trunk

[ET-VK] Replace Uniform buffers with push constants for copy op #319

Workflow file for this run

	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, xnnpack+custom+quantize_kv]
	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-2-2b]
	fail-fast: false
	with:
	secrets-env: EXECUTORCH_HF_TOKEN
	runner: linux.2xlarge.memory
	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
	DOWNLOADED_TOKENIZER_FILE_PATH=$(bash .ci/scripts/download_hf_hub.sh --model_id "${{ matrix.hf_model_repo }}" --files "${TOKENIZER_FILE}")
	if [ -f "$DOWNLOADED_TOKENIZER_FILE_PATH/$TOKENIZER_FILE" ]; then
	echo "${TOKENIZER_FILE} downloaded successfully at: $DOWNLOADED_TOKENIZER_FILE_PATH"
	python -m extension.llm.tokenizer.tokenizer -t "$DOWNLOADED_TOKENIZER_FILE_PATH/$TOKENIZER_FILE" -o ./${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}"

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[ET-VK] Replace Uniform buffers with push constants for copy op #319

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[ET-VK] Replace Uniform buffers with push constants for copy op #319

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Workflow file for this run