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[aoti-et] Add an ASR runner and an Whisper example to showcase how to use it #15486
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4d18e03
[aoti-et] Add an ASR runner and an Whisper example to showcase how to
larryliu0820 c28431d
Fix cuda.yml
larryliu0820 305381f
Fix cuda.yml
larryliu0820 ea90759
Address comment
larryliu0820 f348cee
Create scripts for export and e2e run
larryliu0820 ca343e7
lint
larryliu0820 779a7ce
Install extra deps
larryliu0820 cf8d6be
Fix artifact name
larryliu0820 2ef76b7
Fix CI
larryliu0820 a20f528
Address comments
larryliu0820 9da10a3
More fixes
larryliu0820 81ac56f
More fixes
larryliu0820 23b7c15
Install ffmpeg and use unsloth tokenizer.json
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| 467660923a5a25e4718e1d6697b93ff1bab4e807 | ||
| 4361747abfc55e40e929396ed986efe775d745f9 |
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| #!/bin/bash | ||
| # Copyright (c) Meta Platforms, Inc. and affiliates. | ||
| # All rights reserved. | ||
| # | ||
| # This source code is licensed under the BSD-style license found in the | ||
| # LICENSE file in the root directory of this source tree. | ||
|
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| # Export model to CUDA format with optional quantization | ||
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| show_help() { | ||
| cat << EOF | ||
| Usage: export_model_cuda_artifact.sh <hf_model> [quant_name] [output_dir] | ||
|
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| Export a HuggingFace model to CUDA format with optional quantization. | ||
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| Arguments: | ||
| hf_model HuggingFace model ID (required) | ||
| Supported models: | ||
| - mistralai/Voxtral-Mini-3B-2507 | ||
| - openai/whisper-small | ||
| - google/gemma-3-4b-it | ||
|
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| quant_name Quantization type (optional, default: non-quantized) | ||
| Options: | ||
| - non-quantized | ||
| - quantized-int4-tile-packed | ||
| - quantized-int4-weight-only | ||
|
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| output_dir Output directory for artifacts (optional, default: current directory) | ||
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| Examples: | ||
| export_model_cuda_artifact.sh "openai/whisper-small" | ||
| export_model_cuda_artifact.sh "mistralai/Voxtral-Mini-3B-2507" "quantized-int4-tile-packed" | ||
| export_model_cuda_artifact.sh "google/gemma-3-4b-it" "non-quantized" "./output" | ||
| EOF | ||
| } | ||
|
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| if [ "${1:-}" = "-h" ] || [ "${1:-}" = "--help" ]; then | ||
| show_help | ||
| exit 0 | ||
| fi | ||
|
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| if [ -z "${1:-}" ]; then | ||
| echo "Error: hf_model argument is required" | ||
| echo "Run with -h or --help for usage information" | ||
| exit 1 | ||
| fi | ||
|
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| set -eux | ||
|
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| HF_MODEL="$1" | ||
| QUANT_NAME="${2:-non-quantized}" | ||
| OUTPUT_DIR="${3:-.}" | ||
|
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| # Determine model configuration based on HF model ID | ||
| case "$HF_MODEL" in | ||
| mistralai/Voxtral-Mini-3B-2507) | ||
| MODEL_NAME="voxtral" | ||
| TASK="multimodal-text-to-text" | ||
| MAX_SEQ_LEN="1024" | ||
| EXTRA_PIP="mistral-common librosa" | ||
| PREPROCESSOR_FEATURE_SIZE="128" | ||
| PREPROCESSOR_OUTPUT="voxtral_preprocessor.pte" | ||
| ;; | ||
| openai/whisper-small) | ||
| MODEL_NAME="whisper" | ||
| TASK="automatic-speech-recognition" | ||
| MAX_SEQ_LEN="" | ||
| EXTRA_PIP="librosa" | ||
| PREPROCESSOR_FEATURE_SIZE="80" | ||
| PREPROCESSOR_OUTPUT="whisper_preprocessor.pte" | ||
| ;; | ||
