 0d776a88
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 b91a3035
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 1790608a
|
||||
SplitLargeConvReduction x112 4a2f750c
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 4a5f8b7f
|
||||
_FoldBiasAdd x6 eb017eb5
|
||||
unstamped x93 e8b9902a
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+72 Add
|
||||
+40 Slice
|
||||
+36 Conv dilations=(1, 1) group=1 kernel_shape=(1, 1) pads=(0, 0, 0, 0) strides=(1, 1)
|
||||
+32 Conv dilations=(1, 1) group=1 kernel_shape=(9, 9) pads=(4, 4, 4, 4) strides=(1, 1)
|
||||
-8 Concat axis=1
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
390 nodes, weights be31199e4857
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x88 18ed6894
|
||||
FuseBatchNormIntoConv x74 0d776a88
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 b91a3035
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 1790608a
|
||||
SplitLargeConvReduction x112 4a2f750c
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 4a5f8b7f
|
||||
_FoldBiasAdd x6 eb017eb5
|
||||
unstamped x93 e8b9902a
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+72 Add
|
||||
+40 Slice
|
||||
+36 Conv dilations=(1, 1) group=1 kernel_shape=(1, 1) pads=(0, 0, 0, 0) strides=(1, 1)
|
||||
+32 Conv dilations=(1, 1) group=1 kernel_shape=(9, 9) pads=(4, 4, 4, 4) strides=(1, 1)
|
||||
-8 Concat axis=1
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
390 nodes, weights be31199e4857
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x88 18ed6894
|
||||
FuseBatchNormIntoConv x74 0d776a88
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 b91a3035
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 1790608a
|
||||
SplitLargeConvReduction x112 4a2f750c
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 4a5f8b7f
|
||||
_FoldBiasAdd x6 eb017eb5
|
||||
unstamped x93 e8b9902a
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,128 @@
|
||||
CPUExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
222 nodes, weights 491162e4edda
|
||||
FuseBatchNormIntoConv x86 90bbcf85
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x129 d37df2c7
|
||||
|
||||
CUDAExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
222 nodes, weights 491162e4edda
|
||||
FuseBatchNormIntoConv x86 90bbcf85
|
||||
FuseGreedyCtcTopK x2 5682aea5
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x127 81fd1f5b
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
225 nodes, weights 491162e4edda
|
||||
FuseBatchNormIntoConv x86 90bbcf85
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x132 a9e2e2f3
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
-2 Conv auto_pad=SAME_UPPER dilations=(1, 1) group=1 kernel_shape=(2, 2) strides=(1, 1)
|
||||
+2 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
226 nodes, weights 59de39ec79f2
|
||||
FuseBatchNormIntoConv x84 b8821a21
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
SymmetrizeConvPads, FuseBatchNormIntoConv x2 0681b679
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x133 799acf81
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
226 nodes, weights 491162e4edda
|
||||
FuseBatchNormIntoConv x86 90bbcf85
|
||||
FuseGreedyCtcTopK x2 5682aea5
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x131 558fc80b
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
220 nodes, weights 491162e4edda
|
||||
FuseBatchNormIntoConv x86 90bbcf85
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x127 048b915f
|
||||
|
||||
RKNPU width=2048
|
||||
+44 Add
|
||||
+36 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(1, 1) pads=(0, 0, 0, 0) strides=(1, 1)
|
||||
+9 Slice
|
||||
+9 Transpose perm=(0, 3, 2, 1)
|
||||
-8 Concat axis=1
|
||||
+7 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(1, 3) pads=(0, 1, 0, 1) strides=(1, 1)
|
||||
-2 Sub
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
+1 Concat axis=3
|
||||
+1 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Unsqueeze
|
||||
318 nodes, weights 98aeab86de6c
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x82 3e07422b
|
||||
FuseBatchNormIntoConv x77 8054b0d7
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
SplitLargeConvReduction, FoldConcatIntoConv, FuseBatchNormIntoConv x16 fc4dfb30
|
||||
SplitLargeConvReduction, FuseBatchNormIntoConv x8 eee87394
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x128 46df0390
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
226 nodes, weights 491162e4edda
|
||||
FuseBatchNormIntoConv x86 90bbcf85
|
||||
FuseGreedyCtcTopK x2 5682aea5
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x131 558fc80b
|
||||
@@ -0,0 +1,132 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
167 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x50 06530e5e
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,163 @@
|
||||
CPUExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
194 nodes, weights 2b14c2784510
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x77 07b210e0
|
||||
|
||||
CUDAExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
166 nodes, weights 2b14c2784510
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x75 b10bd6c0
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
197 nodes, weights 2b14c2784510
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x80 247ec9fe
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights 2b14c2784510
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
164 nodes, weights 2b14c2784510
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 5772e2e9
|
||||
|
||||
RKNPU width=2048
|
||||
-2 Sub
|
||||
+1 Add
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
-1 Concat axis=1
|
||||
+1 Concat axis=3
|
||||
+1 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(1, 3) pads=(0, 1, 0, 1) strides=(1, 1)
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Transpose perm=(0, 3, 2, 1)
|
||||
+1 Unsqueeze
|
||||
194 nodes, weights 30be6d90cba8
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x3 f950ecb9
|
||||
FuseBatchNormIntoConv x5 5453ec31
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 57f586e5
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights 2b14c2784510
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
@@ -0,0 +1,132 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
167 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x50 06530e5e
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,163 @@
|
||||
CPUExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
194 nodes, weights 67c58a51fc40
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x77 07b210e0
|
||||
|
||||
CUDAExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
166 nodes, weights 67c58a51fc40
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x75 b10bd6c0
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
197 nodes, weights 67c58a51fc40
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x80 247ec9fe
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights 67c58a51fc40
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
164 nodes, weights 67c58a51fc40
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 5772e2e9
|
||||
|
||||
RKNPU width=2048
|
||||
-2 Sub
|
||||
+1 Add
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
-1 Concat axis=1
|
||||
+1 Concat axis=3
|
||||
+1 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(1, 3) pads=(0, 1, 0, 1) strides=(1, 1)
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Transpose perm=(0, 3, 2, 1)
|
||||
+1 Unsqueeze
|
||||
194 nodes, weights 953b7c1ead6e
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x3 f950ecb9
|
||||
FuseBatchNormIntoConv x5 5453ec31
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 57f586e5
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights 67c58a51fc40
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
@@ -0,0 +1,132 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
167 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x50 06530e5e
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,163 @@
|
||||
CPUExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
194 nodes, weights 8eb43f013f6f
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x77 07b210e0
|
||||
|
||||
CUDAExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
166 nodes, weights 8eb43f013f6f
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x75 b10bd6c0
