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Summary: Since v1.7, oneDNN (MKL-DNN) has supported the use of Compute Library for the Arm architeture to provide optimised convolution primitives on AArch64. This change enables the use of Compute Library in the PyTorch build. Following the approach used to enable the use of CBLAS in MKLDNN, It is enabled by setting the env vars USE_MKLDNN and USE_MKLDNN_ACL. The location of the Compute Library build must be set useing `ACL_ROOT_DIR`. This is an extension of the work in https://github.com/pytorch/pytorch/pull/50400 which added support for the oneDNN/MKL-DNN backend on AArch64. _Note: this assumes that Compute Library has been built and installed at ACL_ROOT_DIR. Compute library can be downloaded here: `https://github.com/ARM-software/ComputeLibrary`_ Fixes #{issue number} Pull Request resolved: https://github.com/pytorch/pytorch/pull/55913 Reviewed By: ailzhang Differential Revision: D28559516 Pulled By: malfet fbshipit-source-id: 29d24996097d0a54efc9ab754fb3f0bded290005 |
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| .. | ||
| External | ||
| Modules | ||
| Modules_CUDA_fix | ||
| public | ||
| Allowlist.cmake | ||
| BuildVariables.cmake | ||
| Caffe2Config.cmake.in | ||
| Caffe2ConfigVersion.cmake.in | ||
| cmake_uninstall.cmake.in | ||
| Codegen.cmake | ||
| DebugHelper.cmake | ||
| Dependencies.cmake | ||
| GoogleTestPatch.cmake | ||
| iOS.cmake | ||
| Metal.cmake | ||
| MiscCheck.cmake | ||
| ProtoBuf.cmake | ||
| ProtoBufPatch.cmake | ||
| Summary.cmake | ||
| TorchConfig.cmake.in | ||
| TorchConfigVersion.cmake.in | ||
| VulkanCodegen.cmake | ||
| VulkanDependencies.cmake | ||