mirror of
https://github.com/sunnypilot/sunnypilot.git
synced 2026-08-23 06:43:47 +08:00
Compare commits
3 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 1dd14656be | |||
| 4f46433e2b | |||
| 5a8567e3e7 |
@@ -8,17 +8,35 @@ env:
|
||||
HF_DEFAULTS_PATH: models/defaults/big
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jobs:
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resolve_name:
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runs-on: ubuntu-24.04
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outputs:
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model_name: ${{ steps.name.outputs.model_name }}
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onnx_ref: ${{ steps.name.outputs.onnx_ref }}
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steps:
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- uses: actions/checkout@v4
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- id: name
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run: |
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NAME=$(PYTHONPATH=${{ github.workspace }} python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL; print(DEFAULT_BIG_MODEL)")
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ONNX_REF=$(git log -1 --format='%H' -- openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx)
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echo "model_name=${NAME}" >> $GITHUB_OUTPUT
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echo "onnx_ref=$ONNX_REF" >> $GITHUB_OUTPUT
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build_model:
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needs: resolve_name
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uses: ./.github/workflows/sunnypilot-build-model.yaml
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with:
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upstream_branch: ${{ github.sha }}
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custom_name: default-big-model
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upstream_branch: ${{ needs.resolve_name.outputs.onnx_ref }}
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custom_name: ${{ needs.resolve_name.outputs.model_name }}
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target_hardware: usbgpu
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secrets: inherit
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upload_defaults:
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needs: build_model
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needs: [ resolve_name, build_model ]
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runs-on: ubuntu-24.04
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permissions:
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id-token: write
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contents: write
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steps:
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- uses: actions/checkout@v4
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with:
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@@ -31,7 +49,7 @@ jobs:
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- name: Download artifact name
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uses: actions/download-artifact@v4
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with:
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name: artifact-name-default-big-model
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name: artifact-name-${{ needs.resolve_name.outputs.model_name }}
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path: artifact_name
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- name: Read artifact name
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@@ -46,33 +64,20 @@ jobs:
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name: ${{ steps.artifact.outputs.artifact_name }}
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path: output
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- name: Upload model to HF defaults
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- name: Upload to HF and update default_models.json
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env:
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HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
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ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
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run: |
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rm -f output/artifact_name.txt
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hf upload ${{ env.HF_REPO }} \
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output/ \
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"${HF_DEFAULTS_PATH}/${ARTIFACT_NAME}/" \
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--repo-type=dataset
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- name: Get tinygrad ref and ONNX hash
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id: meta
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run: |
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export PYTHONPATH=$(pwd)
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echo "tinygrad_ref=$(python3 openpilot/sunnypilot/models/tinygrad_ref.py)" >> $GITHUB_OUTPUT
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echo "onnx_sha256=$(sha256sum openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx | cut -d' ' -f1)" >> $GITHUB_OUTPUT
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- name: Update default_models.json on HF
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env:
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HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
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ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
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run: |
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python3 release/ci/upload_default_model.py \
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--hf-repo "${{ env.HF_REPO }}" \
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--hf-defaults-path "${{ env.HF_DEFAULTS_PATH }}" \
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--artifact-name "$ARTIFACT_NAME" \
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--metadata-path "output/metadata.json" \
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--onnx-sha256 "${{ steps.meta.outputs.onnx_sha256 }}" \
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--tinygrad-ref "${{ steps.meta.outputs.tinygrad_ref }}"
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--model-dir output \
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--onnx-path "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" \
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--onnx-ref "${{ needs.resolve_name.outputs.onnx_ref }}" \
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--model-name "${{ needs.resolve_name.outputs.model_name }}" \
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--tinygrad-ref "$(python3 openpilot/sunnypilot/models/tinygrad_ref.py)" \
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--run-number "${{ github.run_number }}"
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@@ -36,6 +36,7 @@ jobs:
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publish_concurrency_group: ${{ steps.strategy.outputs.publish_concurrency_group }}
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is_stable_branch: ${{ steps.strategy.outputs.is_stable_branch }}
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build: ${{ steps.strategy.outputs.build }}
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include_big_model: ${{ steps.strategy.outputs.include_big_model }}
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steps:
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- uses: actions/checkout@v4
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- name: Extract deploy strategy
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@@ -78,6 +79,9 @@ jobs:
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stable_version=$(cat openpilot/sunnypilot/common/version.h | grep SUNNYPILOT_VERSION | sed -e 's/[^0-9|.]//g');
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echo "version=$([ "$is_stable_branch" = "true" ] && echo "$stable_version" || echo "$BUILD")" >> $GITHUB_OUTPUT