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
197 nodes, weights 8eb43f013f6f
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x80 247ec9fe
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights 8eb43f013f6f
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
164 nodes, weights 8eb43f013f6f
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 5772e2e9
|
||||
|
||||
RKNPU width=2048
|
||||
-2 Sub
|
||||
+1 Add
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
-1 Concat axis=1
|
||||
+1 Concat axis=3
|
||||
+1 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(1, 3) pads=(0, 1, 0, 1) strides=(1, 1)
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Transpose perm=(0, 3, 2, 1)
|
||||
+1 Unsqueeze
|
||||
194 nodes, weights bc1fcf4583c6
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x3 f950ecb9
|
||||
FuseBatchNormIntoConv x5 5453ec31
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 57f586e5
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights 8eb43f013f6f
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
@@ -0,0 +1,132 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
167 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x50 06530e5e
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,163 @@
|
||||
CPUExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
194 nodes, weights 7609aaebfbe4
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x77 07b210e0
|
||||
|
||||
CUDAExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
166 nodes, weights 7609aaebfbe4
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x75 b10bd6c0
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
197 nodes, weights 7609aaebfbe4
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x80 247ec9fe
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights 7609aaebfbe4
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
164 nodes, weights 7609aaebfbe4
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 5772e2e9
|
||||
|
||||
RKNPU width=2048
|
||||
+6 Transpose perm=(0, 3, 2, 1)
|
||||
-2 Sub
|
||||
+1 Add
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
-1 Concat axis=1
|
||||
+1 Concat axis=3
|
||||
+1 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(1, 3) pads=(0, 1, 0, 1) strides=(1, 1)
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Unsqueeze
|
||||
199 nodes, weights 47600c49647e
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x3 f950ecb9
|
||||
FuseBatchNormIntoConv x5 5453ec31
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x80 6a62091c
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights 7609aaebfbe4
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
@@ -107,6 +107,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
622 nodes, weights c1b2feb7b330
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x168 41dfedfa
|
||||
DecomposeGelu x60 0b43d613
|
||||
SplitLargeReduction x204 a55486b0
|
||||
|
||||
@@ -33,9 +33,11 @@ CUDAExecutionProvider
|
||||
unstamped x321 c90f7cd8
|
||||
|
||||
CoreMLExecutionProvider
|
||||
+120 MatMul
|
||||
+96 Reshape
|
||||
+96 Slice
|
||||
+96 Transpose perm=(0, 2, 1, 3)
|
||||
+48 MatMul
|
||||
+72 Add
|
||||
+25 Mul
|
||||
-24 Attention is_causal=0 kv_num_heads=16 q_num_heads=16 qk_matmul_output_mode=0 softcap=0.0
|
||||
+24 Softmax axis=-1
|
||||
@@ -44,15 +46,16 @@ CoreMLExecutionProvider
|
||||
+1 ReduceSum keepdims=1
|
||||
+1 Sqrt
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
713 nodes, weights d02df6125762
|
||||
953 nodes, weights 58f0cb46a43a
|
||||
DecomposeAttention x312 b153a8df
|
||||
DecomposeReduceL2 x3 4108ebd9
|
||||
RemoveOptionalBiasFromConv x1 95405b53
|
||||
SplitLargeReduction x264 e8913650
|
||||
_ConstantifyReshapeTarget x1 f786528a
|
||||
_FuseClassTokenPrepend x2 64b83b02
|
||||
_ScalarGatherToSlice, _SelectBeforeLayerNorm x1 cde77a8c
|
||||
_SelectBeforeLayerNorm x1 ab62bee7
|
||||
unstamped x392 78976231
|
||||
unstamped x368 d45bad00
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
+96 Reshape
|
||||
@@ -129,6 +132,8 @@ RKNPU static
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
1532 nodes, weights 3bdf40ff5eb6
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x312 b153a8df
|
||||
PatchEmbedToMatMul, _ConstantifyReshapeTarget, RemoveOptionalBiasFromConv x5 37ecaa30
|
||||
SplitLargeReduction x917 67719055
|
||||
|
||||
@@ -0,0 +1,132 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
167 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x50 06530e5e
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,163 @@
|
||||
CPUExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
194 nodes, weights 4d2a3dd5fcab
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x77 07b210e0
|
||||
|
||||
CUDAExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
166 nodes, weights 4d2a3dd5fcab
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x75 b10bd6c0
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
197 nodes, weights 4d2a3dd5fcab
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x80 247ec9fe
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights 4d2a3dd5fcab
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
164 nodes, weights 4d2a3dd5fcab
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 5772e2e9
|
||||
|
||||
RKNPU width=2048
|
||||
-2 Sub
|
||||
+1 Add
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
-1 Concat axis=1
|
||||
+1 Concat axis=3
|
||||
+1 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(1, 3) pads=(0, 1, 0, 1) strides=(1, 1)
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Transpose perm=(0, 3, 2, 1)
|
||||
+1 Unsqueeze
|
||||
194 nodes, weights bf0ead508fef
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x3 f950ecb9
|
||||
FuseBatchNormIntoConv x5 5453ec31
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 57f586e5
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights 4d2a3dd5fcab
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
@@ -0,0 +1,132 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
167 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x50 06530e5e
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,163 @@
|
||||
CPUExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
194 nodes, weights c701fdf571c7
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x77 07b210e0
|
||||
|
||||
CUDAExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
166 nodes, weights c701fdf571c7
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x75 b10bd6c0
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
197 nodes, weights c701fdf571c7
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x80 247ec9fe
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights c701fdf571c7
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
164 nodes, weights c701fdf571c7
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 5772e2e9
|
||||
|
||||
RKNPU width=2048
|
||||
+9 Transpose perm=(0, 3, 2, 1)
|
||||
-2 Sub
|
||||
+1 Add
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
-1 Concat axis=1
|
||||
+1 Concat axis=3
|
||||
+1 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(1, 3) pads=(0, 1, 0, 1) strides=(1, 1)
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Unsqueeze
|
||||
202 nodes, weights bf24b5f54ecf
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x3 f950ecb9
|
||||
FuseBatchNormIntoConv x5 5453ec31
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x83 249adb8f
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights c701fdf571c7
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
@@ -0,0 +1,108 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
unchanged
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
216 nodes, weights 9baeda5351d0
|
||||
FuseBatchNormIntoConv x82 e269b1c6
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 b91a3035
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 1790608a
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 4a5f8b7f
|
||||
_FoldBiasAdd x6 fff058bc
|
||||
unstamped x111 714b42e5
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
-2 Conv auto_pad=SAME_UPPER dilations=(1, 1) group=1 kernel_shape=(2, 2) strides=(1, 1)
|
||||
+2 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
217 nodes, weights 76826f1f1013
|
||||
FuseBatchNormIntoConv x80 f811511a
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 b91a3035
