Merge branch 'main' into op-floor-div

Author: Sebastian-Larsson

.ci/docker/ci_commit_pins/optimum-executorch.txt

@@ -1 +1 @@
-e8f76b4295584c4328e7fd7971c131cb341c7438
+467660923a5a25e4718e1d6697b93ff1bab4e807

.github/workflows/cuda.yml

@@ -164,6 +164,75 @@ jobs:
         ls -al "${RUNNER_ARTIFACT_DIR}"
         echo "::endgroup::"
 
+  export-gemma3-cuda-artifact:
+    name: export-gemma3-cuda-${{ matrix.quant.name }}
+    uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
+    permissions:
+      id-token: write
+      contents: read
+    secrets: inherit
+    strategy:
+      fail-fast: false
+      matrix:
+        quant:
+          - name: "non-quantized"
+            artifact: "voxtral-cuda-export"
+            extra_args: ""
+          # TODO: enable gemma3 quantization
+          # - name: "quantized-int4-tile-packed"
+          #   artifact: "voxtral-cuda-quantized-int4-tile-packed"
+          #   extra_args: "--qlinear 4w --qlinear_encoder 4w --qlinear_packing_format tile_packed_to_4d --qlinear_encoder_packing_format tile_packed_to_4d"
+          # - name: "quantized-int4-weight-only"
+          #   artifact: "voxtral-cuda-quantized-int4-weight-only"
+          #   # TODO: adding "--qlinear 4w" produces invalid results. Need further investigation.
+          #   extra_args: "--qlinear_encoder 4w"
+    with:
+      timeout: 90
+      secrets-env: EXECUTORCH_HF_TOKEN
+      runner: linux.g5.4xlarge.nvidia.gpu
+      gpu-arch-type: cuda
+      gpu-arch-version: 12.6
+      use-custom-docker-registry: false
+      submodules: recursive
+      upload-artifact: gemma3-cuda-export
+      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
+      script: |
+        set -eux
+
+        echo "::group::Setup ExecuTorch"
+        ./install_executorch.sh
+        echo "::endgroup::"
+
+        echo "::group::Setup Huggingface"
+        pip install -U "huggingface_hub[cli]" accelerate
+        huggingface-cli login --token $SECRET_EXECUTORCH_HF_TOKEN
+        OPTIMUM_ET_VERSION=$(cat .ci/docker/ci_commit_pins/optimum-executorch.txt)
+        pip install git+https://github.com/huggingface/optimum-executorch.git@${OPTIMUM_ET_VERSION}
+        pip list
+        echo "::endgroup::"
+
+        echo "::group::Export Gemma3 (${{ matrix.quant.name }})"
+        EXTRA_ARGS="${{ matrix.quant.extra_args }}"
+        optimum-cli export executorch \
+            --model "google/gemma-3-4b-it" \
+            --task "multimodal-text-to-text" \
+            --recipe "cuda" \
+            --dtype bfloat16 \
+            --device cuda \
+            --max_seq_len 64 \
+            --output_dir ./
+
+        test -f model.pte
+        test -f aoti_cuda_blob.ptd
+        echo "::endgroup::"
+
+        echo "::group::Store Gemma3 Artifacts (${{ matrix.quant.name }})"
+        mkdir -p "${RUNNER_ARTIFACT_DIR}/"
+        cp model.pte "${RUNNER_ARTIFACT_DIR}/"
+        cp aoti_cuda_blob.ptd "${RUNNER_ARTIFACT_DIR}/"
+        ls -al "${RUNNER_ARTIFACT_DIR}/"
+        echo "::endgroup::"
+
   benchmark-voxtral-cuda:
     name: benchmark-voxtral-cuda
     needs: export-voxtral-cuda-artifact
@@ -204,13 +273,63 @@ jobs:
               -DEXECUTORCH_BUILD_EXTENSION_NAMED_DATA_MAP=ON \
               -DEXECUTORCH_BUILD_TESTS=ON \
               -Bcmake-out .
-        cmake --build cmake-out -j$(( $(nproc) - 1 )) --target voxtral_runner
+        cmake --build cmake-out -j$(( $(nproc) - 1 )) --target multimodal_benchmark
         echo "::endgroup::"
 
         echo "::group::Run Voxtral Benchmark"
 