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echo "extra_version_identifier=${environment}" >> $GITHUB_OUTPUT
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|
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include_big_model="$(echo "$CONFIG" | jq -r '.include_big_model // false')";
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echo "include_big_model=$include_big_model" >> $GITHUB_OUTPUT
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fi
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echo "build=$BUILD" >> $GITHUB_OUTPUT
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cat $GITHUB_OUTPUT
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@@ -203,6 +207,101 @@ jobs:
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source ${UV_PROJECT_ENVIRONMENT}/bin/activate
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PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
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|
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prepare_chestnut:
|
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needs: [ prepare_strategy ]
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||||
runs-on: ubuntu-24.04
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if: ${{ needs.prepare_strategy.outputs.include_big_model == 'true' }}
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env:
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HF_REPO: sunnypilot/sunnypilot_models_v1
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HF_DEFAULTS_PATH: models/defaults/big
|
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steps:
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- uses: actions/checkout@v4
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with:
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ref: ${{ github.head_ref || github.ref_name }}
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- run: git lfs pull -I "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
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- name: Check HF defaults and build if needed
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id: resolve
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run: |
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ACTUAL_ONNX_HASH=$(sha256sum "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" | cut -d' ' -f1)
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echo "Repo ONNX hash: $ACTUAL_ONNX_HASH"
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JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
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check_hash() {
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DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
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BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ACTUAL_ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
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[ -n "$BUNDLE" ] && [ "$BUNDLE" != "null" ]
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}
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if check_hash; then
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echo "HF defaults match repo ONNX"
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else
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echo "No matching model on HF — triggering build"
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gh workflow run build-default-big-model.yaml --ref "${{ github.head_ref || github.ref_name }}"
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echo "Waiting for build to start..."
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sleep 120
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RUN_ID=$(gh run list --workflow=build-default-big-model.yaml --branch="${{ github.head_ref || github.ref_name }}" --limit=1 --json databaseId --jq '.[0].databaseId')
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if [ -z "$RUN_ID" ] || [ "$RUN_ID" = "null" ]; then
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echo "::error::Failed to find build-default-big-model run"
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exit 1
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fi
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echo "Waiting for run $RUN_ID..."
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gh run watch "$RUN_ID"
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CONCLUSION=$(gh run view "$RUN_ID" --json conclusion --jq '.conclusion')
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if [ "$CONCLUSION" != "success" ]; then
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echo "::error::build-default-big-model failed: $CONCLUSION"
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exit 1
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||||
fi
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||||
|
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if ! check_hash; then
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echo "::error::HF defaults still don't match after build"
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exit 1
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||||
fi
|
||||
fi
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||||
env:
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||||
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
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- name: Download big model chunks
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||||
run: |
|
||||
ACTUAL_ONNX_HASH=$(sha256sum "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" | cut -d' ' -f1)
|
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JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
|
||||
DEFAULTS=$(curl -fsSL "$JSON_URL")
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||||
BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ACTUAL_ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)')
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mkdir -p big_model_chunks
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ARTIFACT=$(echo "$BUNDLE" | jq -r '.models[0].artifact')
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BASE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url' | sed 's|/[^/]*$||')
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NUM_CHUNKS=$(echo "$ARTIFACT" | jq -r '.chunks | length')
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CANONICAL="big_driving_tinygrad.pkl"
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echo "$ARTIFACT" | jq -r '.chunks[].file_name' | while read CHUNK_NAME; do
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CHUNK_IDX=$(echo "$CHUNK_NAME" | grep -oP 'chunk\K[0-9]+of[0-9]+')
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CANONICAL_CHUNK="${CANONICAL}.chunk${CHUNK_IDX}"
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ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${CHUNK_NAME}', safe=':/'))")
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echo "Downloading $CHUNK_NAME -> $CANONICAL_CHUNK"
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curl -fsSL -o "big_model_chunks/${CANONICAL_CHUNK}" "$ENCODED_URL"
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done
|
||||
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||||
echo "$NUM_CHUNKS" > "big_model_chunks/${CANONICAL}.chunkmanifest"
|
||||
|
||||
- name: Upload big model chunks
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||||
uses: actions/upload-artifact@v4
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||||
with:
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name: big-model-chunks
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||||
path: big_model_chunks/
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compression-level: 0
|
||||
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- name: Cancel run on failure
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if: failure()
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run: gh run cancel ${{ github.run_id }}
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
publish:
|
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concurrency:
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||||
@@ -211,14 +310,20 @@ jobs:
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# Otherwise, if a job is waiting to be published due to environment wait time, it would be canceled by a new commit and restart the wait time.