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 1790608a
|
||||
SymmetrizeConvPads, FuseBatchNormIntoConv x2 0681b679
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 4a5f8b7f
|
||||
_FoldBiasAdd x6 fff058bc
|
||||
unstamped x112 823f9e9e
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
unchanged
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+72 Add
|
||||
+40 Slice
|
||||
+36 Conv dilations=(1, 1) group=1 kernel_shape=(1, 1) pads=(0, 0, 0, 0) strides=(1, 1)
|
||||
+32 Conv dilations=(1, 1) group=1 kernel_shape=(9, 9) pads=(4, 4, 4, 4) strides=(1, 1)
|
||||
-8 Concat axis=1
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
390 nodes, weights be31199e4857
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x88 18ed6894
|
||||
FuseBatchNormIntoConv x74 0d776a88
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 b91a3035
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 1790608a
|
||||
SplitLargeConvReduction x112 4a2f750c
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 4a5f8b7f
|
||||
_FoldBiasAdd x6 eb017eb5
|
||||
unstamped x93 e8b9902a
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+72 Add
|
||||
+40 Slice
|
||||
+36 Conv dilations=(1, 1) group=1 kernel_shape=(1, 1) pads=(0, 0, 0, 0) strides=(1, 1)
|
||||
+32 Conv dilations=(1, 1) group=1 kernel_shape=(9, 9) pads=(4, 4, 4, 4) strides=(1, 1)
|
||||
-8 Concat axis=1
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
390 nodes, weights be31199e4857
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x88 18ed6894
|
||||
FuseBatchNormIntoConv x74 0d776a88
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 b91a3035
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 1790608a
|
||||
SplitLargeConvReduction x112 4a2f750c
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 4a5f8b7f
|
||||
_FoldBiasAdd x6 eb017eb5
|
||||
unstamped x93 e8b9902a
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+72 Add
|
||||
+40 Slice
|
||||
+36 Conv dilations=(1, 1) group=1 kernel_shape=(1, 1) pads=(0, 0, 0, 0) strides=(1, 1)
|
||||
+32 Conv dilations=(1, 1) group=1 kernel_shape=(9, 9) pads=(4, 4, 4, 4) strides=(1, 1)
|
||||
-8 Concat axis=1
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
390 nodes, weights be31199e4857
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x88 18ed6894
|
||||
FuseBatchNormIntoConv x74 0d776a88
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 b91a3035
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 1790608a
|
||||
SplitLargeConvReduction x112 4a2f750c
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 4a5f8b7f
|
||||
_FoldBiasAdd x6 eb017eb5
|
||||
unstamped x93 e8b9902a
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,128 @@
|
||||
CPUExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
222 nodes, weights 491162e4edda
|
||||
FuseBatchNormIntoConv x86 90bbcf85
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x129 d37df2c7
|
||||
|
||||
CUDAExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
222 nodes, weights 491162e4edda
|
||||
FuseBatchNormIntoConv x86 90bbcf85
|
||||
FuseGreedyCtcTopK x2 5682aea5
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x127 81fd1f5b
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
225 nodes, weights 491162e4edda
|
||||
FuseBatchNormIntoConv x86 90bbcf85
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x132 a9e2e2f3
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
-2 Conv auto_pad=SAME_UPPER dilations=(1, 1) group=1 kernel_shape=(2, 2) strides=(1, 1)
|
||||
+2 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
226 nodes, weights 59de39ec79f2
|
||||
FuseBatchNormIntoConv x84 b8821a21
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
SymmetrizeConvPads, FuseBatchNormIntoConv x2 0681b679
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x133 799acf81
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
226 nodes, weights 491162e4edda
|
||||
FuseBatchNormIntoConv x86 90bbcf85
|
||||
FuseGreedyCtcTopK x2 5682aea5
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x131 558fc80b
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
220 nodes, weights 491162e4edda
|
||||
FuseBatchNormIntoConv x86 90bbcf85
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x127 048b915f
|
||||
|
||||
RKNPU width=2048
|
||||
+44 Add
|
||||
+36 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(1, 1) pads=(0, 0, 0, 0) strides=(1, 1)
|
||||
+9 Slice
|
||||
+9 Transpose perm=(0, 3, 2, 1)
|
||||
-8 Concat axis=1
|
||||
+7 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(1, 3) pads=(0, 1, 0, 1) strides=(1, 1)
|
||||
-2 Sub
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
+1 Concat axis=3
|
||||
+1 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Unsqueeze
|
||||
318 nodes, weights 98aeab86de6c
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x82 3e07422b
|
||||
FuseBatchNormIntoConv x77 8054b0d7
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
SplitLargeConvReduction, FoldConcatIntoConv, FuseBatchNormIntoConv x16 fc4dfb30
|
||||
SplitLargeConvReduction, FuseBatchNormIntoConv x8 eee87394
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x128 46df0390
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
226 nodes, weights 491162e4edda
|
||||
FuseBatchNormIntoConv x86 90bbcf85
|
||||
FuseGreedyCtcTopK x2 5682aea5
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 29f6d61e
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x131 558fc80b
|
||||
@@ -0,0 +1,103 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
unchanged
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
177 nodes, weights cec0648fd947
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 f34c76f1
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 5400703b
|
||||
_FoldBiasAdd x77 b88346ee
|
||||
_FuseErfGelu x13 837b6556
|
||||
unstamped x71 957d1144
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
-2 Conv auto_pad=SAME_UPPER dilations=(1, 1) group=1 kernel_shape=(2, 2) strides=(1, 1)
|
||||
+2 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
178 nodes, weights 74673ca875bf
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 f34c76f1
|
||||
SymmetrizeConvPads, _FoldBiasAdd x2 67f062ca
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 5400703b
|
||||
_FoldBiasAdd x75 7cc8ab48
|
||||
_FuseErfGelu x13 837b6556
|
||||
unstamped x72 bb40f7c7
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
unchanged
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+26 Mul
|
||||
+17 Add
|
||||
+13 Div
|
||||
+13 Erf
|
||||
-13 Gelu approximate=none
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-2 Concat axis=1
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
233 nodes, weights 9d280467bf08
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
DecomposeGelu, _FuseErfGelu x65 806e4876
|
||||
FoldConcatIntoConv, _FoldBiasAdd x10 7429e6fe
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 f34c76f1
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 5400703b
|
||||
_FoldBiasAdd x75 dc2c1362
|
||||
unstamped x67 492b6de5
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+26 Mul
|
||||
+17 Add
|
||||
+13 Div
|
||||
+13 Erf
|
||||
-13 Gelu approximate=none
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-2 Concat axis=1
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
233 nodes, weights 9d280467bf08
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
DecomposeGelu, _FuseErfGelu x65 806e4876
|
||||
FoldConcatIntoConv, _FoldBiasAdd x10 7429e6fe
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 f34c76f1
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 5400703b
|
||||
_FoldBiasAdd x75 dc2c1362
|
||||
unstamped x67 492b6de5
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+26 Mul
|
||||
+17 Add
|
||||
+13 Div
|
||||
+13 Erf
|
||||
-13 Gelu approximate=none
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-2 Concat axis=1
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
233 nodes, weights 9d280467bf08
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
DecomposeGelu, _FuseErfGelu x65 806e4876
|
||||
FoldConcatIntoConv, _FoldBiasAdd x10 7429e6fe
|
||||
FuseBatchNormIntoConv, _FoldBiasAdd x4 f34c76f1
|
||||
_FoldAsymmetricConvs, _FoldBiasAdd, _FoldBiasAdd, _FoldBiasAdd x12 5400703b
|
||||
_FoldBiasAdd x75 dc2c1362
|
||||
unstamped x67 492b6de5
