torch-mlir/.github/workflows/buildAndTest.yml

177 lines
7.2 KiB
YAML

name: Build and Test
on:
pull_request:
branches: [ main ]
push:
branches: [ main ]
workflow_dispatch:
# Provisioned Jobs:
# ubuntu - x86_64 - llvm in-tree - pytorch binary - build+test # most used dev flow and fastest signal
# ubuntu - x86_64 - llvm out-of-tree - pytorch source - build+test # most elaborate build
# macos - arm64 - llvm in-tree - pytorch binary - build only # cross compile, can't test arm64
jobs:
build-test:
strategy:
fail-fast: true
matrix:
os-arch: [ubuntu-x86_64, macos-arm64]
llvm-build: [in-tree, out-of-tree]
torch-binary: [ON, OFF]
exclude:
# Exclude llvm in-tree and pytorch source
- llvm-build: in-tree
torch-binary: OFF
# Exclude llvm out-of-tree and pytorch binary
- llvm-build: out-of-tree
torch-binary: ON
# Exclude macos-arm64 and llvm out-of-tree altogether
- os-arch: macos-arm64
llvm-build: out-of-tree
include:
# Specify OS versions
- os-arch: ubuntu-x86_64
os: ubuntu-22.04
- os-arch: macos-arm64
os: macos-12
runs-on: ${{ matrix.os }}
steps:
- name: Checkout torch-mlir
uses: actions/checkout@v2
with:
submodules: 'true'
- name: Setup ccache
uses: ./.github/actions/setup-build
with:
cache-suffix: ${{ matrix.os-arch }}-${{ matrix.llvm-build }}-${{ matrix.torch-binary }}
- name: Configure os-arch='ubuntu-x86_64' llvm-build='in-tree' torch-binary='${{ matrix.torch-binary }}'
# Fastest build, most used dev flow
if: ${{ matrix.os-arch == 'ubuntu-x86_64' && matrix.llvm-build == 'in-tree' }}
run: |
cmake -GNinja -Bbuild \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_C_COMPILER=clang \
-DCMAKE_CXX_COMPILER=clang++ \
-DCMAKE_C_COMPILER_LAUNCHER=ccache \
-DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
-DCMAKE_LINKER=lld \
-DLLVM_ENABLE_ASSERTIONS=ON \
-DLLVM_ENABLE_PROJECTS=mlir \
-DLLVM_EXTERNAL_PROJECTS="torch-mlir;torch-mlir-dialects" \
-DLLVM_EXTERNAL_TORCH_MLIR_SOURCE_DIR="$GITHUB_WORKSPACE" \
-DLLVM_EXTERNAL_TORCH_MLIR_DIALECTS_SOURCE_DIR="${GITHUB_WORKSPACE}/externals/llvm-external-projects/torch-mlir-dialects" \
-DLLVM_TARGETS_TO_BUILD=host \
-DMLIR_ENABLE_BINDINGS_PYTHON=ON \
-DTORCH_MLIR_ENABLE_MHLO=ON \
-DTORCH_MLIR_USE_INSTALLED_PYTORCH="${{ matrix.torch-binary }}" \
-DPython3_EXECUTABLE="$(which python)" \
$GITHUB_WORKSPACE/externals/llvm-project/llvm
- name: Configure os-arch='ubuntu-x86_64' llvm-build='out-of-tree' torch-binary='${{ matrix.torch-binary }}'
# Most elaborate build, but cached
if: ${{ matrix.os-arch == 'ubuntu-x86_64' && matrix.llvm-build == 'out-of-tree' }}
run: |
cmake -GNinja -Bllvm-build \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_C_COMPILER=clang \
-DCMAKE_CXX_COMPILER=clang++ \
-DCMAKE_C_COMPILER_LAUNCHER=ccache \
-DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
-DCMAKE_LINKER=lld \
-DLLVM_ENABLE_ASSERTIONS=ON \
-DLLVM_ENABLE_PROJECTS=mlir \
-DLLVM_TARGETS_TO_BUILD=host \
-DMLIR_ENABLE_BINDINGS_PYTHON=ON \
-DPython3_EXECUTABLE="$(which python)" \
$GITHUB_WORKSPACE/externals/llvm-project/llvm
cmake --build llvm-build
# TODO: Reenable LTC once OOT build is successful (https://github.com/llvm/torch-mlir/issues/1154)
cmake -GNinja -Bbuild \
