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