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,143 @@
|
||||
CPUExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
188 nodes, weights e7e45dd78cf8
|
||||
FuseBatchNormIntoConv x3 f0034f99
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 5bba76a2
|
||||
_FoldBiasAdd x59 cd1e1b9f
|
||||
_FuseErfGelu x14 a1e48475
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x105 3c73f0d8
|
||||
|
||||
CUDAExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
188 nodes, weights e7e45dd78cf8
|
||||
FuseBatchNormIntoConv x3 f0034f99
|
||||
FuseGreedyCtcTopK x2 cbcd7d37
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 5bba76a2
|
||||
_FoldBiasAdd x59 cd1e1b9f
|
||||
_FuseErfGelu x14 a1e48475
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x103 f11e1c0f
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
191 nodes, weights e7e45dd78cf8
|
||||
FuseBatchNormIntoConv x3 f0034f99
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 5bba76a2
|
||||
_FoldBiasAdd x59 cd1e1b9f
|
||||
_FuseErfGelu x14 a1e48475
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x108 8928ade5
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
-2 Conv auto_pad=SAME_UPPER dilations=(1, 1) group=1 kernel_shape=(2, 2) strides=(1, 1)
|
||||
+2 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
192 nodes, weights 352e09469662
|
||||
FuseBatchNormIntoConv x3 f0034f99
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
SymmetrizeConvPads, _FoldBiasAdd x2 0a5187dc
|
||||
_FlattenToSqueeze x1 5bba76a2
|
||||
_FoldBiasAdd x57 c355cf96
|
||||
_FuseErfGelu x14 a1e48475
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x109 fc4f340b
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
192 nodes, weights e7e45dd78cf8
|
||||
FuseBatchNormIntoConv x3 f0034f99
|
||||
FuseGreedyCtcTopK x2 cbcd7d37
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 5bba76a2
|
||||
_FoldBiasAdd x59 cd1e1b9f
|
||||
_FuseErfGelu x14 a1e48475
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x107 205592f8
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
186 nodes, weights e7e45dd78cf8
|
||||
FuseBatchNormIntoConv x3 f0034f99
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 5bba76a2
|
||||
_FoldBiasAdd x59 cd1e1b9f
|
||||
_FuseErfGelu x14 a1e48475
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x103 0232e6e3
|
||||
|
||||
RKNPU width=2048
|
||||
+28 Mul
|
||||
+15 Add
|
||||
+14 Div
|
||||
+14 Erf
|
||||
-14 Gelu approximate=none
|
||||
+10 Transpose perm=(0, 3, 2, 1)
|
||||
-2 Sub
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
-1 Concat axis=1
|
||||
+1 Concat axis=3
|
||||
+1 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Unsqueeze
|
||||
253 nodes, weights 7682e031e070
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
DecomposeGelu, _FuseErfGelu x70 a24a2b3d
|
||||
FoldConcatIntoConv, _FoldBiasAdd x3 072a41c0
|
||||
FuseBatchNormIntoConv x3 f0034f99
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 5bba76a2
|
||||
_FoldBiasAdd x58 99e3e7e0
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x112 7aa507f0
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
192 nodes, weights e7e45dd78cf8
|
||||
FuseBatchNormIntoConv x3 f0034f99
|
||||
FuseGreedyCtcTopK x2 cbcd7d37
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 5bba76a2
|
||||
_FoldBiasAdd x59 cd1e1b9f
|
||||
_FuseErfGelu x14 a1e48475
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x107 205592f8
|
||||
@@ -0,0 +1,98 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
unchanged
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
171 nodes, weights 0ee30064ccf1
|
||||
_FoldBiasAdd x61 4caa5d46
|
||||
_FoldSeResidual x16 11481d1e
|
||||
_FuseErfGelu x13 837b6556
|
||||
unstamped x81 881fc022
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
-2 Conv auto_pad=SAME_UPPER dilations=(1, 1) group=1 kernel_shape=(2, 2) strides=(1, 1)
|
||||
+2 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
172 nodes, weights cc89ee39057e
|
||||
SymmetrizeConvPads, _FoldBiasAdd x2 3ea10a40
|
||||
_FoldBiasAdd x59 79659130
|
||||
_FoldSeResidual x16 11481d1e
|
||||
_FuseErfGelu x13 837b6556
|
||||
unstamped x82 cead5f70
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
unchanged
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+26 Mul
|
||||
+17 Add
|
||||
+13 Div
|
||||
+13 Erf
|
||||
-13 Gelu approximate=none
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-2 Concat axis=1
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
227 nodes, weights dd59c43c946b
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
DecomposeGelu, _FuseErfGelu x65 8ccf2ca9
|
||||
FoldConcatIntoConv, _FoldBiasAdd x10 1aebe9a4
|
||||
_FoldBiasAdd x59 f2ff1967
|
||||
_FoldSeResidual x16 11481d1e
|
||||
unstamped x77 e08220e4
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+26 Mul
|
||||
+17 Add
|
||||
+13 Div
|
||||
+13 Erf
|
||||
-13 Gelu approximate=none
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-2 Concat axis=1
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
227 nodes, weights dd59c43c946b
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
DecomposeGelu, _FuseErfGelu x65 8ccf2ca9
|
||||
FoldConcatIntoConv, _FoldBiasAdd x10 1aebe9a4
|
||||
_FoldBiasAdd x59 f2ff1967
|
||||
_FoldSeResidual x16 11481d1e
|
||||
unstamped x77 e08220e4
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+26 Mul
|
||||
+17 Add
|
||||
+13 Div
|
||||
+13 Erf
|
||||
-13 Gelu approximate=none
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-2 Concat axis=1
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
227 nodes, weights dd59c43c946b
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
DecomposeGelu, _FuseErfGelu x65 8ccf2ca9
|
||||
FoldConcatIntoConv, _FoldBiasAdd x10 1aebe9a4
|
||||
_FoldBiasAdd x59 f2ff1967
|
||||
_FoldSeResidual x16 11481d1e
|
||||
unstamped x77 e08220e4
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,143 @@
|
||||
CPUExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
178 nodes, weights 1c71e1598778
|
||||
FuseBatchNormIntoConv x3 cafd8b4b
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 f6285ec7
|
||||
_FoldBiasAdd x54 a455ec75
|
||||
_FuseErfGelu x13 837b6556
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x101 48bb1c11
|
||||
|
||||
CUDAExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
178 nodes, weights 1c71e1598778
|
||||
FuseBatchNormIntoConv x3 cafd8b4b
|
||||
FuseGreedyCtcTopK x2 60800ef1
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 f6285ec7
|
||||
_FoldBiasAdd x54 a455ec75
|
||||
_FuseErfGelu x13 837b6556
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x99 543cce05
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
181 nodes, weights 1c71e1598778
|
||||
FuseBatchNormIntoConv x3 cafd8b4b
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 f6285ec7
|
||||
_FoldBiasAdd x54 a455ec75
|
||||
_FuseErfGelu x13 837b6556
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x104 77530022
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
-2 Conv auto_pad=SAME_UPPER dilations=(1, 1) group=1 kernel_shape=(2, 2) strides=(1, 1)
|
||||
+2 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
182 nodes, weights 6b83d5a75df4
|
||||
FuseBatchNormIntoConv x3 cafd8b4b
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
SymmetrizeConvPads, _FoldBiasAdd x2 c440deb2
|
||||
_FlattenToSqueeze x1 f6285ec7
|
||||
_FoldBiasAdd x52 f35bd2c4
|
||||
_FuseErfGelu x13 837b6556
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x105 f6fa16d5
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
182 nodes, weights 1c71e1598778
|
||||
FuseBatchNormIntoConv x3 cafd8b4b
|
||||
FuseGreedyCtcTopK x2 60800ef1
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 f6285ec7
|
||||
_FoldBiasAdd x54 a455ec75
|
||||
_FuseErfGelu x13 837b6556
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x103 e65db882
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
176 nodes, weights 1c71e1598778
|
||||
FuseBatchNormIntoConv x3 cafd8b4b
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 f6285ec7
|
||||
_FoldBiasAdd x54 a455ec75
|
||||
_FuseErfGelu x13 837b6556
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x99 d09d18d3
|
||||
|
||||
RKNPU width=2048
|
||||
+26 Mul
|
||||
+14 Add
|
||||
+13 Div
|
||||
+13 Erf
|
||||
-13 Gelu approximate=none
|
||||
+10 Transpose perm=(0, 3, 2, 1)
|
||||
-2 Sub