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||||
group: ${{ needs.prepare_strategy.outputs.publish_concurrency_group }}
|
||||
cancel-in-progress: ${{ needs.prepare_strategy.outputs.cancel_publish_in_progress == 'true' }}
|
||||
if: ${{ (always() && !cancelled() && !failure()) && needs.build.result == 'success' && needs.prepare_strategy.result == 'success' && (!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt')) }}
|
||||
needs: [ build, prepare_strategy ]
|
||||
if: ${{
|
||||
always() && !cancelled() &&
|
||||
needs.build.result == 'success' &&
|
||||
needs.prepare_strategy.result == 'success' &&
|
||||
(!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt')) &&
|
||||
(needs.prepare_strategy.outputs.include_big_model != 'true' || needs.prepare_chestnut.result == 'success')
|
||||
}}
|
||||
needs: [ build, prepare_strategy, prepare_chestnut ]
|
||||
runs-on: ubuntu-24.04
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||||
environment: ${{ needs.prepare_strategy.outputs.environment }}
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Download build artifacts
|
||||
- name: Download prebuilt artifact
|
||||
uses: actions/download-artifact@v4
|
||||
with:
|
||||
name: prebuilt
|
||||
@@ -228,6 +333,24 @@ jobs:
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||||
mkdir -p ${{ env.OUTPUT_DIR }}
|
||||
tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
|
||||
|
||||
- name: Prepare chestnut output
|
||||
if: ${{ needs.prepare_chestnut.result == 'success' }}
|
||||
run: |
|
||||
mkdir -p "${{ github.workspace }}/chestnut_output"
|
||||
tar xzf prebuilt.tar.gz -C "${{ github.workspace }}/chestnut_output"
|
||||
|
||||
- name: Download big model chunks
|
||||
if: ${{ needs.prepare_chestnut.result == 'success' }}
|
||||
uses: actions/download-artifact@v4
|
||||
with:
|
||||
name: big-model-chunks
|
||||
path: big_model_chunks
|
||||
|
||||
- name: Inject big model into chestnut
|
||||
if: ${{ needs.prepare_chestnut.result == 'success' }}
|
||||
run: |
|
||||
cp big_model_chunks/* "${{ github.workspace }}/chestnut_output/openpilot/selfdrive/modeld/models/"
|
||||
|
||||
- name: Configure Git
|
||||
run: |
|
||||
git config --global user.email "github-actions[bot]@users.noreply.github.com"
|
||||
@@ -248,6 +371,22 @@ jobs:
|
||||
"https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
|
||||
"${{ needs.prepare_strategy.outputs.extra_version_identifier }}"
|
||||
|
||||
- name: Publish chestnut branch
|
||||
if: ${{ needs.prepare_chestnut.result == 'success' }}
|
||||
env:
|
||||
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
run: |
|
||||
CHESTNUT_BRANCH="${{ needs.prepare_strategy.outputs.new_branch }}-chestnut"
|
||||
CHESTNUT_DIR="${{ github.workspace }}/chestnut_output"
|
||||
|
||||
${{ env.CI_DIR }}/publish.sh \
|
||||
"${{ github.workspace }}" \
|
||||
"$CHESTNUT_DIR" \
|
||||
"$CHESTNUT_BRANCH" \
|
||||
"${{ needs.prepare_strategy.outputs.version }}" \
|
||||
"https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
|
||||
"${{ needs.prepare_strategy.outputs.extra_version_identifier }}"
|
||||
|
||||
- name: Tag ${{ needs.prepare_strategy.outputs.environment }}
|
||||
if: ${{ needs.prepare_strategy.outputs.is_stable_branch == 'true' && (github.event_name != 'push' || !startsWith(github.ref, 'refs/tags/')) }}
|
||||
run: |
|
||||
@@ -260,6 +399,7 @@ jobs:
|
||||
- prepare_strategy
|
||||
- build
|
||||
- publish
|
||||