| google/gemma-3-4b-it) | ||
| MODEL_NAME="gemma3" | ||
| TASK="multimodal-text-to-text" | ||
| MAX_SEQ_LEN="64" | ||
| EXTRA_PIP="" | ||
| PREPROCESSOR_FEATURE_SIZE="" | ||
| PREPROCESSOR_OUTPUT="" | ||
| ;; | ||
| *) | ||
| echo "Error: Unsupported model '$HF_MODEL'" | ||
| echo "Supported models: mistralai/Voxtral-Mini-3B-2507, openai/whisper-small, google/gemma-3-4b-it" | ||
| exit 1 | ||
| ;; | ||
| esac | ||
|
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| # Determine quantization args based on quant name | ||
| case "$QUANT_NAME" in | ||
| non-quantized) | ||
| EXTRA_ARGS="" | ||
| ;; | ||
| 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" | ||
| ;; | ||
| quantized-int4-weight-only) | ||
| EXTRA_ARGS="--qlinear_encoder 4w" | ||
| ;; | ||
| *) | ||
| echo "Error: Unsupported quantization '$QUANT_NAME'" | ||
| echo "Supported quantizations: non-quantized, quantized-int4-tile-packed, quantized-int4-weight-only" | ||
| exit 1 | ||
| ;; | ||
| esac | ||
|
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| echo "::group::Export $MODEL_NAME" | ||
|
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| if [ -n "$EXTRA_PIP" ]; then | ||
| pip install $EXTRA_PIP | ||
| fi | ||
| pip list | ||
|
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| MAX_SEQ_LEN_ARG="" | ||
| if [ -n "$MAX_SEQ_LEN" ]; then | ||
| MAX_SEQ_LEN_ARG="--max_seq_len $MAX_SEQ_LEN" | ||
| fi | ||
| optimum-cli export executorch \ | ||
| --model "$HF_MODEL" \ | ||
| --task "$TASK" \ | ||
| --recipe "cuda" \ | ||
| --dtype bfloat16 \ | ||
| --device cuda \ | ||
| ${MAX_SEQ_LEN_ARG} \ | ||
| ${EXTRA_ARGS} \ | ||
| --output_dir ./ | ||
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| if [ -n "$PREPROCESSOR_OUTPUT" ]; then | ||
| python -m executorch.extension.audio.mel_spectrogram \ | ||
| --feature_size $PREPROCESSOR_FEATURE_SIZE \ | ||
| --stack_output \ | ||
| --max_audio_len 300 \ | ||
| --output_file $PREPROCESSOR_OUTPUT | ||
| fi | ||
|
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| test -f model.pte | ||
| test -f aoti_cuda_blob.ptd | ||
| if [ -n "$PREPROCESSOR_OUTPUT" ]; then | ||
| test -f $PREPROCESSOR_OUTPUT | ||
| fi | ||
| echo "::endgroup::" | ||
|
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| echo "::group::Store $MODEL_NAME Artifacts" | ||
| mkdir -p "${OUTPUT_DIR}" | ||
| cp model.pte "${OUTPUT_DIR}/" | ||
| cp aoti_cuda_blob.ptd "${OUTPUT_DIR}/" | ||
| if [ -n "$PREPROCESSOR_OUTPUT" ]; then | ||
| cp $PREPROCESSOR_OUTPUT "${OUTPUT_DIR}/" | ||
| fi | ||
| ls -al "${OUTPUT_DIR}" | ||
| echo "::endgroup::" | ||
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| #!/bin/bash | ||
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| # Copyright (c) Meta Platforms, Inc. and affiliates. | ||
| # All rights reserved. | ||
| # | ||
| # This source code is licensed under the BSD-style license found in the | ||
| # LICENSE file in the root directory of this source tree. | ||
|
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| # Test CUDA model end-to-end, need to run .ci/scripts/export_model_cuda_artifact.sh first | ||
|
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| show_help() { | ||
| cat << EOF | ||
| Usage: test_model_cuda_e2e.sh <hf_model> <quant_name> [model_dir] | ||
|
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| Build and run end-to-end tests for CUDA models. | ||
|
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| Arguments: | ||
| hf_model HuggingFace model ID (required) | ||
| Supported models: | ||
| - mistralai/Voxtral-Mini-3B-2507 | ||
| - openai/whisper-small | ||
| - google/gemma-3-4b-it | ||
|
|
||
| quant_name Quantization type (required) | ||
| Options: | ||
| - non-quantized | ||
| - quantized-int4-tile-packed | ||
| - quantized-int4-weight-only | ||
|
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| model_dir Directory containing model artifacts (optional, default: current directory) | ||