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
-1 Concat axis=1
|
||||
+1 Concat axis=3
|
||||
+1 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Unsqueeze
|
||||
239 nodes, weights d10aaa3f70ba
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
DecomposeGelu, _FuseErfGelu x65 a950e748
|
||||
FoldConcatIntoConv, _FoldBiasAdd x3 40db084c
|
||||
FuseBatchNormIntoConv x3 cafd8b4b
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 f6285ec7
|
||||
_FoldBiasAdd x53 176f5c08
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x108 aec73a75
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
182 nodes, weights 1c71e1598778
|
||||
FuseBatchNormIntoConv x3 cafd8b4b
|
||||
FuseGreedyCtcTopK x2 60800ef1
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 f6285ec7
|
||||
_FoldBiasAdd x54 a455ec75
|
||||
_FuseErfGelu x13 837b6556
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x103 e65db882
|
||||
@@ -0,0 +1,98 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
unchanged
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
171 nodes, weights 39fde6614b6c
|
||||
_FoldBiasAdd x61 265bf66a
|
||||
_FoldSeResidual x16 11481d1e
|
||||
_FuseErfGelu x13 837b6556
|
||||
unstamped x81 caa53d6f
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
-2 Conv auto_pad=SAME_UPPER dilations=(1, 1) group=1 kernel_shape=(2, 2) strides=(1, 1)
|
||||
+2 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
172 nodes, weights 52b390ae5ce9
|
||||
SymmetrizeConvPads, _FoldBiasAdd x2 a2ff9cf8
|
||||
_FoldBiasAdd x59 169c4fca
|
||||
_FoldSeResidual x16 11481d1e
|
||||
_FuseErfGelu x13 837b6556
|
||||
unstamped x82 2ccb5d0c
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
unchanged
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+26 Mul
|
||||
+17 Add
|
||||
+13 Div
|
||||
+13 Erf
|
||||
-13 Gelu approximate=none
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-2 Concat axis=1
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
227 nodes, weights 623ebf5b4b64
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
DecomposeGelu, _FuseErfGelu x65 8ccf2ca9
|
||||
FoldConcatIntoConv, _FoldBiasAdd x10 d7b409b2
|
||||
_FoldBiasAdd x59 fda46f28
|
||||
_FoldSeResidual x16 11481d1e
|
||||
unstamped x77 ba854663
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+26 Mul
|
||||
+17 Add
|
||||
+13 Div
|
||||
+13 Erf
|
||||
-13 Gelu approximate=none
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-2 Concat axis=1
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
227 nodes, weights 623ebf5b4b64
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
DecomposeGelu, _FuseErfGelu x65 8ccf2ca9
|
||||
FoldConcatIntoConv, _FoldBiasAdd x10 d7b409b2
|
||||
_FoldBiasAdd x59 fda46f28
|
||||
_FoldSeResidual x16 11481d1e
|
||||
unstamped x77 ba854663
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+26 Mul
|
||||
+17 Add
|
||||
+13 Div
|
||||
+13 Erf
|
||||
-13 Gelu approximate=none
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-2 Concat axis=1
|
||||
-1 Cast to=1
|
||||
+1 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(2, 2)
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
227 nodes, weights 623ebf5b4b64
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
DecomposeGelu, _FuseErfGelu x65 8ccf2ca9
|
||||
FoldConcatIntoConv, _FoldBiasAdd x10 d7b409b2
|
||||
_FoldBiasAdd x59 fda46f28
|
||||
_FoldSeResidual x16 11481d1e
|
||||
unstamped x77 ba854663
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,113 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
-2 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+2 HardSwish
|
||||
-2 Mul
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
89 nodes, weights 6307b4e60881
|
||||
FuseBatchNormIntoConv x2 a6b06e3d
|
||||
FuseBatchNormIntoConv, _HoistBatchNormOverSqueeze x2 7e7cb29a
|
||||
FuseGreedyCtcTopK x2 cf2f64e5
|
||||
FuseHardSwish x2 f424200c
|
||||
_FoldBiasAdd x33 b2294c37
|
||||
_FuseErfGelu x10 094e651a
|
||||
_HoistBatchNormOverSqueeze x2 34d81872
|
||||
unstamped x36 1a25fd6c
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
90 nodes, weights 4dc0e0a39884
|
||||
FuseBatchNormIntoConv x2 a6b06e3d
|
||||
FuseBatchNormIntoConv, _HoistBatchNormOverSqueeze x2 7e7cb29a
|
||||
_FoldBiasAdd x33 b2294c37
|
||||
_FuseErfGelu x10 094e651a
|
||||
_HoistBatchNormOverSqueeze x2 34d81872
|
||||
unstamped x41 c18248a1
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
91 nodes, weights 6307b4e60881
|
||||
FuseBatchNormIntoConv x2 a6b06e3d
|
||||
FuseBatchNormIntoConv, _HoistBatchNormOverSqueeze x2 7e7cb29a
|
||||
FuseGreedyCtcTopK x2 cf2f64e5
|
||||
_FoldBiasAdd x33 b2294c37
|
||||
_FuseErfGelu x10 094e651a
|
||||
_HoistBatchNormOverSqueeze x2 34d81872
|
||||
unstamped x40 492c5c16
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-2 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+2 HardSwish
|
||||
-2 Mul
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
83 nodes, weights 4dc0e0a39884
|
||||
FuseBatchNormIntoConv x2 a6b06e3d
|
||||
FuseBatchNormIntoConv, _HoistBatchNormOverSqueeze x2 7e7cb29a
|
||||
FuseHardSwish x2 f424200c
|
||||
_FoldBiasAdd x33 b2294c37
|
||||
_FuseErfGelu x10 094e651a
|
||||
_HoistBatchNormOverSqueeze x2 34d81872
|
||||
unstamped x32 80fa2071
|
||||
|
||||
RKNPU width=2048
|
||||
+20 Mul
|
||||
+10 Add
|
||||
+10 Div
|
||||
+10 Erf
|
||||
-10 Gelu approximate=none
|
||||
+4 Transpose perm=(0, 3, 2, 1)
|
||||
-2 Sub
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
+1 Concat axis=3
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Unsqueeze
|
||||
129 nodes, weights fac4c916c227
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
DecomposeGelu, _FuseErfGelu x50 c8c55aac
|
||||
FuseBatchNormIntoConv x2 b8290aa0
|
||||
FuseBatchNormIntoConv, _HoistBatchNormOverSqueeze x2 7e7cb29a
|
||||
_FoldBiasAdd x33 e15d452c
|
||||
_HoistBatchNormOverSqueeze x2 34d81872
|
||||
unstamped x40 cd9c5258
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
91 nodes, weights 6307b4e60881
|
||||
FuseBatchNormIntoConv x2 a6b06e3d
|
||||
FuseBatchNormIntoConv, _HoistBatchNormOverSqueeze x2 7e7cb29a
|
||||
FuseGreedyCtcTopK x2 cf2f64e5
|
||||
_FoldBiasAdd x33 b2294c37
|
||||
_FuseErfGelu x10 094e651a
|
||||
_HoistBatchNormOverSqueeze x2 34d81872
|
||||
unstamped x40 492c5c16
|
||||
@@ -101,6 +101,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
494 nodes, weights 3eac0e390a47
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 e3c7aa4c
|
||||
SplitLargeReduction x132 d3b9957d
|
||||
_EotOneHotSelect x3 b5dd8d0a
|
||||
|
||||
@@ -62,21 +62,25 @@ OpenVINOExecutionProvider
|
||||
unstamped x166 91df0027
|
||||
|
||||
RKNPU static
|
||||
+12 Slice
|
||||
+15 Slice
|
||||
+11 Add
|
||||
+11 MatMul
|
||||
+9 Add
|
||||
+2 Conv auto_pad=NOTSET dilations=(1, 1) group=1 pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Attention is_causal=0 qk_matmul_output_mode=0 softcap=0.0
|
||||
-1 Cast to=1
|
||||
+1 Mul
|
||||
+1 Softmax axis=-1
|
||||
+1 Transpose perm=(0, 1, 3, 2)
|
||||
316 nodes, weights 879b6ebde0db
|
||||
323 nodes, weights 6abbb9da1d3a
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x5 b00b8abe
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x106 e66e5f08
|
||||
SplitLargeReduction x33 5c3b97e2
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x105 95c1ee4e
|
||||
SplitLargeConvReduction, FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x8 c9a3f0f3
|
||||
SplitLargeReduction x33 463c69a3
|
||||
_ConstantifyReshapeTarget x9 8c4eb3c1
|
||||
_ScalarGatherToSlice x1 68716d7d
|
||||
unstamped x162 e776c70d
|
||||
unstamped x162 e8bc9e8b
|
||||
|
||||
TensorrtExecutionProvider
|
||||
+2 MatMul
|
||||
|
||||
@@ -104,6 +104,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
518 nodes, weights 617bc52f8c3a
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 06d4787f
|
||||
DecomposeGelu x60 55e0b8fd
|
||||
SplitLargeReduction x132 8d307a1d
|
||||
|
||||
@@ -62,21 +62,25 @@ OpenVINOExecutionProvider
|
||||
unstamped x166 91df0027
|
||||
|
||||
RKNPU static
|
||||
+12 Slice
|
||||
+15 Slice
|
||||
+11 Add
|
||||
+11 MatMul
|
||||
+9 Add
|
||||
+2 Conv auto_pad=NOTSET dilations=(1, 1) group=1 pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Attention is_causal=0 qk_matmul_output_mode=0 softcap=0.0
|
||||
-1 Cast to=1
|
||||
+1 Mul
|
||||
+1 Softmax axis=-1
|
||||