- prepare_chestnut
|
||||
runs-on: ubuntu-24.04
|
||||
if: ${{ (always() && !cancelled() && !failure())
|
||||
&& needs.publish.result == 'success'
|
||||
@@ -279,6 +419,7 @@ jobs:
|
||||
export commit_short_sha="${commit_short_sha:0:7}"
|
||||
export extra_version_identifier="${{ needs.prepare_strategy.outputs.extra_version_identifier || github.run_number }}"
|
||||
export PUBLIC_REPO_URL="${{ env.PUBLIC_REPO_URL }}"
|
||||
export chestnut_branch="${{ needs.prepare_chestnut.result == 'success' && format('{0}-chestnut', needs.prepare_strategy.outputs.new_branch) || '' }}"
|
||||
|
||||
MESSAGE=$(cat << 'EOF' | envsubst
|
||||
${{ vars.DISCOURSE_GENERAL_UPDATE_NOTICE }}
|
||||
|
||||
@@ -16,6 +16,15 @@ MASTER_SP_BRANCHES = ['master']
|
||||
RELEASE_BRANCHES = ['release-tizi-staging', 'release-mici-staging', 'release-tizi', 'release-mici', 'nightly']
|
||||
TESTED_BRANCHES = RELEASE_BRANCHES + ['devel-staging', 'nightly-dev'] + RELEASE_SP_BRANCHES + TESTED_SP_BRANCHES
|
||||
|
||||
CHESTNUT_BRANCHES = {
|
||||
"staging": "staging-chestnut",
|
||||
"dev": "dev-chestnut",
|
||||
"release-mici": "release-chestnut",
|
||||
"release-tizi": "release-chestnut",
|
||||
"release-mici-staging": "release-chestnut-staging",
|
||||
"release-tizi-staging": "release-chestnut-staging",
|
||||
}
|
||||
|
||||
SP_BRANCH_MIGRATIONS = {
|
||||
("tici", "staging-c3-new"): "staging-tici",
|
||||
("tici", "dev-c3-new"): "staging-tici",
|
||||
|
||||
@@ -18,7 +18,7 @@
|
||||
"_comment": "Set extra field to the failed reason."
|
||||
},
|
||||
"Offroad_ChestnutBranch": {
|
||||
"text": "Chestnut detected! Switch to the release-chestnut branch to use chestnut-class models.",
|
||||
"text": "Chestnut detected! Switch to the %1 branch to use chestnut-class models.",
|
||||
"severity": 0
|
||||
},
|
||||
"Offroad_UnregisteredHardware": {
|
||||
|
||||
@@ -7,6 +7,7 @@ See the LICENSE.md file in the root directory for more details.
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import math
|
||||
import os
|
||||
import tempfile
|
||||
import time
|
||||
@@ -66,14 +67,15 @@ def get_policy_npy_shapes(input_shapes: dict, is_supercombo: bool = False) -> tu
|
||||
if desire_key:
|
||||
shapes['desire'] = (input_shapes[desire_key][2],)
|
||||
|
||||
if is_supercombo and 'features_buffer' in input_shapes:
|
||||
fb = input_shapes['features_buffer']
|
||||
shapes['prev_feat'] = (fb[0], fb[2])
|
||||
|
||||
for key, shape in input_shapes.items():
|
||||
if key not in (desire_key, 'features_buffer') and 'img' not in key:
|
||||
shapes[key] = tuple(shape)
|
||||
|
||||
if is_supercombo and 'features_buffer' in input_shapes:
|
||||
fb = input_shapes['features_buffer']
|
||||
feat_dim = math.prod(fb[2:])
|
||||
shapes['prev_feat'] = (fb[0], feat_dim)
|
||||
|
||||
sizes = [int(np.prod(size)) for size in shapes.values()]
|
||||
return shapes, sizes
|
||||
|
||||
@@ -117,8 +119,9 @@ def generate_queues_and_npy(input_shapes: dict, frame_skip: int, device: str = D
|
||||
}
|
||||
|
||||
if features_buffer:
|
||||
feat_dim = math.prod(features_buffer[2:])
|
||||
feat_q_len = frame_skip * features_buffer[1] if is_supercombo else frame_skip * (features_buffer[1] - 1) + 1
|
||||
queues['feat_q'] = Tensor(np.zeros((feat_q_len, features_buffer[0], features_buffer[2]),
|
||||
queues['feat_q'] = Tensor(np.zeros((feat_q_len, features_buffer[0], feat_dim),
|
||||
dtype=np.float32), device=device).contiguous().realize()
