colin
/
onnx-mlir
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
onnx-mlir/test/backend/CMakeLists.txt

20 lines
595 B
CMake
Raw Normal View History

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.
2020-01-21 01:30:08 +08:00
configure_file(test.py test.py COPYONLY)
configure_file(test_config.py.in test_config.py)
find_package(PythonInterp 3 REQUIRED)
Fix running backend tests triggered by preloading cruntime dynamic library (#104) * Reorganize main function. * Follow review comments. * Emit constants are globals in Krnl and LLVM dialects. * Fix preloading of runtime shared library for backend tests. * Update library name. * Only add libstdc++ library if it exists.
2020-05-04 20:37:58 +08:00
set(LD_PRELOADS $<TARGET_FILE:cruntime>)
get_filename_component(CXX_BIN_DIR ${CMAKE_CXX_COMPILER} PATH)
set(LIBSTDCXX_LIB "${CXX_BIN_DIR}/../lib64/libstdc++.so")
if(EXISTS ${LIBSTDCXX_LIB})
set(LD_PRELOADS ${LIBSTDCXX_LIB}:${LD_PRELOADS})
endif()
Name change for tests, to be check-onnx-(lit | backend) (#62)
2020-03-31 22:06:14 +08:00
add_custom_target(check-onnx-backend
Specify in linking stage, where runtime shared library is located. (#120) * Specify in linking stage, where runtime shared library is located. * Cite & make comment a full sentence. * Fix error communicating runtime dir to ld.
2020-05-14 09:04:16 +08:00
COMMAND ${PYTHON_EXECUTABLE}
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.
2020-01-21 01:30:08 +08:00
${CMAKE_CURRENT_BINARY_DIR}/test.py)
Name change for tests, to be check-onnx-(lit | backend) (#62)
2020-03-31 22:06:14 +08:00
add_dependencies(check-onnx-backend onnx-mlir)
Rapid check test (#141) * Call llc, ld from within onnx-mlir. * Rename EmitLLVMBC -> EmitLib., reorder header files * Edit comment. * Checkpoint, debug.py works. * Automatically generate inputs in debug.py. * Use float. * initial support for rapidcheck tests. * Convolution test case works. * Format code. * Link library with MainUtils. * Fix CMake script error. * Fast implementation of array assertion, more detailed error analysis. * More utility for DynMemRef. * Fix linking issue. * Uncomment unit test. * Refactor to separate C++/Python ExecutionSession, enable unit test. * format code. * Verbose build. * Enable PIC option for ExecusionSession. * Fix cmake error. * Build all targets. * Fix doc to build all targets. * Clean up. * Clean up, debug. * Use type alias consistently. * Move definitions to DynMemRef.cpp. * include algorithm. * pyruntime -> PyRuntime * Format code. * Free memory. * Add comments. * Copyright notice. * Improve stylistic consistency. * Add comment. * Revert irrelevant changes. * Disambiguate. * Refator test case generator out from test case implementation, implement example exhaustive test driver. * Add documentation for testing.
2020-06-08 10:18:55 +08:00
add_dependencies(check-onnx-backend PyRuntime)