         export LD_LIBRARY_PATH=/opt/conda/lib:$LD_LIBRARY_PATH
-        cmake-out/backends/cuda/voxtral_runner model.pte aoti_cuda_blob.ptd
+        cmake-out/backends/cuda/multimodal_benchmark voxtral model.pte aoti_cuda_blob.ptd
+
+        echo "::endgroup::"
+
+  benchmark-gemma3-cuda:
+    name: benchmark-gemma3-cuda
+    needs: export-gemma3-cuda-artifact
+    uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
+    permissions:
+      id-token: write
+      contents: read
+    strategy:
+      fail-fast: false
+    with:
+      timeout: 90
+      runner: linux.g5.4xlarge.nvidia.gpu
+      gpu-arch-type: cuda
+      gpu-arch-version: 12.6
+      use-custom-docker-registry: false
+      submodules: recursive
+      download-artifact: gemma3-cuda-export
+      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
+      script: |
+        set -eux
+
+        echo "::group::Setup ExecuTorch Requirements"
+        CMAKE_ARGS="-DEXECUTORCH_BUILD_CUDA=ON" ./install_requirements.sh
+        pip list
+        echo "::endgroup::"
+
+        echo "::group::Prepare Gemma3 Artifacts"
+        cp "${RUNNER_ARTIFACT_DIR}/model.pte" .
+        cp "${RUNNER_ARTIFACT_DIR}/aoti_cuda_blob.ptd" .
+        ls -al model.pte aoti_cuda_blob.ptd
+        echo "::endgroup::"
+
+        echo "::group::Build Gemma3 Benchmark"
+        cmake -DCMAKE_BUILD_TYPE=Release \
+              -DEXECUTORCH_BUILD_CUDA=ON \
+              -DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \
+              -DEXECUTORCH_BUILD_EXTENSION_MODULE=ON \
+              -DEXECUTORCH_BUILD_EXTENSION_NAMED_DATA_MAP=ON \
+              -DEXECUTORCH_BUILD_TESTS=ON \
+              -Bcmake-out .
+        cmake --build cmake-out -j$(( $(nproc) - 1 )) --target multimodal_benchmark
+        echo "::endgroup::"
+
+        echo "::group::Run Gemma3 Benchmark"
+
+        export LD_LIBRARY_PATH=/opt/conda/lib:$LD_LIBRARY_PATH
+        cmake-out/backends/cuda/multimodal_benchmark gemma3 model.pte aoti_cuda_blob.ptd
 
         echo "::endgroup::"
 
@@ -302,3 +421,87 @@ jobs:
           exit $EXIT_CODE
         fi
         echo "::endgroup::"
+
+  test-gemma3-cuda-e2e:
+    name: test-gemma3-cuda-e2e-${{ matrix.format.name }}
+    needs: export-gemma3-cuda-artifact
+    uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
+    permissions:
+      id-token: write
+      contents: read
+    strategy:
+      fail-fast: false
+      matrix:
+        format:
+          - name: "non-quantized"
+            artifact: "gemma3-cuda-export"
+          # TODO: enable quantized gemma3.
+          # - name: "quantized-int4-tile-packed"
+          #   artifact: "gemma3-cuda-quantized-int4-tile-packed"
+          # - name: "quantized-int4-weight-only"
+          #   artifact: "gemma3-cuda-quantized-int4-weight-only"
+    with:
+      timeout: 90
+      runner: linux.g5.4xlarge.nvidia.gpu
+      gpu-arch-type: cuda
+      gpu-arch-version: 12.6
+      use-custom-docker-registry: false
+      submodules: recursive
+      download-artifact: ${{ matrix.format.artifact }}
+      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
+      script: |
+        set -eux
+
+        echo "::group::Setup ExecuTorch Requirements"
+        ./install_requirements.sh
+        pip list
+        echo "::endgroup::"
+
+        echo "::group::Prepare Gemma3 Artifacts (${{ matrix.format.name }})"
+        cp "${RUNNER_ARTIFACT_DIR}/model.pte" .
+        cp "${RUNNER_ARTIFACT_DIR}/aoti_cuda_blob.ptd" .
+        TOKENIZER_URL="https://huggingface.co/unsloth/gemma-3-1b-it/resolve/main/tokenizer.json"
+        curl -L $TOKENIZER_URL -o tokenizer.json
+        ls -al model.pte aoti_cuda_blob.ptd tokenizer.json
+        IMAGE_PATH="docs/source/_static/img/et-logo.png"
+        echo "::endgroup::"
+
+        echo "::group::Build Gemma3 Runner"
+        cmake --preset llm \
+              -DEXECUTORCH_BUILD_CUDA=ON \
+              -DCMAKE_INSTALL_PREFIX=cmake-out \
+              -DCMAKE_BUILD_TYPE=Release \
+              -Bcmake-out -S.
+        cmake --build cmake-out -j$(( $(nproc) - 1 )) --target install --config Release
+
+        cmake -DEXECUTORCH_BUILD_CUDA=ON \
+              -DCMAKE_BUILD_TYPE=Release \
+              -Sexamples/models/gemma3 \
+              -Bcmake-out/examples/models/gemma3/
+        cmake --build cmake-out/examples/models/gemma3 --target gemma3_e2e_runner --config Release
+        echo "::endgroup::"
+
+        echo "::group::Run Gemma3 Runner (${{ matrix.format.name }})"
+        set +e
+        export LD_LIBRARY_PATH=/opt/conda/lib:$LD_LIBRARY_PATH
+        OUTPUT=$(cmake-out/examples/models/gemma3/gemma3_e2e_runner \
+              --model_path model.pte \
+              --data_path aoti_cuda_blob.ptd \
+              --tokenizer_path tokenizer.json \
+              --image_path $IMAGE_PATH \
+              --temperature 0 2>&1)
+        EXIT_CODE=$?
+        set -e
+
+        echo "$OUTPUT"
+
+        if ! echo "$OUTPUT" | grep -iq "chip"; then
+          echo "Expected output 'chip' not found in output"
+          exit 1
+        fi
+
+        if [ $EXIT_CODE -ne 0 ]; then
+          echo "Unexpected exit code: $EXIT_CODE"
+          exit $EXIT_CODE
+        fi
+        echo "::endgroup::"