|
||||
|
||||
queues.update({key: Tensor(value, device='NPY').realize() for key, value in npy_arrays.items() if key in ('tfm', 'big_tfm')})
|
||||
@@ -183,14 +186,14 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,
|
||||
warped_dev = warped.to(Device.DEFAULT)
|
||||
Tensor.realize(packed_npy_inputs_dev, warped_dev)
|
||||
|
||||
img = shift_and_sample(img_q, warped_dev[0:1], sample_skip_fn).realize()
|
||||
big_img = shift_and_sample(big_img_q, warped_dev[1:2], sample_skip_fn).realize()
|
||||
img = shift_and_sample(img_q, warped_dev[0:1], sample_skip_fn)
|
||||
big_img = shift_and_sample(big_img_q, warped_dev[1:2], sample_skip_fn)
|
||||
|
||||
unpacked_tensors = [tensor.reshape(shape) for tensor, shape in zip(packed_npy_inputs_dev.split(npy_sizes), npy_shapes.values(), strict=True)]
|
||||
unpacked_dict = dict(zip(npy_shapes.keys(), unpacked_tensors, strict=True))
|
||||
|
||||
desire_dev = unpacked_dict['desire']
|
||||
desire_buf = shift_and_sample(desire_q, desire_dev.reshape(1, 1, -1), sample_desire_fn).realize()
|
||||
desire_buf = shift_and_sample(desire_q, desire_dev.reshape(1, 1, -1), sample_desire_fn)
|
||||
|
||||
inputs = {desire_key: desire_buf}
|
||||
for key, tensor_val in unpacked_dict.items():
|
||||
@@ -199,19 +202,22 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,
|
||||
|
||||
if 'prev_feat' in unpacked_dict:
|
||||
prev_feat_dev = unpacked_dict['prev_feat']
|
||||
inputs['features_buffer'] = shift_and_sample(feat_q, prev_feat_dev.reshape(1, 1, -1), sample_skip_fn).realize()
|
||||
feat_buf = shift_and_sample(feat_q, prev_feat_dev.reshape(1, 1, -1), sample_skip_fn)
|
||||
inputs['features_buffer'] = feat_buf if len(fb := input_shapes['features_buffer']) <= 3 else feat_buf.reshape(fb)
|
||||
|
||||
if vision_runner:
|
||||
vision_out_cast = next(iter(vision_runner({road_key: img, wide_key: big_img}).values())).cast('float32').realize()
|
||||
if 'features_buffer' not in inputs:
|
||||
new_feat = vision_out_cast[:, features_slice].reshape(1, -1).unsqueeze(0)
|
||||
inputs['features_buffer'] = shift_and_sample(feat_q, new_feat, sample_skip_fn).realize()
|
||||
feat_buf = shift_and_sample(feat_q, new_feat, sample_skip_fn).realize()
|
||||
inputs['features_buffer'] = feat_buf if len(fb := input_shapes['features_buffer']) <= 3 else feat_buf.reshape(fb)
|
||||
policy_outs = [next(iter(pol_runner(inputs).values())).cast('float32').realize() for pol_runner in policy_runners]
|
||||
return (vision_out_cast, *policy_outs) if len(policy_outs) > 1 else (vision_out_cast, policy_outs[0])
|
||||
|
||||
inputs.update({road_key: img, wide_key: big_img})
|
||||
if 'features_buffer' not in inputs:
|
||||
inputs['features_buffer'] = sample_skip_fn(feat_q)
|
||||
feat_buf = sample_skip_fn(feat_q)
|
||||
inputs['features_buffer'] = feat_buf if len(fb := input_shapes['features_buffer']) <= 3 else feat_buf.reshape(fb)
|
||||
|
||||
policy_out = next(iter(policy_runners[0](inputs).values())).cast('float32').realize()
|
||||
if 'features_buffer' not in inputs and features_slice is not None:
|
||||
|
||||
@@ -195,3 +195,85 @@ class TestReadFileChunkedToDisk(OpenpilotTestCase):
|
||||
|
||||
assert out.parent == Path(d)
|
||||
assert out.read_bytes() == payload
|
||||
|
||||
|
||||
class Test4DFeaturesBuffer(OpenpilotTestCase):
|
||||
def test_get_policy_npy_shapes_4d(self):
|
||||
from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes
|
||||
input_shapes = {