+1 Transpose perm=(0, 1, 3, 2)
|
||||
316 nodes, weights 87caa0ae61ec
|
||||
323 nodes, weights 094e4023914c
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x5 b00b8abe
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x106 e66e5f08
|
||||
SplitLargeReduction x33 5c3b97e2
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x105 95c1ee4e
|
||||
SplitLargeConvReduction, FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x8 c9a3f0f3
|
||||
SplitLargeReduction x33 463c69a3
|
||||
_ConstantifyReshapeTarget x9 8c4eb3c1
|
||||
_ScalarGatherToSlice x1 68716d7d
|
||||
unstamped x162 e776c70d
|
||||
unstamped x162 e8bc9e8b
|
||||
|
||||
TensorrtExecutionProvider
|
||||
+2 MatMul
|
||||
|
||||
@@ -104,6 +104,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
518 nodes, weights c444ea7f15bb
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 06d4787f
|
||||
DecomposeGelu x60 55e0b8fd
|
||||
SplitLargeReduction x132 8d307a1d
|
||||
|
||||
@@ -62,21 +62,25 @@ OpenVINOExecutionProvider
|
||||
unstamped x98 a5d8a72d
|
||||
|
||||
RKNPU static
|
||||
+12 Slice
|
||||
+15 Slice
|
||||
+11 Add
|
||||
+11 MatMul
|
||||
+9 Add
|
||||
+2 Conv auto_pad=NOTSET dilations=(1, 1) group=1 pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Attention is_causal=0 qk_matmul_output_mode=0 softcap=0.0
|
||||
-1 Cast to=1
|
||||
+1 Mul
|
||||
+1 Softmax axis=-1
|
||||
+1 Transpose perm=(0, 1, 3, 2)
|
||||
197 nodes, weights ac6ea1b2b4b9
|
||||
204 nodes, weights b627aace5dd8
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x5 b00b8abe
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x55 18e54fd8
|
||||
SplitLargeReduction x33 925fe9f6
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x54 8f65283c
|
||||
SplitLargeConvReduction, FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x8 679b95aa
|
||||
SplitLargeReduction x33 3cabc813
|
||||
_ConstantifyReshapeTarget x9 8c4eb3c1
|
||||
_ScalarGatherToSlice x1 6e430d0a
|
||||
unstamped x94 a1aff241
|
||||
unstamped x94 9d87f2e4
|
||||
|
||||
TensorrtExecutionProvider
|
||||
+2 MatMul
|
||||
|
||||
@@ -101,6 +101,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
494 nodes, weights e08be46e140b
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 e3c7aa4c
|
||||
SplitLargeReduction x132 d3b9957d
|
||||
_EotOneHotSelect x3 b5dd8d0a
|
||||
|
||||
@@ -62,21 +62,25 @@ OpenVINOExecutionProvider
|
||||
unstamped x98 a5d8a72d
|
||||
|
||||
RKNPU static
|
||||
+12 Slice
|
||||
+15 Slice
|
||||
+11 Add
|
||||
+11 MatMul
|
||||
+9 Add
|
||||
+2 Conv auto_pad=NOTSET dilations=(1, 1) group=1 pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Attention is_causal=0 qk_matmul_output_mode=0 softcap=0.0
|
||||
-1 Cast to=1
|
||||
+1 Mul
|
||||
+1 Softmax axis=-1
|
||||
+1 Transpose perm=(0, 1, 3, 2)
|
||||
197 nodes, weights 1279fe2d28a6
|
||||
204 nodes, weights 307a9ce37455
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x5 b00b8abe
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x55 18e54fd8
|
||||
SplitLargeReduction x33 925fe9f6
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x54 8f65283c
|
||||
SplitLargeConvReduction, FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x8 679b95aa
|
||||
SplitLargeReduction x33 3cabc813
|
||||
_ConstantifyReshapeTarget x9 8c4eb3c1
|
||||
_ScalarGatherToSlice x1 6e430d0a
|
||||
unstamped x94 a1aff241
|
||||
unstamped x94 9d87f2e4
|
||||
|
||||
TensorrtExecutionProvider
|
||||
+2 MatMul
|
||||
|
||||
@@ -104,6 +104,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
518 nodes, weights 7288660274c8
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 06d4787f
|
||||
DecomposeGelu x60 55e0b8fd
|
||||
SplitLargeReduction x132 8d307a1d
|
||||
|
||||
@@ -62,21 +62,25 @@ OpenVINOExecutionProvider
|
||||
unstamped x98 a5d8a72d
|
||||
|
||||
RKNPU static
|
||||
+12 Slice
|
||||
+15 Slice
|
||||
+11 Add
|
||||
+11 MatMul
|
||||
+9 Add
|
||||
+2 Conv auto_pad=NOTSET dilations=(1, 1) group=1 pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Attention is_causal=0 qk_matmul_output_mode=0 softcap=0.0
|
||||
-1 Cast to=1
|
||||
+1 Mul
|
||||
+1 Softmax axis=-1
|
||||
+1 Transpose perm=(0, 1, 3, 2)
|
||||
197 nodes, weights 2318f7f490b3
|
||||
204 nodes, weights f79af060a719
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x5 b00b8abe
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x55 18e54fd8
|
||||
SplitLargeReduction x33 925fe9f6
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x54 8f65283c
|
||||
SplitLargeConvReduction, FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x8 679b95aa
|
||||
SplitLargeReduction x33 3cabc813
|
||||
_ConstantifyReshapeTarget x9 8c4eb3c1
|
||||
_ScalarGatherToSlice x1 6e430d0a
|
||||
unstamped x94 a1aff241
|
||||
unstamped x94 9d87f2e4
|
||||
|
||||
TensorrtExecutionProvider
|
||||
+2 MatMul
|
||||
|
||||
@@ -101,6 +101,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
566 nodes, weights 51a86d202212
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 e3c7aa4c
|
||||
SplitLargeReduction x204 cc817052
|
||||
_EotOneHotSelect x3 b5dd8d0a
|
||||
|
||||
@@ -62,21 +62,25 @@ OpenVINOExecutionProvider
|
||||
unstamped x194 38d47366
|
||||
|
||||
RKNPU static
|
||||
+18 Slice
|
||||
+86 Slice
|
||||
+57 Add
|
||||
+42 Conv auto_pad=NOTSET dilations=(1, 1) group=1 pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
+17 MatMul
|
||||
+15 Add
|
||||
-1 Attention is_causal=0 qk_matmul_output_mode=0 softcap=0.0
|
||||
-1 Cast to=1
|
||||
+1 Mul
|
||||
+1 Softmax axis=-1
|
||||
+1 Transpose perm=(0, 1, 3, 2)
|
||||
383 nodes, weights af8597a42bb3
|
||||
535 nodes, weights 78aa30da84e1
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x5 b00b8abe
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x127 ea935478
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x101 71a7a3c3
|
||||
SplitLargeConvReduction, FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x178 b839f170
|
||||
SplitLargeReduction x51 2df90287
|
||||
_ConstantifyReshapeTarget x9 8c4eb3c1
|
||||
_ScalarGatherToSlice x1 788edd2f
|
||||
unstamped x190 20155172
|
||||
unstamped x190 15293d22
|
||||
|
||||
TensorrtExecutionProvider
|
||||
+2 MatMul
|
||||
|
||||
@@ -101,6 +101,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
530 nodes, weights e5dc6fa666ab
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 e3c7aa4c
|
||||
SplitLargeReduction x168 7085f08c
|
||||
_EotOneHotSelect x3 b5dd8d0a
|
||||
|
||||
@@ -62,21 +62,25 @@ OpenVINOExecutionProvider
|
||||
unstamped x138 743040bd
|
||||
|
||||
RKNPU static
|
||||
+15 Slice
|
||||
+33 Slice
|
||||
+24 Add
|
||||
+14 MatMul
|
||||
+12 Add
|
||||
+12 Conv auto_pad=NOTSET dilations=(1, 1) group=1 pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Attention is_causal=0 qk_matmul_output_mode=0 softcap=0.0
|
||||
-1 Cast to=1
|
||||
+1 Mul
|
||||
+1 Softmax axis=-1
|
||||
+1 Transpose perm=(0, 1, 3, 2)
|
||||
276 nodes, weights 10a41729ee08
|
||||
318 nodes, weights b07e1d97dd4f
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x5 b00b8abe
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x85 1ad75ae5
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x79 f89f4aa0
|
||||
SplitLargeConvReduction, FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x48 db035233
|
||||
SplitLargeReduction x42 fe862331
|
||||
_ConstantifyReshapeTarget x9 8c4eb3c1
|
||||
_ScalarGatherToSlice x1 72ff007c
|
||||
unstamped x134 0b8401b3
|
||||
unstamped x134 38b5d3b6
|
||||
|
||||
TensorrtExecutionProvider
|
||||
+2 MatMul
|
||||
|
||||
@@ -23,24 +23,26 @@ CUDAExecutionProvider
|
||||
unstamped x153 da976bc3
|
||||
|
||||
CoreMLExecutionProvider
|
||||
+60 MatMul
|
||||
+48 Add
|
||||
+48 Reshape
|
||||
+48 Slice
|
||||
+48 Transpose perm=(0, 2, 1, 3)
|
||||
+24 MatMul
|
||||
+13 Mul
|
||||
+12 Add
|
||||
-12 Attention is_causal=1 kv_num_heads=16 q_num_heads=16 qk_matmul_output_mode=0 softcap=0.0
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
-1 ReduceL2 keepdims=1 noop_with_empty_axes=0
|
||||
+1 ReduceSum keepdims=1
|
||||
+1 Sqrt
|
||||
376 nodes, weights d0e7a671b85c
|
||||
496 nodes, weights 4015ad71c047
|
||||
DecomposeAttention, _FlipCausalAttention x168 e3c7aa4c
|
||||
DecomposeReduceL2 x3 919a4b2e
|
||||
SplitLargeReduction x132 c9fd97c6
|
||||
_EotOneHotSelect x3 b5dd8d0a
|
||||
_EotSelectBeforeLayerNorm, _EotOneHotSelect x1 9780cd73
|
||||
