Add scuba logging to edge API's #6395
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name: trunk | |
on: | |
push: | |
branches: | |
- main | |
- release/* | |
tags: | |
- ciflow/trunk/* | |
pull_request: | |
paths: | |
- .ci/docker/ci_commit_pins/pytorch.txt | |
- .ci/scripts/** | |
workflow_dispatch: | |
concurrency: | |
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }} | |
cancel-in-progress: true | |
jobs: | |
gather-models: | |
runs-on: ubuntu-22.04 | |
outputs: | |
models: ${{ steps.gather-models.outputs.models }} | |
steps: | |
- uses: actions/checkout@v3 | |
with: | |
submodules: 'false' | |
- uses: actions/setup-python@v4 | |
with: | |
python-version: '3.10' | |
- name: Extract the list of models to test | |
id: gather-models | |
run: | | |
set -eux | |
PYTHONPATH="${PWD}" python .ci/scripts/gather_test_models.py --target-os macos --event "${GITHUB_EVENT_NAME}" | |
test-models-macos: | |
name: test-models-macos | |
uses: pytorch/test-infra/.github/workflows/macos_job.yml@main | |
needs: gather-models | |
strategy: | |
matrix: ${{ fromJSON(needs.gather-models.outputs.models) }} | |
fail-fast: false | |
with: | |
runner: ${{ matrix.runner }} | |
python-version: '3.11' | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
timeout: ${{ matrix.timeout }} | |
script: | | |
MODEL_NAME=${{ matrix.model }} | |
BUILD_TOOL=${{ matrix.build-tool }} | |
BACKEND=${{ matrix.backend }} | |
DEMO_BACKEND_DELEGATION=${{ matrix.demo_backend_delegation }} | |
bash .ci/scripts/setup-conda.sh | |
# Setup MacOS dependencies as there is no Docker support on MacOS atm | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}" | |
# Build and test executorch | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/test_model.sh "${MODEL_NAME}" "${BUILD_TOOL}" "${BACKEND}" "${DEMO_BACKEND_DELEGATION}" | |
test-custom-ops-macos: | |
name: test-custom-ops-macos | |
uses: pytorch/test-infra/.github/workflows/macos_job.yml@main | |
strategy: | |
matrix: | |
include: | |
- build-tool: cmake | |
fail-fast: false | |
with: | |
runner: macos-m1-stable | |
python-version: '3.11' | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
script: | | |
BUILD_TOOL=${{ matrix.build-tool }} | |
bash .ci/scripts/setup-conda.sh | |
# Setup MacOS dependencies as there is no Docker support on MacOS atm | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}" | |
# Build and test custom ops | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash examples/portable/custom_ops/test_custom_ops.sh "${BUILD_TOOL}" | |
test-selective-build-macos: | |
name: test-selective-build-macos | |
uses: pytorch/test-infra/.github/workflows/macos_job.yml@main | |
strategy: | |
matrix: | |
include: | |
- build-tool: cmake | |
fail-fast: false | |
with: | |
runner: macos-m1-stable | |
python-version: '3.11' | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
script: | | |
BUILD_TOOL=${{ matrix.build-tool }} | |
bash .ci/scripts/setup-conda.sh | |
# Setup MacOS dependencies as there is no Docker support on MacOS atm | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}" | |
# Build and test selective build | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash examples/selective_build/test_selective_build.sh "${BUILD_TOOL}" | |
test-demo-backend-delegation: | |
name: test-demo-backend-delegation | |
uses: pytorch/test-infra/.github/workflows/linux_job.yml@main | |
strategy: | |
matrix: | |
include: | |
- build-tool: buck2 | |
- build-tool: cmake | |
fail-fast: false | |
with: | |
runner: linux.2xlarge | |
docker-image: executorch-ubuntu-22.04-clang12 | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
script: | | |
# The generic Linux job chooses to use base env, not the one setup by the image | |
CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]") | |
conda activate "${CONDA_ENV}" | |
BUILD_TOOL=${{ matrix.build-tool }} | |
PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "${BUILD_TOOL}" | |
# Test selective build | |
PYTHON_EXECUTABLE=python bash examples/portable/scripts/test_demo_backend_delegation.sh "${BUILD_TOOL}" | |
test-arm-backend-delegation: | |
name: test-arm-backend-delegation | |