| Expected files: model.pte, aoti_cuda_blob.ptd | ||
| Tokenizers and test files will be downloaded to this directory | ||
|
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| Examples: | ||
| test_model_cuda_e2e.sh "openai/whisper-small" "non-quantized" | ||
| test_model_cuda_e2e.sh "mistralai/Voxtral-Mini-3B-2507" "quantized-int4-tile-packed" "./model_output" | ||
| EOF | ||
| } | ||
|
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| if [ "${1:-}" = "-h" ] || [ "${1:-}" = "--help" ]; then | ||
| show_help | ||
| exit 0 | ||
| fi | ||
|
|
||
| if [ -z "${1:-}" ]; then | ||
| echo "Error: hf_model argument is required" | ||
| echo "Run with -h or --help for usage information" | ||
| exit 1 | ||
| fi | ||
|
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| if [ -z "${2:-}" ]; then | ||
| echo "Error: quant_name argument is required" | ||
| echo "Run with -h or --help for usage information" | ||
| exit 1 | ||
| fi | ||
|
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| set -eux | ||
|
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| HF_MODEL="$1" | ||
| QUANT_NAME="$2" | ||
| # Download tokenizers, audio, and image files to this directory | ||
| MODEL_DIR="${3:-.}" | ||
|
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| echo "Testing model: $HF_MODEL (quantization: $QUANT_NAME)" | ||
|
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| # Make sure model.pte and aoti_cuda_blob.ptd exist | ||
| if [ ! -f "$MODEL_DIR/model.pte" ]; then | ||
| echo "Error: model.pte not found in $MODEL_DIR" | ||
| exit 1 | ||
| fi | ||
| if [ ! -f "$MODEL_DIR/aoti_cuda_blob.ptd" ]; then | ||
| echo "Error: aoti_cuda_blob.ptd not found in $MODEL_DIR" | ||
| exit 1 | ||
| fi | ||
| # Locate EXECUTORCH_ROOT from the directory of this script | ||
| SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" | ||
| EXECUTORCH_ROOT="$(cd "$SCRIPT_DIR/../.." && pwd)" | ||
|
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| pushd "$EXECUTORCH_ROOT" | ||
|
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| # Determine model configuration based on HF model ID | ||
| case "$HF_MODEL" in | ||
| mistralai/Voxtral-Mini-3B-2507) | ||
| MODEL_NAME="voxtral" | ||
| RUNNER_TARGET="voxtral_runner" | ||
| RUNNER_PATH="voxtral" | ||
| EXPECTED_OUTPUT="poem" | ||
| PREPROCESSOR="voxtral_preprocessor.pte" | ||
| TOKENIZER_URL="https://huggingface.co/mistralai/Voxtral-Mini-3B-2507/resolve/main" # @lint-ignore | ||
| TOKENIZER_FILE="tekken.json" | ||
| AUDIO_URL="https://github.com/voxserv/audio_quality_testing_samples/raw/refs/heads/master/testaudio/16000/test01_20s.wav" | ||
| AUDIO_FILE="poem.wav" | ||
| IMAGE_PATH="" | ||
| ;; | ||
| openai/whisper-small) | ||
| MODEL_NAME="whisper" | ||
| RUNNER_TARGET="whisper_runner" | ||
| RUNNER_PATH="whisper" | ||
| EXPECTED_OUTPUT="Mr. Quilter is the apostle of the middle classes" | ||
| PREPROCESSOR="whisper_preprocessor.pte" | ||
| TOKENIZER_URL="https://huggingface.co/openai/whisper-small/resolve/main" # @lint-ignore | ||
| TOKENIZER_FILE="" | ||
| AUDIO_URL="" | ||
| AUDIO_FILE="output.wav" | ||
| IMAGE_PATH="" | ||
| ;; | ||
| google/gemma-3-4b-it) | ||
| MODEL_NAME="gemma3" | ||
| RUNNER_TARGET="gemma3_e2e_runner" | ||
| RUNNER_PATH="gemma3" | ||
| EXPECTED_OUTPUT="chip" | ||
| PREPROCESSOR="" | ||
| TOKENIZER_URL="https://huggingface.co/google/gemma-3-4b-it/resolve/main" # @lint-ignore | ||
| TOKENIZER_FILE="" | ||
| AUDIO_URL="" | ||
| AUDIO_FILE="" | ||
| IMAGE_PATH="docs/source/_static/img/et-logo.png" | ||
| ;; | ||
| *) | ||
| echo "Error: Unsupported model '$HF_MODEL'" | ||
| echo "Supported models: mistralai/Voxtral-Mini-3B-2507, openai/whisper-small, google/gemma-3-4b-it" | ||
| exit 1 | ||
| ;; | ||
| esac | ||
|
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| echo "::group::Setup ExecuTorch Requirements" | ||