-DCMAKE_C_COMPILER=clang \
-DCMAKE_CXX_COMPILER=clang++ \
-DCMAKE_C_COMPILER_LAUNCHER=ccache \
-DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
-DCMAKE_LINKER=lld \
-DLLVM_DIR="$GITHUB_WORKSPACE/llvm-build/lib/cmake/llvm/" \
-DMLIR_DIR="$GITHUB_WORKSPACE/llvm-build/lib/cmake/mlir/" \
-DMLIR_ENABLE_BINDINGS_PYTHON=OFF \
-DTORCH_MLIR_ENABLE_MHLO=ON \
-DTORCH_MLIR_USE_INSTALLED_PYTORCH="${{ matrix.torch-binary }}" \
-DTORCH_MLIR_ENABLE_LTC=OFF \
-DPython3_EXECUTABLE="$(which python)" \
$GITHUB_WORKSPACE
- name: Configure os-arch='macos-arm64' llvm-build='in-tree' torch-binary='${{ matrix.torch-binary }}'
# cross compile, can't test arm64
if: ${{ matrix.os-arch == 'macos-arm64' && matrix.llvm-build == 'in-tree' }}
run: |
cmake -GNinja -Bbuild_arm64 \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_C_COMPILER=clang \
-DCMAKE_CXX_COMPILER=clang++ \
-DCMAKE_C_COMPILER_LAUNCHER=ccache \
-DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
-DCMAKE_LINKER=lld \
-DCMAKE_OSX_ARCHITECTURES=arm64 \
-DLLVM_ENABLE_ASSERTIONS=ON \
-DLLVM_ENABLE_PROJECTS=mlir \
-DLLVM_EXTERNAL_PROJECTS="torch-mlir;torch-mlir-dialects" \
-DLLVM_EXTERNAL_TORCH_MLIR_SOURCE_DIR="$GITHUB_WORKSPACE" \
-DLLVM_EXTERNAL_TORCH_MLIR_DIALECTS_SOURCE_DIR="${GITHUB_WORKSPACE}/externals/llvm-external-projects/torch-mlir-dialects" \
-DLLVM_TARGETS_TO_BUILD=AArch64 \
-DLLVM_USE_HOST_TOOLS=ON \
-DLLVM_ENABLE_ZSTD=OFF \
-DMLIR_ENABLE_BINDINGS_PYTHON=ON \
-DTORCH_MLIR_ENABLE_LTC=OFF \
-DTORCH_MLIR_ENABLE_MHLO=OFF \
-DTORCH_MLIR_USE_INSTALLED_PYTORCH="${{ matrix.torch-binary }}" \
-DMACOSX_DEPLOYMENT_TARGET=12.0 \
-DPython3_EXECUTABLE="$(which python)" \
$GITHUB_WORKSPACE/externals/llvm-project/llvm
- name: Build torch-mlir
if: ${{ matrix.os-arch == 'ubuntu-x86_64' }}
run: |
cmake --build build
- name: Build torch-mlir (cross-compile)
if: ${{ matrix.os-arch == 'macos-arm64' }}
run: |
cmake --build build_arm64
- name: Run torch-mlir unit tests
if: ${{ matrix.os-arch == 'ubuntu-x86_64' }}
run: |
cmake --build build --target check-torch-mlir-all
- name: Run refbackend e2e integration tests
if: ${{ matrix.os-arch == 'ubuntu-x86_64' && matrix.llvm-build == 'in-tree' }}
run: |
export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir"
python -m e2e_testing.torchscript.main --config=refbackend -v
- name: Run eager_mode e2e integration tests
if: ${{ matrix.os-arch == 'ubuntu-x86_64' && matrix.llvm-build == 'in-tree' }}
run: |
export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir"
python -m e2e_testing.torchscript.main --config=eager_mode -v
- name: Run tosa e2e integration tests
if: ${{ matrix.os-arch == 'ubuntu-x86_64' && matrix.llvm-build == 'in-tree' }}
run: |
export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir"
python -m e2e_testing.torchscript.main --config=tosa -v
- name: Run lazy_tensor_core e2e integration tests
if: ${{ matrix.os-arch == 'ubuntu-x86_64' && matrix.llvm-build == 'in-tree' }}
run: |
export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir"
python -m e2e_testing.torchscript.main --config=lazy_tensor_core -v