|
||||
'desire_pulse': (1, 25, 8),
|
||||
'features_buffer': (1, 24, 32, 512), # compare 4d to 3d for regression
|
||||
'traffic_convention': (1, 2),
|
||||
'action_t': (1, 2)
|
||||
}
|
||||
shapes, sizes = get_policy_npy_shapes(input_shapes, is_supercombo=True)
|
||||
assert shapes['prev_feat'] == (1, 16384)
|
||||
assert sizes == [8, 2, 2, 16384]
|
||||
|
||||
def test_get_policy_npy_shapes_3d(self):
|
||||
from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes
|
||||
input_shapes = {
|
||||
'desire_pulse': (1, 25, 8),
|
||||
'features_buffer': (1, 24, 512),
|
||||
'traffic_convention': (1, 2),
|
||||
'action_t': (1, 2)
|
||||
}
|
||||
shapes, sizes = get_policy_npy_shapes(input_shapes, is_supercombo=True)
|
||||
assert shapes['prev_feat'] == (1, 512)
|
||||
assert sizes == [8, 2, 2, 512]
|
||||
|
||||
|
||||
class TestStockCompileModeldEquivalence(OpenpilotTestCase):
|
||||
def test_get_policy_npy_shapes_matches_stock(self):
|
||||
from openpilot.selfdrive.modeld.compile_modeld import get_policy_npy_shapes as stock_get_policy_npy_shapes
|
||||
from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes as sunny_get_policy_npy_shapes
|
||||
|
||||
stock_input_shapes = {
|
||||
'desire_pulse': (1, 25, 8),
|
||||
'features_buffer': (1, 24, 512), # see below comment
|
||||
'traffic_convention': (1, 2),
|
||||
'action_t': (1, 2),
|
||||
}
|
||||
|
||||
stock_shapes, stock_sizes = stock_get_policy_npy_shapes(stock_input_shapes)
|
||||
sunny_shapes, sunny_sizes = sunny_get_policy_npy_shapes(stock_input_shapes, is_supercombo=True)
|
||||
|
||||
assert sunny_shapes == stock_shapes
|
||||
assert sunny_sizes == stock_sizes
|
||||
assert sunny_shapes['prev_feat'] == (1, 512)
|
||||
|
||||
def test_make_input_queues_full_stock_equivalence(self):
|
||||
from openpilot.selfdrive.modeld.compile_modeld import make_input_queues as stock_make_input_queues
|
||||
from openpilot.sunnypilot.modeld_v2.compile_modeld import make_supercombo_input_queues as sunny_make_supercombo_input_queues
|
||||
input_shapes = {
|
||||
'img': (1, 12, 128, 256),
|
||||
'desire_pulse': (1, 25, 8),
|
||||
'features_buffer': (1, 24, 512), # when https://github.com/commaai/openpilot/pull/38681 merges, update to 1,24,32,512
|
||||
'traffic_convention': (1, 2),
|
||||
'action_t': (1, 2),
|
||||
}
|
||||
frame_skip = 4
|
||||
|
||||
stock_queues, stock_npy = stock_make_input_queues(input_shapes, frame_skip, device='NPY')
|
||||
sunny_queues, sunny_npy = sunny_make_supercombo_input_queues(input_shapes, frame_skip, device='NPY')
|
||||
assert set(sunny_queues.keys()) == set(stock_queues.keys())
|
||||
for key in stock_queues:
|
||||
assert sunny_queues[key].shape == stock_queues[key].shape, \
|
||||
f"Queue shape mismatch for {key}: sunny {sunny_queues[key].shape} != stock {stock_queues[key].shape}"
|
||||
assert set(sunny_npy.keys()) == set(stock_npy.keys())
|
||||
for key in stock_npy:
|
||||
assert sunny_npy[key].shape == stock_npy[key].shape, \
|
||||
f"Numpy array shape mismatch for {key}: sunny {sunny_npy[key].shape} != stock {stock_npy[key].shape}"
|
||||
|
||||
def test_make_warp_queues_stock_equivalence(self):
|
||||
from openpilot.selfdrive.modeld.compile_modeld import make_warp_input_queues as stock_make_warp_queues
|
||||
from openpilot.sunnypilot.modeld_v2.compile_modeld import make_warp_queues as sunny_make_warp_queues
|
||||
stock_vision_shapes = {'img': (1, 12, 128, 256)} # for now?