_Fp16TokenEmbedding x2 777a3503
|
||||
unstamped x199 43397bf9
|
||||
unstamped x187 0da410e5
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
+48 Reshape
|
||||
@@ -101,6 +103,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
786 nodes, weights c43e6785ea78
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 e3c7aa4c
|
||||
SplitLargeReduction x461 fef12197
|
||||
_EotOneHotSelect x3 b5dd8d0a
|
||||
|
||||
@@ -5,7 +5,9 @@ CUDAExecutionProvider
|
||||
unchanged
|
||||
|
||||
CoreMLExecutionProvider
|
||||
+2 MatMul
|
||||
+12 Slice
|
||||
+11 MatMul
|
||||
+9 Add
|
||||
+2 Mul
|
||||
-1 Attention is_causal=0 qk_matmul_output_mode=0 softcap=0.0
|
||||
-1 ReduceL2 keepdims=1 noop_with_empty_axes=0
|
||||
@@ -14,13 +16,14 @@ CoreMLExecutionProvider
|
||||
+1 Sqrt
|
||||
+1 Transpose perm=(0, 1, 3, 2)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
505 nodes, weights 95b5f0ed0d20
|
||||
535 nodes, weights 92f96a725b3d
|
||||
DecomposeAttention x5 b00b8abe
|
||||
DecomposeReduceL2 x3 a689cbf8
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x199 323cfe83
|
||||
SplitLargeReduction x33 46040459
|
||||
_ConstantifyReshapeTarget x9 8c4eb3c1
|
||||
_ScalarGatherToSlice x1 c2f58daf
|
||||
unstamped x288 eda9e19b
|
||||
unstamped x285 8079f14d
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
+2 MatMul
|
||||
@@ -62,21 +65,26 @@ OpenVINOExecutionProvider
|
||||
unstamped x290 20772a87
|
||||
|
||||
RKNPU static
|
||||
+24 Slice
|
||||
+200 Slice
|
||||
+142 Add
|
||||
+112 Conv auto_pad=NOTSET dilations=(1, 1) group=1 pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
+23 MatMul
|
||||
+21 Add
|
||||
+9 Conv auto_pad=NOTSET dilations=(1, 1) group=1 pads=(0, 0, 0, 0) strides=(1, 1)
|
||||
-1 Attention is_causal=0 qk_matmul_output_mode=0 softcap=0.0
|
||||
-1 Cast to=1
|
||||
+1 Mul
|
||||
+1 Softmax axis=-1
|
||||
+1 Transpose perm=(0, 1, 3, 2)
|
||||
569 nodes, weights 12f45dfe2af8
|
||||
987 nodes, weights 7fc618c42854
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x5 b00b8abe
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x199 8d4edbb1
|
||||
SplitLargeReduction x69 a0a2a935
|
||||
FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x144 84f30084
|
||||
SplitLargeConvReduction, FuseBatchNormIntoConv, RemoveOptionalBiasFromConv x473 45af76e7
|
||||
SplitLargeReduction x69 2f748d6a
|
||||
_ConstantifyReshapeTarget x9 8c4eb3c1
|
||||
_ScalarGatherToSlice x1 c2f58daf
|
||||
unstamped x286 fe905832
|
||||
unstamped x286 2bdc87b7
|
||||
|
||||
TensorrtExecutionProvider
|
||||
+2 MatMul
|
||||
|
||||
@@ -0,0 +1,132 @@
|
||||
CPUExecutionProvider
|
||||
unchanged
|
||||
|
||||
CUDAExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
167 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x50 06530e5e
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
unchanged
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-24 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+24 HardSwish
|
||||
-24 Mul
|
||||
144 nodes, weights d3391a68551b
|
||||
FuseBatchNormIntoConv x2 2d29c72c
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x24 88c59ad1
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 9586dfce
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 197fa113
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 971d4d3a
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x51 a0e04758
|
||||
|
||||
RKNPU height=1472 width=736
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":1472,"width":736},{"height":736,"width":736},{"height":992,"width":736},{"height":736,"width":992},{"height":1120,"width":736},{"height":736,"width":1120},{"height":736,"width":1472}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2176 width=1088
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2176,"width":1088},{"height":1088,"width":1088},{"height":1472,"width":1088},{"height":1088,"width":1472},{"height":1632,"width":1088},{"height":1088,"width":1632},{"height":1088,"width":2176}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
RKNPU height=2880 width=1440
|
||||
+3 Add
|
||||
+3 Conv dilations=(1, 1) group=1 kernel_shape=(3, 3) pads=(1, 1, 1, 1) strides=(1, 1)
|
||||
-1 Cast to=1
|
||||
-1 Concat axis=1
|
||||
-1 Sub
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
170 nodes, weights ef297fdbed1f
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"height":2880,"width":1440},{"height":1440,"width":1440},{"height":1920,"width":1440},{"height":1440,"width":1920},{"height":2176,"width":1440},{"height":1440,"width":2176},{"height":1440,"width":2880}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x7 95c1e4a7
|
||||
FuseBatchNormIntoConv x1 188ee567
|
||||
FuseBatchNormIntoConvTranspose, _FoldBiasAdd x1 01869e18
|
||||
_DecomposeHardSwish x48 03b81a7a
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x9 88effc35
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x6 556032f0
|
||||
_FoldAffineBeforeConv x1 97363f91
|
||||
_FoldAffineScaleBeforeConv x3 20599d5b
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 4c022d13
|
||||
_FoldBiasAdd x5 f89d5e54
|
||||
_FoldSeResidual x16 528c3523
|
||||
unstamped x47 eda712e6
|
||||
|
||||
TensorrtExecutionProvider
|
||||
unchanged
|
||||
@@ -0,0 +1,163 @@
|
||||
CPUExecutionProvider
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
194 nodes, weights d4bc27d463ac
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x77 07b210e0
|
||||
|
||||
CUDAExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-4 Add
|
||||
-3 LayerNormalization axis=-1 epsilon=9.999999747378752e-06 stash_type=1
|
||||
+3 SkipLayerNormalization epsilon=9.999999747378752e-06
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 LayerNormalization axis=-1 epsilon=9.999999974752427e-07 stash_type=1
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 SkipLayerNormalization epsilon=9.999999974752427e-07
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
166 nodes, weights d4bc27d463ac
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
FuseSkipLayerNorm, LayerNormBiasFusion, LayerNormFusion x4 dfce4419
|
||||
LayerNormBiasFusion, LayerNormFusion x1 2a80a1b2
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 1f22e914
|
||||
unstamped x75 b10bd6c0
|
||||
|
||||
CoreMLExecutionProvider
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
197 nodes, weights d4bc27d463ac
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x80 247ec9fe
|
||||
|
||||
MIGraphXExecutionProvider
|
||||
unchanged
|
||||
|
||||
NvTensorRTRTXExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights d4bc27d463ac
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
|
||||
OpenVINOExecutionProvider
|
||||
-28 HardSigmoid alpha=0.1666666716337204 beta=0.5
|
||||
+28 HardSwish
|
||||
-28 Mul
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=6
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Softmax axis=2
|
||||
-1 Sub
|
||||
164 nodes, weights d4bc27d463ac
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseHardSwish, _DecomposeHardSwish, _DecomposeHardSwish x28 b3760222
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 b9316958
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 ff145bf3
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 87e9a09a
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 5772e2e9
|
||||
|
||||
RKNPU width=2048
|
||||
-2 Sub
|
||||
+1 Add
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 Cast to=1
|
||||
-1 Cast to=6
|
||||
-1 Concat axis=1
|
||||
+1 Concat axis=3
|
||||
+1 Conv auto_pad=NOTSET dilations=(1, 1) group=1 kernel_shape=(1, 3) pads=(0, 1, 0, 1) strides=(1, 1)
|
||||
-1 Exp
|
||||
-1 Reciprocal
|
||||
-1 ReduceMax keepdims=1
|
||||
-1 ReduceSum keepdims=0
|
||||
+1 Split axis=1
|
||||
+1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
+1 Transpose perm=(0, 3, 2, 1)
|
||||
+1 Unsqueeze
|
||||
194 nodes, weights 1122beeac490
|
||||
config {'mean_values': [[127.5, 127.5, 127.5]], 'std_values': [[1.0, 1.0, 1.0]]}
|
||||
contract {"dims":[{"width":2048},{"width":224},{"width":320},{"width":448},{"width":640},{"width":1280}]}
|
||||
opset 19
|
||||
FoldConcatIntoConv, FuseBatchNormIntoConv x3 f950ecb9
|
||||
FuseBatchNormIntoConv x5 5453ec31
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x75 57f586e5
|
||||
|
||||
TensorrtExecutionProvider
|
||||
-1 ArgMax axis=2 keepdims=0
|
||||