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main | |
with: | |
runner: linux.2xlarge | |
docker-image: executorch-ubuntu-22.04-arm-sdk | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
timeout: 90 | |
script: | | |
# The generic Linux job chooses to use base env, not the one setup by the image | |
CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]") | |
conda activate "${CONDA_ENV}" | |
source .ci/scripts/utils.sh | |
install_executorch | |
install_arm | |
# Increase number of files user can monitor to bypass buck failures. | |
# Hopefully this is high enough for this setup. | |
sudo sysctl fs.inotify.max_user_watches=1048576 # 1024 * 1024 | |
# Test ethos-u delegate examples with run.sh | |
PYTHON_EXECUTABLE=python bash examples/arm/run.sh examples/arm/ethos-u-scratch/ | |
test-arm-reference-delegation: | |
name: test-arm-reference-delegation | |
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main | |
with: | |
runner: linux.2xlarge | |
docker-image: executorch-ubuntu-22.04-arm-sdk | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
timeout: 90 | |
script: | | |
# The generic Linux job chooses to use base env, not the one setup by the image | |
CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]") | |
conda activate "${CONDA_ENV}" | |
source .ci/scripts/utils.sh | |
install_executorch | |
install_arm | |
# Run arm unit tests | |
pytest -c /dev/null -v -n auto --cov=./ --cov-report=xml backends/arm/test | |
test-coreml-delegate: | |
name: test-coreml-delegate | |
uses: pytorch/test-infra/.github/workflows/macos_job.yml@main | |
with: | |
runner: macos-13-xlarge | |
python-version: '3.11' | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
timeout: 90 | |
script: | | |
BUILD_TOOL=cmake | |
bash .ci/scripts/setup-conda.sh | |
# Setup MacOS dependencies as there is no Docker support on MacOS atm | |
GITHUB_RUNNER=1 PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}" | |
# Build and test coreml delegate | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash backends/apple/coreml/scripts/build_all.sh | |
test-pybind-build-macos: | |
name: test-pybind-build-macos | |
uses: pytorch/test-infra/.github/workflows/macos_job.yml@main | |
strategy: | |
matrix: | |
include: | |
- build-tool: cmake | |
fail-fast: false | |
with: | |
runner: macos-m1-stable | |
python-version: '3.11' | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
timeout: 180 | |
script: | | |
bash .ci/scripts/setup-conda.sh | |
# build module for executorch.extension.pybindings.portable_lib | |
BUILD_TOOL=${{ matrix.build-tool }} | |
EXECUTORCH_BUILD_PYBIND=ON PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}" | |
# see if we can import the module successfully | |
${CONDA_RUN} python -c "from executorch.extension.pybindings import portable_lib; print('success!')" | |
test-llama-runner-macos: | |
name: test-llama-runner-mac | |
uses: pytorch/test-infra/.github/workflows/macos_job.yml@main | |
strategy: | |
matrix: | |
dtype: [fp32] | |
mode: [portable, xnnpack+kv+custom, mps, coreml] | |
include: | |
- dtype: bf16 | |
mode: portable | |
- dtype: bf16 | |
mode: custom | |
fail-fast: false | |
with: | |
runner: macos-m1-stable | |
python-version: '3.11' | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
timeout: 900 | |
script: | | |
DTYPE=${{ matrix.dtype }} | |
MODE=${{ matrix.mode }} | |
bash .ci/scripts/setup-conda.sh | |
# Setup executorch | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh cmake | |
if [[ "${MODE}" == "mps" ]]; then | |
# Install mps delegate | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash backends/apple/mps/install_requirements.sh | |
echo "Finishing installing mps." | |
elif [[ "${MODE}" == "coreml" ]]; then | |
# Install coreml delegate | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash backends/apple/coreml/scripts/install_requirements.sh | |
echo "Finishing installing coreml." | |
fi | |
