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ACL is already built with PyTorch as a shared library when USE_MKLDNN_ACL is set. Currently, it is only used indirectly in ATen via oneDNN for AArch64 targets. However there are cases where it makes sense to utilize ACL directly without oneDNN as an intermediary - e.g. quantization. See #145942, #147337, #146620. This patch enables such use cases by exposing ACL to ATen Pull Request resolved: https://github.com/pytorch/pytorch/pull/148584 Approved by: https://github.com/malfet |
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| External | ||
| Modules | ||
| Modules_CUDA_fix | ||
| public | ||
| Allowlist.cmake | ||
| BuildVariables.cmake | ||
| Caffe2Config.cmake.in | ||
| CheckAbi.cmake | ||
| cmake_uninstall.cmake.in | ||
| Codegen.cmake | ||
| DebugHelper.cmake | ||
| Dependencies.cmake | ||
| FlatBuffers.cmake | ||
| GoogleTestPatch.cmake | ||
| IncludeSource.cpp.in | ||
| iOS.cmake | ||
| Metal.cmake | ||
| MiscCheck.cmake | ||
| prioritized_text.txt | ||
| ProtoBuf.cmake | ||
| ProtoBufPatch.cmake | ||
| Summary.cmake | ||
| TorchConfig.cmake.in | ||
| TorchConfigVersion.cmake.in | ||
| VulkanCodegen.cmake | ||
| VulkanDependencies.cmake | ||