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

183 lines
7.3 KiB
YAML

name: Build and Test
on:
push:
branches:
- main
pull_request:
workflow_dispatch:
jobs:
build-validate:
strategy:
fail-fast: true
matrix:
os: [macos-12, ubuntu-22.04]
targetarch: [x86_64, arm64]
python-version: ["3.10"]
torch-binary: [ON, OFF]
llvmtype: [source, binary]
llvmbuildtype: [in-tree, out-of-tree]
exclude:
# No need for "out-of-tree LLVM and PyTorch source"
- llvmtype: source
llvmbuildtype: in-tree
- llvmtype: binary
llvmbuildtype: out-of-tree
- llvmbuildtype: out-of-tree
torch-binary: OFF
# Disable M1 builds until https://github.com/llvm/torch-mlir/issues/1094 is fixed
- targetarch: arm64
os: ubuntu-22.04
# macOS we only do source builds to reduce options
- os: macos-12
torch-binary: OFF
- os: macos-12
llvmtype: source
- os: macos-12
llvmtype: out-of-tree
- os: macos-12
targetarch: x86_64
runs-on: ${{ matrix.os }}
steps:
- name: Checkout torch-mlir
uses: actions/checkout@v2
with:
submodules: 'true'
- uses: ./.github/actions/setup-build
with:
cache-suffix: ${{ matrix.os }}-${{ matrix.targetarch }}-${{ matrix.llvmtype }}-${{ matrix.llvmbuildtype }}
- name: Configure llvm-cross-compile
# libzstd on GH Runners are only x86_64 to remove them.
if: matrix.targetarch == 'arm64'
run: |
sudo rm -rf /usr/local/lib/libzstd.*.dylib
sudo rm -rf /usr/local/lib/cmake/zstd/*
cd $GITHUB_WORKSPACE
cmake -GNinja -Bbuild_${{ matrix.targetarch }} \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_LINKER=lld \
-DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
-DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ \
-DPython3_EXECUTABLE=$(which python) \
-DLLVM_ENABLE_ASSERTIONS=ON \
-DLLVM_ENABLE_PROJECTS=mlir \
-DLLVM_EXTERNAL_PROJECTS="torch-mlir;torch-mlir-dialects" \
-DLLVM_EXTERNAL_TORCH_MLIR_SOURCE_DIR="$GITHUB_WORKSPACE" \
-DLLVM_EXTERNAL_TORCH_MLIR_DIALECTS_SOURCE_DIR="${GITHUB_WORKSPACE}/external/llvm-external-projects/torch-mlir-dialects" \
-DMLIR_ENABLE_BINDINGS_PYTHON=ON \
-DTORCH_MLIR_ENABLE_LTC=OFF \
-DTORCH_MLIR_ENABLE_MHLO=OFF \
-DTORCH_MLIR_USE_INSTALLED_PYTORCH=${{ matrix.torch-binary }} \
-DCMAKE_OSX_ARCHITECTURES=${{ matrix.targetarch }} \
-DMACOSX_DEPLOYMENT_TARGET=12.0 \
-DLLVM_TARGETS_TO_BUILD="AArch64" \
-DLLVM_USE_HOST_TOOLS=ON \
$GITHUB_WORKSPACE/externals/llvm-project/llvm
- name: Configure llvm-binary-torch-src-or-binary
# Should be the fastest builds for CI and fails fast
# OSX CMake flags are ignored on Linux
if: matrix.llvmtype == 'binary'
run: |
cd $GITHUB_WORKSPACE
cmake -GNinja -Bbuild \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_LINKER=lld \
-DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
-DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ \
-DPython3_EXECUTABLE=$(which python) \
-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}/external/llvm-external-projects/torch-mlir-dialects" \
-DMLIR_ENABLE_BINDINGS_PYTHON=ON \
-DTORCH_MLIR_ENABLE_MHLO=ON \
-DTORCH_MLIR_USE_INSTALLED_PYTORCH=${{ matrix.torch-binary }} \
-DCMAKE_OSX_ARCHITECTURES=${{ matrix.taregetarch }} \
-DMACOSX_DEPLOYMENT_TARGET=10.15 \
-DLLVM_TARGETS_TO_BUILD=host \
$GITHUB_WORKSPACE/externals/llvm-project/llvm
- name: Configure llvm-source-out-of-tree-torch-src-or-binary
# This build takes a while but is expected to almost always be cached.
# A cache invalidation occurs when the committed LLVM version is changed.
if: matrix.llvmtype == 'source'
run: |
cd $GITHUB_WORKSPACE
cmake -GNinja -Bllvm-build \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_LINKER=lld \
-DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
-DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ \
-DPython3_EXECUTABLE=$(which python) \
-DLLVM_ENABLE_ASSERTIONS=ON \
-DLLVM_ENABLE_PROJECTS=mlir \
-DMLIR_ENABLE_BINDINGS_PYTHON=ON \
-DLLVM_TARGETS_TO_BUILD=host \
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_LINKER=lld \
-DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
-DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ \
-DMLIR_DIR="$(pwd)/llvm-build/lib/cmake/mlir/" \
-DLLVM_DIR="$(pwd)/llvm-build/lib/cmake/llvm/" \
-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) \
-DLLVM_TARGETS_TO_BUILD=host \
.
- name: Build torch-mlir
if: matrix.targetarch == 'x86_64'
run: |
cmake --build build
- name: Build torch-mlir (cross-compile)
if: matrix.targetarch == 'arm64'
run: |
cmake --build build_${{ matrix.targetarch }}
- name: Run torch-mlir unit tests
if: matrix.llvmtype == 'binary'
run: |
cd $GITHUB_WORKSPACE
export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir"
cmake --build build --target check-torch-mlir-all
- name: Run RefBackend - TorchScript end-to-end tests
if: matrix.llvmtype == 'binary'
run: |
cd $GITHUB_WORKSPACE
export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir"
python -m e2e_testing.torchscript.main --config=refbackend -v
- name: Run EagerMode - TorchScript end-to-end tests
if: matrix.llvmtype == 'binary'
run: |
cd $GITHUB_WORKSPACE
export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir"
python -m e2e_testing.torchscript.main --config=eager_mode -v
- name: Run TOSA backend - TorchScript end-to-end tests
if: matrix.llvmtype == 'binary'
run: |
cd $GITHUB_WORKSPACE
export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir"
python -m e2e_testing.torchscript.main --config=tosa -v
- name: Run Lazy Tensor Core - TorchScript end-to-end tests
if: matrix.llvmtype == 'binary'
run: |
cd $GITHUB_WORKSPACE
export PYTHONPATH="$GITHUB_WORKSPACE/build/tools/torch-mlir/python_packages/torch_mlir"
python -m e2e_testing.torchscript.main --config=lazy_tensor_core -v