mirror of https://github.com/llvm/torch-mlir
168 lines
6.1 KiB
CMake
168 lines
6.1 KiB
CMake
include(AddMLIRPython)
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# Disables generation of "version soname" (i.e. libFoo.so.<version>), which
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# causes pure duplication as part of Python wheels.
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set(CMAKE_PLATFORM_NO_VERSIONED_SONAME ON)
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# The directory at which the Python import tree begins.
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# See documentation for `declare_mlir_python_sources`'s ROOT_DIR
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# argument.
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set(TORCH_MLIR_PYTHON_ROOT_DIR "${CMAKE_CURRENT_SOURCE_DIR}/torch_mlir")
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# We vendor our own MLIR instance in the `torch_mlir` namespace.
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add_compile_definitions("MLIR_PYTHON_PACKAGE_PREFIX=torch_mlir.")
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################################################################################
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# PyTorch
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################################################################################
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option(TORCH_MLIR_USE_INSTALLED_PYTORCH "Build from local PyTorch in environment" ON)
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if (NOT TORCH_MLIR_USE_INSTALLED_PYTORCH)
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# Source builds
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set(ENV{TORCH_MLIR_SRC_PYTORCH_REPO} ${TORCH_MLIR_SRC_PYTORCH_REPO})
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set(ENV{TORCH_MLIR_SRC_PYTORCH_BRANCH} ${TORCH_MLIR_SRC_PYTORCH_BRANCH})
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set(ENV{MACOSX_DEPLOYMENT_TARGET} ${MACOSX_DEPLOYMENT_TARGET})
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set(ENV{CMAKE_OSX_ARCHITECTURES} ${CMAKE_OSX_ARCHITECTURES})
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set(ENV{CMAKE_C_COMPILER_LAUNCHER} ${CMAKE_C_COMPILER_LAUNCHER})
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set(ENV{CMAKE_CXX_COMPILER_LAUNCHER} ${CMAKE_CXX_COMPILER_LAUNCHER})
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execute_process(
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COMMAND ${CMAKE_CURRENT_SOURCE_DIR}/../build_tools/build_libtorch.sh
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RESULT_VARIABLE _result
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)
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if(_result)
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message(FATAL_ERROR "Failed to run `build_libtorch.sh`")
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endif()
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set(TORCH_INSTALL_PREFIX "libtorch")
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endif()
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################################################################################
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# Sources
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################################################################################
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declare_mlir_python_sources(TorchMLIRPythonSources)
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declare_mlir_python_sources(TorchMLIRPythonExtensions)
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declare_mlir_python_sources(TorchMLIRPythonSources.TopLevel
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ROOT_DIR "${TORCH_MLIR_PYTHON_ROOT_DIR}"
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ADD_TO_PARENT TorchMLIRPythonSources
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SOURCES
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__init__.py
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compiler_utils.py
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)
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declare_mlir_python_sources(TorchMLIRPythonSources.Dialects
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ROOT_DIR "${TORCH_MLIR_PYTHON_ROOT_DIR}"
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ADD_TO_PARENT TorchMLIRPythonSources
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)
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declare_mlir_dialect_python_bindings(
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ADD_TO_PARENT TorchMLIRPythonSources.Dialects
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ROOT_DIR "${TORCH_MLIR_PYTHON_ROOT_DIR}"
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TD_FILE dialects/TorchBinding.td
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SOURCES dialects/torch/__init__.py
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DIALECT_NAME torch
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)
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################################################################################
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# Extensions
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################################################################################
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declare_mlir_python_extension(TorchMLIRPythonExtensions.Main
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MODULE_NAME _torchMlir
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ADD_TO_PARENT TorchMLIRPythonExtensions
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SOURCES
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TorchMLIRModule.cpp
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EMBED_CAPI_LINK_LIBS
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TorchMLIRCAPI
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PRIVATE_LINK_LIBS
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LLVMSupport
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)
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################################################################################
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# Lazy Tensor Core
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################################################################################
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if(TORCH_MLIR_ENABLE_LTC)
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add_subdirectory(torch_mlir/csrc/base_lazy_backend)
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endif()
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# Reference backend has a separate check for TORCH_MLIR_ENABLE_LTC, since it
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# generates a dummy Python library when disabled.
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add_subdirectory(torch_mlir/csrc/reference_lazy_backend)
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################################################################################
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# Optionally handle JIT IR importer.
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################################################################################
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if(TORCH_MLIR_ENABLE_JIT_IR_IMPORTER)
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add_subdirectory(torch_mlir/dialects/torch/importer/jit_ir)
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add_subdirectory(torch_mlir_e2e_test)
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endif()
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################################################################################
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# Eager mode
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################################################################################
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add_subdirectory(torch_mlir/eager_mode)
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################################################################################
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# Custom op example
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# Required for running the update_torch_ods.sh and update_shape_lib.sh scripts.
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################################################################################
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# add_subdirectory(torch_mlir/_torch_mlir_custom_op_example)
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################################################################################
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# Generate packages and shared library
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# Downstreams typically will not use these, but they are useful for local
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# testing.
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################################################################################
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set(_source_components
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# TODO: Core is now implicitly building/registering all dialects, increasing
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# build burden by ~5x. Make it stop.
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# TODO: Reduce dependencies. We need ExecutionEngine and a bunch of passes
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# for the reference backend, but logically they can be separate. But seemingly
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# the only way to handle that is to create a separate mlir python package
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# tree, which seems excessive.
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MLIRPythonSources
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MLIRPythonExtension.Core
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MLIRPythonExtension.RegisterEverything
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TorchMLIRPythonSources
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TorchMLIRPythonExtensions
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)
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add_mlir_python_common_capi_library(TorchMLIRAggregateCAPI
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INSTALL_COMPONENT TorchMLIRPythonModules
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INSTALL_DESTINATION python_packages/torch_mlir/torch_mlir/_mlir_libs
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OUTPUT_DIRECTORY "${TORCH_MLIR_PYTHON_PACKAGES_DIR}/torch_mlir/torch_mlir/_mlir_libs"
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RELATIVE_INSTALL_ROOT "../../../.."
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DECLARED_SOURCES ${_source_components}
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)
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add_mlir_python_modules(TorchMLIRPythonModules
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ROOT_PREFIX "${TORCH_MLIR_PYTHON_PACKAGES_DIR}/torch_mlir/torch_mlir"
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INSTALL_PREFIX "python_packages/torch_mlir/torch_mlir"
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DECLARED_SOURCES ${_source_components}
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COMMON_CAPI_LINK_LIBS
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TorchMLIRAggregateCAPI
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)
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# TODO: Find a cleaner way to do this.
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# Can we build the JIT IR importer with `declare_mlir_python_extension`?
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# Then it would "just work".
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if(TORCH_MLIR_ENABLE_JIT_IR_IMPORTER)
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add_dependencies(TorchMLIRPythonModules TorchMLIRJITIRImporter)
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# Build the E2E Tests (which depend on the JIT IR importer now).
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add_dependencies(TorchMLIRPythonModules TorchMLIRE2ETestPythonModules)
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endif()
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if(TORCH_MLIR_ENABLE_LTC)
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# Add Torch-MLIR LTC backend as dependency
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add_dependencies(TorchMLIRPythonModules torch_mlir_ltc_backend)
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add_dependencies(TorchMLIRPythonModules reference_lazy_backend)
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endif()
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add_subdirectory(test)
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