|
||||
stock_queues, stock_npy = stock_make_warp_queues(stock_vision_shapes, frame_skip=4, device='NPY')
|
||||
sunny_queues, sunny_npy = sunny_make_warp_queues(device='NPY')
|
||||
|
||||
assert set(sunny_npy.keys()) == set(stock_npy.keys()) == {'tfm', 'big_tfm'}
|
||||
for key in sunny_npy:
|
||||
assert sunny_npy[key].shape == stock_npy[key].shape == (3, 3)
|
||||
|
||||
|
||||
|
||||
@@ -141,7 +141,7 @@ class ModelCache:
|
||||
class ModelFetcher:
|
||||
"""Handles fetching and caching of model data from remote source"""
|
||||
MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v20.json"
|
||||
MODEL_URL_USBGPU = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_usbgpu_v21.json"
|
||||
MODEL_URL_USBGPU = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_usbgpu_v22.json"
|
||||
|
||||
def __init__(self, params: Params):
|
||||
self.params = params
|
||||
|
||||
@@ -27,7 +27,7 @@ from openpilot.common.swaglog import cloudlog
|
||||
from openpilot.sunnypilot.system.statsd import statlog
|
||||
from openpilot.system.hardware.power_monitoring import PowerMonitoring
|
||||
from openpilot.system.hardware.fan_controller import FanController
|
||||
from openpilot.common.version import terms_version, training_version, get_build_metadata, terms_version_sp
|
||||
from openpilot.common.version import terms_version, training_version, get_build_metadata, terms_version_sp, CHESTNUT_BRANCHES
|
||||
|
||||
|
||||
ThermalStatus = log.DeviceState.ThermalStatus
|
||||
@@ -301,7 +301,11 @@ def hardware_thread(end_event, hw_queue) -> None:
|
||||
|
||||
set_usb_state(msg.deviceState, last_hw_state.usb_state)
|
||||
chestnut.update(started_ts is None, last_hw_state.usb_state)
|
||||
set_offroad_alert_if_changed("Offroad_ChestnutBranch", msg.deviceState.chestnutPresent and not big_model_available)
|
||||
current_channel = get_build_metadata().channel
|
||||
chestnut_target = CHESTNUT_BRANCHES.get(current_channel)
|
||||
chestnut_needs_switch = msg.deviceState.chestnutPresent and not big_model_available and chestnut_target is not None
|
||||
set_offroad_alert_if_changed("Offroad_ChestnutBranch", chestnut_needs_switch,
|
||||
extra_text=chestnut_target if chestnut_needs_switch else None)
|
||||
|
||||
# this subset is only used for offroad
|
||||
temp_sources = [
|
||||
|
||||
@@ -90,6 +90,18 @@ def _rename_pkl_with_chunks(old_pkl: Path, new_pkl: Path) -> Path:
|
||||
return old_pkl.rename(new_pkl)
|
||||
|
||||
|
||||
def _hash_onnx_files(model_dir: Path) -> str | None:
|
||||
onnx_files = sorted(model_dir.glob("*.onnx"))
|
||||
if not onnx_files:
|
||||
return None
|
||||
digest = hashlib.sha256()
|
||||
for f in onnx_files:
|
||||
with f.open('rb') as fh:
|
||||
while block := fh.read(1024 * 1024):
|
||||
digest.update(block)
|
||||
return digest.hexdigest()
|
||||
|
||||
|
||||
def generate_chunked_model(driving_pkl: Path) -> dict:
|
||||
tinygrad_hash = _hash_pkl(driving_pkl)
|
||||
|
||||
@@ -123,7 +135,8 @@ def generate_chunked_model(driving_pkl: Path) -> dict:
|
||||
}
|
||||
|
||||
|
||||
def create_metadata_json(models: list, output_dir: Path, custom_name=None, short_name=None, is_20hz=False, upstream_branch="unknown") -> None:
|
||||
def create_metadata_json(models: list, output_dir: Path, custom_name=None, short_name=None, is_20hz=False, upstream_branch="unknown",
|
||||
onnx_sha256=None) -> None:
|
||||
bundle_json = {
|
||||
"short_name": short_name,
|
||||
"display_name": custom_name or upstream_branch,
|
||||
@@ -139,6 +152,9 @@ def create_metadata_json(models: list, output_dir: Path, custom_name=None, short
|
||||
"models": models,
|
||||
}
|
||||
|
||||
if onnx_sha256:
|
||||
bundle_json["onnx_sha256"] = onnx_sha256
|
||||
|
||||
# Write metadata to output_dir
|
||||
metadata_json = {
|
||||
"bundles": [bundle_json]
|
||||
@@ -178,4 +194,6 @@ if __name__ == "__main__":
|
||||
_driving_pkl = new_pkl
|
||||
|
||||
_model_metadata = generate_chunked_model(_driving_pkl)
|
||||
create_metadata_json([_model_metadata], _output_dir, args.custom_name, _short_name, args.is_20hz, args.upstream_branch)
|
||||
_onnx_sha256 = _hash_onnx_files(Path(args.model_dir))
|
||||
create_metadata_json([_model_metadata], _output_dir, args.custom_name, _short_name, args.is_20hz, args.upstream_branch,
|
||||
onnx_sha256=_onnx_sha256)
|
||||
|
||||
@@ -7,35 +7,66 @@ See the LICENSE.md file in the root directory for more details.