-1 ReduceMax keepdims=1
|
||||
+1 Squeeze
|
||||
+1 TopK axis=2 largest=1 sorted=1
|
||||
198 nodes, weights d4bc27d463ac
|
||||
FuseBatchNormIntoConv x6 57c49d14
|
||||
FuseGreedyCtcTopK x2 17e81cc8
|
||||
LayerNormBiasFusion, LayerNormFusion x5 2fcd7a68
|
||||
_DecomposeHardSwish x56 a16778d4
|
||||
_FlattenToSqueeze x1 58119faf
|
||||
_FoldAffineAfterConv, _FoldAffineBeforeConv, _FoldBiasAdd x12 1da27dec
|
||||
_FoldAffineAfterConv, _FoldBiasAdd x3 16ed0de4
|
||||
_FoldAffineScaleBeforeConv, _FoldAffineAfterConv, _FoldBiasAdd x26 030aa498
|
||||
_FoldBiasAdd x4 b3c02511
|
||||
_MoveAffinePastPool x3 96c2aa8d
|
||||
_UnflattenToUnsqueeze x1 ea488eee
|
||||
unstamped x79 04db7477
|
||||
@@ -98,6 +98,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
575 nodes, weights bd358fcd6a2e
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x156 f5d0980b
|
||||
DecomposeGelu x60 a6662a53
|
||||
SplitLargeReduction x204 1e2c9a0f
|
||||
|
||||
@@ -116,6 +116,8 @@ RKNPU static
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
625 nodes, weights f4a1efb0a750
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x169 e55b1e5b
|
||||
DecomposeGelu x65 5a4f24cb
|
||||
OpaqueZeroMul x1 3037fff5
|
||||
|
||||
@@ -98,6 +98,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
575 nodes, weights 03ceec45ed24
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x156 f5d0980b
|
||||
DecomposeGelu x60 a6662a53
|
||||
SplitLargeReduction x204 1e2c9a0f
|
||||
|
||||
@@ -116,6 +116,8 @@ RKNPU static
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
625 nodes, weights 34e0e1b578dc
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x169 e55b1e5b
|
||||
DecomposeGelu x65 5a4f24cb
|
||||
OpaqueZeroMul x1 3037fff5
|
||||
|
||||
@@ -98,6 +98,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
575 nodes, weights 01dd81e48ef4
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x156 f5d0980b
|
||||
DecomposeGelu x60 a6662a53
|
||||
SplitLargeReduction x204 1e2c9a0f
|
||||
|
||||
@@ -116,6 +116,8 @@ RKNPU static
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
625 nodes, weights e73d63d50385
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x169 e55b1e5b
|
||||
DecomposeGelu x65 5a4f24cb
|
||||
OpaqueZeroMul x1 3037fff5
|
||||
|
||||
@@ -98,6 +98,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
575 nodes, weights d979523f1944
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x156 f5d0980b
|
||||
DecomposeGelu x60 a6662a53
|
||||
SplitLargeReduction x204 1e2c9a0f
|
||||
|
||||
@@ -116,6 +116,8 @@ RKNPU static
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
625 nodes, weights 9aa96af3c7bb
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x169 e55b1e5b
|
||||
DecomposeGelu x65 5a4f24cb
|
||||
OpaqueZeroMul x1 3037fff5
|
||||
|
||||
@@ -98,6 +98,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
575 nodes, weights 6d287069d30e
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x156 f5d0980b
|
||||
DecomposeGelu x60 a6662a53
|
||||
SplitLargeReduction x204 1e2c9a0f
|
||||
|
||||
@@ -116,6 +116,8 @@ RKNPU static
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
625 nodes, weights e80f248df57d
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x169 e55b1e5b
|
||||
DecomposeGelu x65 5a4f24cb
|
||||
OpaqueZeroMul x1 3037fff5
|
||||
|
||||
@@ -98,6 +98,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
575 nodes, weights 58bb2d2823fa
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x156 f5d0980b
|
||||
DecomposeGelu x60 a6662a53
|
||||
SplitLargeReduction x204 1e2c9a0f
|
||||
|
||||
@@ -116,6 +116,8 @@ RKNPU static
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
625 nodes, weights d4d7d2e5ae45
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x169 e55b1e5b
|
||||
DecomposeGelu x65 5a4f24cb
|
||||
OpaqueZeroMul x1 3037fff5
|
||||
|
||||
@@ -104,6 +104,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
554 nodes, weights 62d2c91890b6
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 06d4787f
|
||||
DecomposeGelu x60 55e0b8fd
|
||||
SplitLargeReduction x168 91a1c6ab
|
||||
|
||||
@@ -132,6 +132,8 @@ RKNPU static
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
764 nodes, weights 794e1989a736
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x156 85a31e97
|
||||
DecomposeGelu x60 8e465049
|
||||
PatchEmbedToMatMul, _ConstantifyReshapeTarget, RemoveOptionalBiasFromConv x5 37ecaa30
|
||||
|
||||
@@ -104,6 +104,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
554 nodes, weights 62d2c91890b6
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 06d4787f
|
||||
DecomposeGelu x60 55e0b8fd
|
||||
SplitLargeReduction x168 91a1c6ab
|
||||
|
||||
@@ -132,6 +132,8 @@ RKNPU static
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
764 nodes, weights 794e1989a736
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x156 85a31e97
|
||||
DecomposeGelu x60 8e465049
|
||||
PatchEmbedToMatMul, _ConstantifyReshapeTarget, RemoveOptionalBiasFromConv x5 37ecaa30
|
||||
|
||||
@@ -104,6 +104,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
518 nodes, weights 4a3138cd2cac
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 06d4787f
|
||||
DecomposeGelu x60 55e0b8fd
|
||||
SplitLargeReduction x132 8d307a1d
|
||||
|
||||
@@ -132,6 +132,8 @@ RKNPU static
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
580 nodes, weights 1f22a4c94a87
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x156 85a31e97
|
||||
DecomposeGelu x60 8e465049
|
||||
PatchEmbedToMatMul, _ConstantifyReshapeTarget, RemoveOptionalBiasFromConv x5 37ecaa30
|
||||
|
||||
@@ -104,6 +104,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
518 nodes, weights 4639a36af07b
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 06d4787f
|
||||
DecomposeGelu x60 55e0b8fd
|
||||
SplitLargeReduction x132 8d307a1d
|
||||
|
||||
@@ -132,6 +132,8 @@ RKNPU static
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
580 nodes, weights 9161f75faa9f
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x156 85a31e97
|
||||
DecomposeGelu x60 8e465049
|
||||
PatchEmbedToMatMul, _ConstantifyReshapeTarget, RemoveOptionalBiasFromConv x5 37ecaa30
|
||||
|
||||
@@ -101,6 +101,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
494 nodes, weights 17498fc5312c
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 e3c7aa4c
|
||||
SplitLargeReduction x132 d3b9957d
|
||||
_EotOneHotSelect x3 b5dd8d0a
|
||||
|
||||
@@ -129,6 +129,8 @@ RKNPU static
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
556 nodes, weights a086caacb39f
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x156 04519fbd
|
||||
PatchEmbedToMatMul, _ConstantifyReshapeTarget, RemoveOptionalBiasFromConv x5 37ecaa30
|
||||
SplitLargeReduction x204 61274ad0
|
||||
|
||||
@@ -98,6 +98,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
575 nodes, weights 00dbe6ad020c
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x156 f5d0980b
|
||||
DecomposeGelu x60 a6662a53
|
||||
SplitLargeReduction x204 1e2c9a0f
|
||||
|
||||
@@ -97,9 +97,9 @@ OpenVINOExecutionProvider
|
||||
unstamped x191 0eafaea6
|
||||
|
||||
RKNPU static
|
||||
+92 MatMul
|
||||
+79 Add
|
||||
+78 Slice
|
||||
+97 MatMul
|
||||
+84 Add
|
||||
+84 Slice
|
||||
+54 Reshape
|
||||
+53 Transpose perm=(0, 2, 1, 3)
|
||||
+38 Mul
|
||||
@@ -115,12 +115,15 @@ RKNPU static
|
||||
+1 Sub
|
||||
-1 Transpose perm=(0, 2, 1)
|
||||
-1 Transpose perm=(0, 3, 1, 2)
|
||||
625 nodes, weights 5a3e4d97371d
|
||||
641 nodes, weights 5a3e4d97371d
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention x169 e55b1e5b
|
||||
DecomposeGelu x65 5a4f24cb
|
||||
OpaqueZeroMul x1 3037fff5
|
||||
PatchEmbedToMatMul, _ConstantifyReshapeTarget x5 37ecaa30
|
||||
PatchEmbedToMatMul, _ConstantifyReshapeTarget x4 6fa42cac
|
||||
SplitLargeReduction x221 e1527d17
|
||||
SplitLargeReduction, PatchEmbedToMatMul, _ConstantifyReshapeTarget x17 03d5dda6
|
||||
_ScalarGatherToSlice x1 60360a10
|
||||
unstamped x163 b6aec873
|
||||
|
||||
|
||||
@@ -104,6 +104,8 @@ RKNPU static
|
||||
+12 Softmax axis=-1
|
||||
+12 Transpose perm=(0, 1, 3, 2)
|
||||
518 nodes, weights 5c8848887d0e
|
||||
contract {"dims":[{}]}
|
||||
opset 19
|
||||
DecomposeAttention, _FlipCausalAttention x168 06d4787f
|
||||
DecomposeGelu x60 55e0b8fd
|
||||
SplitLargeReduction x132 8d307a1d
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user