Add int4mm test to the CUDA CI flow

.github/workflows/cuda.yml

@@ -275,6 +275,154 @@ jobs:
           exit 1
         fi
 
+        if [ $EXIT_CODE -ne 0 ]; then
+          echo "Unexpected exit code: $EXIT_CODE"
+          exit $EXIT_CODE
+        fi
+          echo "::endgroup::"
+
+  export-voxtral-cuda-quantized:
+    name: export-voxtral-cuda-quantized
+    uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
+    permissions:
+      id-token: write
+      contents: read
+    secrets: inherit
+    strategy:
+      fail-fast: false
+    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: voxtral-cuda-quantized-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@${OPTIMUM_ET_VERSION}
+        pip install mistral-common librosa
+        pip list
+        echo "::endgroup::"
+
+        echo "::group::Export Voxtral with Quantization"
+        optimum-cli export executorch \
+            --model "mistralai/Voxtral-Mini-3B-2507" \
+            --task "multimodal-text-to-text" \
+            --recipe "cuda" \
+            --dtype bfloat16 \
+            --device cuda \
+            --max_seq_len 1024 \
+            --qlinear 4w \
+            --qlinear_encoder 4w \
+            --qlinear_packing_format tile_packed_to_4d \
+            --qlinear_encoder_packing_format tile_packed_to_4d \
+            --output_dir ./
+        python -m executorch.extension.audio.mel_spectrogram \
+            --feature_size 128 \
+            --stack_output \
+            --max_audio_len 300 \
+            --output_file voxtral_preprocessor.pte
+
+        test -f model.pte
+        test -f aoti_cuda_blob.ptd
+        test -f voxtral_preprocessor.pte
+        echo "::endgroup::"
+
+        echo "::group::Store Voxtral Quantized Artifacts"
+        mkdir -p "${RUNNER_ARTIFACT_DIR}"
+        cp model.pte "${RUNNER_ARTIFACT_DIR}/"
+        cp aoti_cuda_blob.ptd "${RUNNER_ARTIFACT_DIR}/"
+        cp voxtral_preprocessor.pte "${RUNNER_ARTIFACT_DIR}/"
+        ls -al "${RUNNER_ARTIFACT_DIR}"
+        echo "::endgroup::"
+
+  test-voxtral-cuda-quantized-e2e:
+    name: test-voxtral-cuda-quantized-e2e
+    needs: export-voxtral-cuda-quantized
+    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: voxtral-cuda-quantized-export
+      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
+      script: |
+        set -eux
+
+        echo "::group::Setup ExecuTorch Requirements"
+        CMAKE_ARGS="-DEXECUTORCH_BUILD_CUDA=ON" ./install_requirements.sh
+        pip list
+        echo "::endgroup::"
+
+        echo "::group::Prepare Voxtral Quantized Artifacts"
+        cp "${RUNNER_ARTIFACT_DIR}/model.pte" .
+        cp "${RUNNER_ARTIFACT_DIR}/aoti_cuda_blob.ptd" .
+        cp "${RUNNER_ARTIFACT_DIR}/voxtral_preprocessor.pte" .
+        TOKENIZER_URL="https://huggingface.co/mistralai/Voxtral-Mini-3B-2507/resolve/main/tekken.json"
+        curl -L $TOKENIZER_URL -o tekken.json
+        ls -al model.pte aoti_cuda_blob.ptd voxtral_preprocessor.pte tekken.json
+        echo "::endgroup::"
+
+        echo "::group::Download Test Audio File"
+        AUDIO_URL="https://github.com/voxserv/audio_quality_testing_samples/raw/refs/heads/master/testaudio/16000/test01_20s.wav"
+        curl -L $AUDIO_URL -o poem.wav
+        echo "::endgroup::"
+
+        echo "::group::Build Voxtral Runner"
+        cmake --preset llm \
+              -DEXECUTORCH_BUILD_CUDA=ON \
+              -DCMAKE_INSTALL_PREFIX=cmake-out \
+              -DCMAKE_BUILD_TYPE=Release \
+              -Bcmake-out -S.
+        cmake --build cmake-out -j$(( $(nproc) - 1 )) --target install --config Release
+
+        cmake -DEXECUTORCH_BUILD_CUDA=ON \
+              -DCMAKE_BUILD_TYPE=Release \
+              -Sexamples/models/voxtral \
+              -Bcmake-out/examples/models/voxtral/
+        cmake --build cmake-out/examples/models/voxtral --target voxtral_runner --config Release
+        echo "::endgroup::"
+
+        echo "::group::Run Voxtral Runner with Quantized Model"
+        set +e
+        export LD_LIBRARY_PATH=/opt/conda/lib:$LD_LIBRARY_PATH
+        OUTPUT=$(cmake-out/examples/models/voxtral/voxtral_runner \
+              --model_path model.pte \
+              --data_path aoti_cuda_blob.ptd \
+              --tokenizer_path tekken.json \
+              --audio_path poem.wav \
+              --processor_path voxtral_preprocessor.pte \
+              --temperature 0 2>&1)
+        EXIT_CODE=$?
+        set -e
+
+        echo "$OUTPUT"
+
+        if ! echo "$OUTPUT" | grep -iq "poem"; then
+          echo "Expected output 'poem' not found in output"
+          exit 1
+        fi
+
         if [ $EXIT_CODE -ne 0 ]; then
           echo "Unexpected exit code: $EXIT_CODE"
           exit $EXIT_CODE