onnx-mlir/CMakeLists.txt

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CMake
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# TODO: remove for release.
if(NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE Debug CACHE STRING "build type")
endif()
# Require 3.3 and set policy CMP0057 for IN_LIST operator support
cmake_minimum_required(VERSION 3.3)
cmake_policy(SET CMP0057 NEW)
project(onnx-mlir)
set(CMAKE_CXX_FLAGS_DEBUG "-g")
set(CMAKE_CXX_FLAGS_RELEASE "-O2 -DNDEBUG")
set(ONNX_MLIR_SRC_ROOT "${CMAKE_CURRENT_SOURCE_DIR}")
set(ONNX_MLIR_BIN_ROOT "${CMAKE_CURRENT_BINARY_DIR}")
set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
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set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
include(MLIR.cmake)
if (MSVC)
# Disable warnings that prevent building of dependencies
# like onnx
set(CMAKE_CXX_FLAGS "-wd4244 -wd4267 -wd4530 -wd4624")
endif()
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add_subdirectory(third_party/onnx)
add_subdirectory(third_party/benchmark)
add_subdirectory(third_party/pybind11)
add_subdirectory(third_party/variant)
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set(CMAKE_CXX_STANDARD 14)
add_subdirectory(utils)
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add_subdirectory(src)
add_subdirectory(docs)
Enable e2e tests (#29) * Sync with latest MLIR. * Enable ONNX backend tests as a means to test ONNF lowering end-to-end. * Install ONNX using quiet mode. * Remove debug comments. * Install ONNX from third_party/onnx. * Check python version and fix pip command for installing ONNX. * Using --user install option to prevent permission denied. * Remove unused imports. * Try using stock ONNX pip package as there are more tests in them. * Pip got stuck building wheels, try sudo. * Use verbose install to debug. * Invalidate cache to build LLVM tools. * Fix mlir installation script location. * Debug to locate ONNF. * Sanity check. * Check out ONNF code first. * Use verbose LIT output. * 1. Update documentation to always use verbose LIT. 2. Update krnl ops to reflect new affine map attribute syntax. * See if conda exists * Install ONNX by manually cloning the repo. * Install cmake first. * Using sudo priviledge when installing. * Limit build parallelism. * Limit parallelism. * Larger memory. * Install onnx package with pip. * Build MLIR tools. * Invalidate cache. * Compile model.so with -fPIC. * Remove module dump to get concise debug output. * Print command before executing. * Use quiet install mode to reduce logging. * Use -relocation-model=pic to generate position independent code. * 1. Remove MAKEFLAGS because now buildbot has enough memory. 2. Run DocCheck as a last step. * 1. Add verbose mode for backtend test. * When dumping to LLVM bitcode, do not dump module IR, but print a message indicating that bitcode has been written to disk. * Do not pass MakeFlags to CMake. * Add more explaination for posible reasons of failing to identify tests.
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add_subdirectory(test)