4ee29d6033
Re-landing #68111/#74596 ## Description v0.5 PR of this [RFC](https://github.com/pytorch/pytorch/issues/49444). On the basis of #50256, the below improvements are included: * The [v0.5 release branch](https://github.com/oneapi-src/oneDNN/releases/tag/graph-v0.5) of the oneDNN Graph API is used * The fuser now works with the profiling graph executor. We have inserted type check nodes to guard the profiled tensor properties. ### User API: The optimization pass is disabled by default. Users could enable it by: ``` torch.jit.enable_onednn_fusion(True) ``` `torch.jit.freeze` should be used after tracing (recommended) or scripting a model. ### Performance: [pytorch/benchmark](https://github.com/pytorch/benchmark) tool is used to compare the performance: * SkyLake 8180 (1 socket of 28 cores):  * SkyLake 8180 (single thread):  * By mapping hardswish to oneDNN Graph, it’s 8% faster than PyTorch JIT (NNC + OFI) ** We expect performance gain after mapping transpose, contiguous & view to oneDNN graph ops ### Directory structure of the integration code Fuser-related code is placed under: ``` torch/csrc/jit/codegen/onednn/ ``` Optimization pass registration is done in: ``` torch/csrc/jit/passes/onednn_graph_fuser.h ``` CMake for the integration code is in: ``` caffe2/CMakeLists.txt cmake/public/mkldnn.cmake cmake/Modules/FindMKLDNN.cmake ``` ## Limitations * In this PR, we only support Pytorch-oneDNN-Graph integration on Linux platform. Support on Windows and MacOS will be enabled as a next step. * We have only optimized the inference use-case. Pull Request resolved: https://github.com/pytorch/pytorch/pull/76622 Approved by: https://github.com/eellison
This folder contains various custom cmake modules for finding libraries and packages. Details about some of them are listed below.
FindOpenMP.cmake
This is modified from the file included in CMake 3.13 release, with the following changes:
-
Replace
VERSION_GREATER_EQUALwithNOT ... VERSION_LESSasVERSION_GREATER_EQUALis not supported in CMake 3.5 (our min supported version). -
Update the
separate_argumentscommands to not useNATIVE_COMMANDwhich is not supported in CMake 3.5 (our min supported version). -
Make it respect the
QUIETflag so that, when it is set,try_compilefailures are not reported. -
For
AppleClangcompilers, use-Xpreprocessorinstead of-Xclangas the later is not documented. -
For
AppleClangcompilers, an extra flag option is tried, which is-Xpreprocessor -openmp -I${DIR_OF_omp_h}, where${DIR_OF_omp_h}is a obtained usingfind_pathonomp.hwithbrew's default include directory as a hint. Without this, the compiler will complain about missing headers as they are not natively included in Apple's LLVM. -
For non-GNU compilers, whenever we try a candidate OpenMP flag, first try it with directly linking MKL's
libompif it has one. Otherwise, we may end up linking twolibomps and end up with this nasty error:OMP: Error #15: Initializing libomp.dylib, but found libiomp5.dylib already initialized. OMP: Hint This means that multiple copies of the OpenMP runtime have been linked into the program. That is dangerous, since it can degrade performance or cause incorrect results. The best thing to do is to ensure that only a single OpenMP runtime is linked into the process, e.g. by avoiding static linking of the OpenMP runtime in any library. As an unsafe, unsupported, undocumented workaround you can set the environment variable KMP_DUPLICATE_LIB_OK=TRUE to allow the program to continue to execute, but that may cause crashes or silently produce incorrect results. For more information, please see http://openmp.llvm.org/See NOTE [ Linking both MKL and OpenMP ] for details.