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onnx-mlir/test/CMakeLists.txt

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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
add_subdirectory(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_subdirectory(backend)
Cleanup rtmemref api (#238) * Detect llvm-project commit change in utils/clone-mlir.sh and rebuild llvm-project for zLinux Jenkins build bot * Cleanup RtMemRef API - use forward declaration to hide private data fields - RtMemRef.h: external user header, C/C++ - _RtMemRef.h: internal user header, C++ only - RtMemRef.hpp and RtMemRef.cpp: implementation header and file - add external APIs OrderedRtMemRefDict *ormrd_create(RtMemRef **rmrs, int n) RtMemRef **ormrd_getRmrs(OrderedRtMemRefDict *ormrd) int ormrd_getNumOfRmrs(OrderedRtMemRefDict *ormrd) for creating and querying OrderedRtMemRefDict with RtMemRef arrays - data buffer installed by rmr_setData() will be managed by user - unique_ptr<RtMemRef> must use custom deleter <RtMemRef,decltype(&rmr_destroy)> * See if I have write access. * Remove test CMake code. * Use new API. * Format code. * Format code & rename variables for readability. * Remove used API spec. * Rename OrderedRtMemRefDict -> RtMemRefList, _dataMalloc -> _owningData. * OrderedRtMemRefDict -> RtMemRefList * Update KrnlToLLVM.cpp * Trigger Jenkins * Restart Jenkins * OrderedRtMemRefDict -> RtRmrRefList * More OrderedRtMemRefDict -> RtMemRefList. * Format jni wrapper. * Rename API functions to maintain stylistic consistency. * Bug fix. * Bug fix. * Format code. * Fix RtMemRefUtils. * Format code. * Using llvm function naming scheme. * Rename runtime api file name to project name (onnx-mlir) as per convention. * Include the new runtime header file. * Reflect api header file name change in build script. * Bug fix. * Remove C++ code. * Revert "Remove C++ code." This reverts commit b217dfabae99e42db30721600cb5507866d4dc98. * Clarify memory management responsibility. * Add constructor to specify name & data ownership. * Include stdbool. * Remove dictionary semantics from RtMemRefList * Bug fix. * Format code. * Format code. * Use macro to define database of metadata. * Prevent formatter from acting on metadata decl. * Nit. * Restore backend unit tests. * Use spaces instead of tabs for better formatting. * Use explicit template instantiation. * Update RtMemRef struct doc. * Make runtime compilable both in c and c++ mode. Build two versions of the runtime library, one c version as the user-facing c runtime, and one c++ version as the one used inside this project. * Bug fix, avoid stack allocation for output rmr list. * Change _dyn_entry_point_main_graph -> run_main_graph for better memorability. * Write a complete introductory tutorial on c99 Runtime and a test for it. * Add onnx installation as dependency. * Use target_include_directory to avoid installation. * Format code. * Fix cmake target_include_directories. * Address compiler warning. * First pass of RtMemRef->OMTensor. * Second pass of RtMemRef -> OMTensor. * nit, omtList -> omTensorList. * omt -> omTensor for clarity. * Rename OnnxMlirInternal.h -> OnnxMlirRuntime.hpp because there's no internal/external API, only C/C++ API. * Format code. * Restructure Runtime source code and move header -> /include and test -> /test/unit. * Bugfix. * Format code. * Add unit test for OMTensor ctor. * Update JNI CMake include directory. * Bugfix. * No need to re-declare ONNX types. * Disable runtime doc test on non-x86 platforms. * Rename OMTensor fields to be more sensible. * Fix data type mismatch. * size_t -> int64_t, prefer fixed width integers. * Use consistent header guard style. * Further tweak OMTensor API. * Bugfix. * Bugfix. * Format code. * Add doxygen config file. * Tweak OMTensor API. * Tweak API doc, hide OMTensorList implementation. * Format code. * Add new documentation item for Runtime API. * Hide internal use only API declarations, move their comments to their implementations. * Clarify ownership semantics in relevant API documentations. * Fix PyRuntime. * Remove alignment concerns from public API and include explaination of alignment issue in struct OMTensor definition. * Print out unsupported numpy dtype. * Use preferred way of type comparison in pybind11. * Debug s390x issue. * Remove debug code. * Clarify semantics of strides/shape setter/getter, use \brief to include short description of API function. * Improve documentation. * Single out unpolished C++ API declarations. * Clarify OMTensorList API. * Bugfix. * Bugfix. * Assert after malloc. * Handle malloc failures. * Nit. * Tweak legal notices. * Format code. * Remove doxygen generated files. * Tweak legal notice format. * Upgrade Cython Numpy installation depends on Cython. Co-authored-by: Tian Jin <tjingrant@gmail.com>
2020-10-10 22:32:09 +08:00
add_subdirectory(numerical)
add_subdirectory(unit)