# Install requirements for export_llama | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash examples/models/llama/install_requirements.sh | |
# Test llama2 | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/test_llama.sh -model stories110M -build_tool cmake -dtype "${DTYPE}" -mode "${MODE}" | |
# # TODO(jackzhxng): Runner consistently runs out of memory before test finishes. Try to find a more powerful runner. | |
# test-llava-runner-macos: | |
# name: test-llava-runner-macos | |
# uses: pytorch/test-infra/.github/workflows/macos_job.yml@main | |
# strategy: | |
# fail-fast: false | |
# with: | |
# runner: macos-14-xlarge | |
# python-version: '3.11' | |
# submodules: 'true' | |
# ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
# timeout: 900 | |
# script: | | |
# BUILD_TOOL=cmake | |
# bash .ci/scripts/setup-conda.sh | |
# # Setup MacOS dependencies as there is no Docker support on MacOS atm | |
# GITHUB_RUNNER=1 PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}" | |
# # install Llava requirements | |
# ${CONDA_RUN} bash examples/models/llama/install_requirements.sh | |
# ${CONDA_RUN} bash examples/models/llava/install_requirements.sh | |
# # run python unittest | |
# ${CONDA_RUN} python -m unittest examples.models.llava.test.test_llava | |
# # run e2e (export, tokenizer and runner) | |
# PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/test_llava.sh | |
test-qnn-model: | |
name: test-qnn-model | |
uses: pytorch/test-infra/.github/workflows/linux_job.yml@main | |
strategy: | |
matrix: | |
dtype: [fp32] | |
model: [dl3, mv3, mv2, ic4, ic3, vit] | |
fail-fast: false | |
with: | |
runner: linux.2xlarge | |
docker-image: executorch-ubuntu-22.04-qnn-sdk | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
timeout: 900 | |
script: | | |
# The generic Linux job chooses to use base env, not the one setup by the image | |
CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]") | |
conda activate "${CONDA_ENV}" | |
PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh cmake | |
PYTHON_EXECUTABLE=python bash .ci/scripts/setup-qnn-deps.sh | |
PYTHON_EXECUTABLE=python bash .ci/scripts/build-qnn-sdk.sh | |
PYTHON_EXECUTABLE=python bash .ci/scripts/test_model.sh ${{ matrix.model }} "cmake" "qnn" | |
test-apple-model: | |
name: test-apple-model | |
uses: pytorch/test-infra/.github/workflows/macos_job.yml@main | |
strategy: | |
fail-fast: false | |
with: | |
runner: macos-m1-stable | |
python-version: '3.11' | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
timeout: 90 | |
script: | | |
BUILD_TOOL=cmake | |
bash .ci/scripts/setup-conda.sh | |
# Setup MacOS dependencies as there is no Docker support on MacOS atm | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}" | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash backends/apple/coreml/scripts/install_requirements.sh | |
echo "Finishing installing coreml." | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash backends/apple/mps/install_requirements.sh | |
echo "Finishing installing mps." | |
# Build and test coreml model | |
MODELS=(mv3 ic4 resnet50 edsr mobilebert w2l) | |
for MODEL_NAME in "${MODELS[@]}"; do | |
echo "::group::Exporting coreml model: $MODEL_NAME" | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/test_model.sh "${MODEL_NAME}" "${BUILD_TOOL}" "coreml" | |
echo "::endgroup::" | |
echo "::group::Exporting mps model: $MODEL_NAME" | |
PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/test_model.sh "${MODEL_NAME}" "${BUILD_TOOL}" "mps" | |
echo "::endgroup::" | |
done | |
test-huggingface-transformers: | |
# NB: Don't run this on fork PRs because they won't have access to the secret and would fail anyway | |
if: ${{ !github.event.pull_request.head.repo.fork }} | |
name: test-huggingface-transformers | |
uses: pytorch/test-infra/.github/workflows/linux_job.yml@main | |
secrets: inherit | |
strategy: | |
matrix: | |
hf_model_repo: [google/gemma-2b] | |
fail-fast: false | |
with: | |
secrets-env: EXECUTORCH_HF_TOKEN | |
runner: linux.12xlarge | |
docker-image: executorch-ubuntu-22.04-clang12 | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
timeout: 90 | |
script: | | |
echo "::group::Set up ExecuTorch" | |
# The generic Linux job chooses to use base env, not the one setup by the image | |
CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]") | |
conda activate "${CONDA_ENV}" | |
PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh cmake | |
echo "Installing libexecutorch.a, libextension_module.so, libportable_ops_lib.a" | |
rm -rf cmake-out | |
cmake \ | |
-DCMAKE_INSTALL_PREFIX=cmake-out \ | |
-DCMAKE_BUILD_TYPE=Release \ | |
-DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON \ | |
-DEXECUTORCH_BUILD_EXTENSION_MODULE=ON \ | |
-DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \ | |
-DEXECUTORCH_BUILD_KERNELS_CUSTOM=ON \ | |
-DEXECUTORCH_BUILD_KERNELS_OPTIMIZED=ON \ | |
-DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON \ | |
-DEXECUTORCH_BUILD_XNNPACK=ON \ | |
-DPYTHON_EXECUTABLE=python \ | |
-Bcmake-out . | |
cmake --build cmake-out -j9 --target install --config Release | |
echo "Build llama runner" | |
dir="examples/models/llama" | |
cmake \ | |
-DCMAKE_INSTALL_PREFIX=cmake-out \ | |
-DCMAKE_BUILD_TYPE=Release \ | |
-DEXECUTORCH_BUILD_KERNELS_CUSTOM=ON \ | |
-DEXECUTORCH_BUILD_KERNELS_OPTIMIZED=ON \ | |
-DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON \ | |
-DEXECUTORCH_BUILD_XNNPACK=ON \ | |
-DPYTHON_EXECUTABLE=python \ | |
-Bcmake-out/${dir} \ | |
${dir} | |
cmake --build cmake-out/${dir} -j9 --config Release | |
echo "::endgroup::" | |
echo "::group::Set up HuggingFace Dependencies" | |
if [ -z "$SECRET_EXECUTORCH_HF_TOKEN" ]; then | |
echo "::error::SECRET_EXECUTORCH_HF_TOKEN is empty. For security reason secrets won't be accessible on forked PRs. Please make sure you submit a non-forked PR." | |
exit 1 | |
fi | |
pip install -U "huggingface_hub[cli]" | |
huggingface-cli login --token $SECRET_EXECUTORCH_HF_TOKEN | |
pip install accelerate sentencepiece | |
pip list | |
echo "::endgroup::" | |
echo "::group::Export to ExecuTorch" | |
TOKENIZER_FILE=tokenizer.model | |
TOKENIZER_BIN_FILE=tokenizer.bin | |
ET_MODEL_NAME=et_model | |
# Fetch the file using a Python one-liner | |
DOWNLOADED_TOKENIZER_FILE_PATH=$(python -c " | |
from huggingface_hub import hf_hub_download | |
# Download the file from the Hugging Face Hub | |
downloaded_path = hf_hub_download( | |
repo_id='${{ matrix.hf_model_repo }}', | |
filename='${TOKENIZER_FILE}' | |
) | |
print(downloaded_path) | |
") | |
if [ -f "$DOWNLOADED_TOKENIZER_FILE_PATH" ]; then | |
echo "${TOKENIZER_FILE} downloaded successfully at: $DOWNLOADED_TOKENIZER_FILE_PATH" | |
python -m extension.llm.tokenizer.tokenizer -t $DOWNLOADED_TOKENIZER_FILE_PATH -o ./${TOKENIZER_BIN_FILE} | |
ls ./tokenizer.bin | |
else | |
echo "Failed to download ${TOKENIZER_FILE} from ${{ matrix.hf_model_repo }}." | |
exit 1 | |
fi | |
python -m extension.export_util.export_hf_model -hfm=${{ matrix.hf_model_repo }} -o ${ET_MODEL_NAME} | |
cmake-out/examples/models/llama/llama_main --model_path=${ET_MODEL_NAME}.pte --tokenizer_path=${TOKENIZER_BIN_FILE} --prompt="My name is" | |
echo "::endgroup::" | |
test-llama-runner-qnn-linux: | |
name: test-llama-runner-qnn-linux | |
uses: pytorch/test-infra/.github/workflows/linux_job.yml@main | |
strategy: | |
matrix: | |
dtype: [fp32] | |
pt2e_quantize: [qnn_16a16w, qnn_8a8w] | |
mode: [qnn] | |
fail-fast: false | |
with: | |
runner: linux.2xlarge | |
docker-image: executorch-ubuntu-22.04-qnn-sdk | |
submodules: 'true' | |
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }} | |
timeout: 900 | |
script: | | |
# The generic Linux job chooses to use base env, not the one setup by the image | |
CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]") | |
conda activate "${CONDA_ENV}" | |
BUILD_TOOL="cmake" | |
DTYPE=${{ matrix.dtype }} | |
MODE=${{ matrix.mode }} | |
PT2E_QUANTIZE=${{ matrix.pt2e_quantize }} | |
PYTHON_EXECUTABLE=python bash .ci/scripts/setup-qnn-deps.sh | |
PYTHON_EXECUTABLE=python bash .ci/scripts/build-qnn-sdk.sh | |
# Setup executorch | |
PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "${BUILD_TOOL}" | |
# Install requirements for export_llama | |
PYTHON_EXECUTABLE=python bash examples/models/llama/install_requirements.sh | |
# Test llama2 | |
PYTHON_EXECUTABLE=python bash .ci/scripts/test_llama.sh -model stories110M -build_tool "${BUILD_TOOL}" -mode "${MODE}" -dtype "${DTYPE}" -pt2e_quantize "${PT2E_QUANTIZE}" |