| ./install_requirements.sh | ||
| pip list | ||
| echo "::endgroup::" | ||
|
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| echo "::group::Prepare $MODEL_NAME Artifacts" | ||
|
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|
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| # Download tokenizer files | ||
| if [ "$TOKENIZER_FILE" != "" ]; then | ||
| curl -L $TOKENIZER_URL/$TOKENIZER_FILE -o $MODEL_DIR/$TOKENIZER_FILE | ||
| else | ||
| curl -L $TOKENIZER_URL/tokenizer.json -o $MODEL_DIR/tokenizer.json | ||
| curl -L $TOKENIZER_URL/tokenizer_config.json -o $MODEL_DIR/tokenizer_config.json | ||
| curl -L $TOKENIZER_URL/special_tokens_map.json -o $MODEL_DIR/special_tokens_map.json | ||
| fi | ||
|
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| # Download test files | ||
| if [ "$AUDIO_URL" != "" ]; then | ||
| curl -L $AUDIO_URL -o ${MODEL_DIR}/$AUDIO_FILE | ||
| elif [ "$MODEL_NAME" = "whisper" ]; then | ||
| python -c "from datasets import load_dataset;import soundfile as sf;sample = load_dataset('distil-whisper/librispeech_long', 'clean', split='validation')[0]['audio'];sf.write('${MODEL_DIR}/$AUDIO_FILE', sample['array'][:sample['sampling_rate']*30], sample['sampling_rate'])" | ||
| fi | ||
|
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| ls -al | ||
| echo "::endgroup::" | ||
|
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| echo "::group::Build $MODEL_NAME Runner" | ||
| cmake --preset llm \ | ||
| -DEXECUTORCH_BUILD_CUDA=ON \ | ||
| -DCMAKE_INSTALL_PREFIX=cmake-out \ | ||
| -DCMAKE_BUILD_TYPE=Release \ | ||
| -Bcmake-out -S. | ||
| cmake --build cmake-out -j$(nproc) --target install --config Release | ||
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| cmake -DEXECUTORCH_BUILD_CUDA=ON \ | ||
| -DCMAKE_BUILD_TYPE=Release \ | ||
| -Sexamples/models/$RUNNER_PATH \ | ||
| -Bcmake-out/examples/models/$RUNNER_PATH/ | ||
| cmake --build cmake-out/examples/models/$RUNNER_PATH --target $RUNNER_TARGET --config Release | ||
| echo "::endgroup::" | ||
|
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| echo "::group::Run $MODEL_NAME Runner" | ||
| set +e | ||
| export LD_LIBRARY_PATH=/opt/conda/lib:$LD_LIBRARY_PATH | ||
|
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| # Build runner command with common arguments | ||
| RUNNER_BIN="cmake-out/examples/models/$RUNNER_PATH/$RUNNER_TARGET" | ||
| RUNNER_ARGS="--model_path ${MODEL_DIR}/model.pte --data_path ${MODEL_DIR}/aoti_cuda_blob.ptd --temperature 0" | ||
|
|
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| # Add model-specific arguments | ||
| case "$MODEL_NAME" in | ||
| voxtral) | ||
| RUNNER_ARGS="$RUNNER_ARGS --tokenizer_path ${MODEL_DIR}/$TOKENIZER_FILE --audio_path ${MODEL_DIR}/$AUDIO_FILE --processor_path ${MODEL_DIR}/$PREPROCESSOR" | ||
| ;; | ||
| whisper) | ||
| RUNNER_ARGS="$RUNNER_ARGS --tokenizer_path ${MODEL_DIR}/ --audio_path ${MODEL_DIR}/$AUDIO_FILE --processor_path ${MODEL_DIR}/$PREPROCESSOR" | ||
| ;; | ||
| gemma3) | ||
| RUNNER_ARGS="$RUNNER_ARGS --tokenizer_path ${MODEL_DIR}/ --image_path $IMAGE_PATH" | ||
| ;; | ||
| esac | ||
|
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| OUTPUT=$($RUNNER_BIN $RUNNER_ARGS 2>&1) | ||
| EXIT_CODE=$? | ||
| set -e | ||
|
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| if ! echo "$OUTPUT" | grep -iq "$EXPECTED_OUTPUT"; then | ||
| echo "Expected output '$EXPECTED_OUTPUT' not found in output" | ||
| exit 1 | ||
| elif | ||
| echo "Success: '$EXPECTED_OUTPUT' found in output" | ||
| fi | ||
|
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| if [ $EXIT_CODE -ne 0 ]; then | ||
| echo "Unexpected exit code: $EXIT_CODE" | ||
| exit $EXIT_CODE | ||
| fi | ||
| echo "::endgroup::" | ||
|
|
||
| popd | ||
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