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import hashlib
|
||||
import json
|
||||
import sys
|
||||
import tempfile
|
||||
|
||||
from huggingface_hub import HfApi, hf_hub_download
|
||||
|
||||
|
||||
def hash_file(path: str) -> str:
|
||||
digest = hashlib.sha256()
|
||||
with open(path, 'rb') as f:
|
||||
while block := f.read(1024 * 1024):
|
||||
digest.update(block)
|
||||
return digest.hexdigest()
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("--hf-repo", required=True)
|
||||
parser.add_argument("--hf-defaults-path", required=True)
|
||||
parser.add_argument("--artifact-name", required=True)
|
||||
parser.add_argument("--metadata-path", required=True)
|
||||
parser.add_argument("--onnx-sha256", required=True)
|
||||
parser.add_argument("--model-dir", required=True)
|
||||
parser.add_argument("--onnx-path", required=True)
|
||||
parser.add_argument("--onnx-ref", required=True)
|
||||
parser.add_argument("--model-name", required=True)
|
||||
parser.add_argument("--tinygrad-ref", required=True)
|
||||
parser.add_argument("--run-number", required=True)
|
||||
args = parser.parse_args()
|
||||
|
||||
with open(args.metadata_path) as f:
|
||||
api = HfApi()
|
||||
onnx_sha256 = hash_file(args.onnx_path)
|
||||
short_ref = args.onnx_ref[:8]
|
||||
folder_name = f"model-{args.model_name}-{short_ref}-{args.run_number}"
|
||||
|
||||
print(f"ONNX hash: {onnx_sha256}")
|
||||
print(f"ONNX ref: {args.onnx_ref} (short: {short_ref})")
|
||||
print(f"Folder: {folder_name}")
|
||||
|
||||
metadata_path = f"{args.model_dir}/metadata.json"
|
||||
with open(metadata_path) as f:
|
||||
metadata = json.load(f)
|
||||
|
||||
bundle = metadata['bundles'][0]
|
||||
bundle['onnx_sha256'] = args.onnx_sha256
|
||||
bundle['display_name'] = args.model_name
|
||||
bundle['onnx_sha256'] = onnx_sha256
|
||||
bundle['onnx_ref'] = args.onnx_ref
|
||||
|
||||
artifact = bundle['models'][0]['artifact']
|
||||
hf_base = f"https://huggingface.co/datasets/{args.hf_repo}/resolve/main/{args.hf_defaults_path}/{args.artifact_name}"
|
||||
hf_base = f"https://huggingface.co/datasets/{args.hf_repo}/resolve/main/{args.hf_defaults_path}/{folder_name}"
|
||||
artifact['download_uri']['url'] = f"{hf_base}/{artifact['file_name']}"
|
||||
for chunk in artifact.get('chunks', []):
|
||||
chunk['url'] = f"{hf_base}/{chunk['file_name']}"
|
||||
|
||||
print(f"Uploading model to {args.hf_defaults_path}/{folder_name}/")
|
||||
api.upload_folder(
|
||||
folder_path=args.model_dir,
|
||||
path_in_repo=f"{args.hf_defaults_path}/{folder_name}",
|
||||
repo_id=args.hf_repo,
|
||||
repo_type="dataset",
|
||||
)
|
||||
|
||||
json_filename = f"{args.hf_defaults_path}/default_models.json"
|
||||
try:
|
||||
local_path = hf_hub_download(repo_id=args.hf_repo, repo_type='dataset', filename=json_filename)
|
||||
@@ -47,7 +78,7 @@ def main():
|
||||
defaults_json['tinygrad_ref'] = args.tinygrad_ref
|
||||
|
||||
existing_idx = next((i for i, b in enumerate(defaults_json['bundles'])
|
||||
if b.get('display_name') == bundle.get('display_name')), None)
|
||||
if b.get('onnx_sha256') == onnx_sha256), None)
|
||||
if existing_idx is not None:
|
||||
defaults_json['bundles'][existing_idx] = bundle
|
||||
else:
|
||||
@@ -55,7 +86,6 @@ def main():
|
||||
|
||||
print(json.dumps(defaults_json, indent=2))
|
||||
|
||||
api = HfApi()
|
||||
with tempfile.NamedTemporaryFile(mode='w', suffix='.json', delete=False) as f:
|
||||
json.dump(defaults_json, f, indent=2)
|
||||
tmp_path = f.name
|
||||
|
||||
Reference in New Issue
Block a user