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This issue came from https://github.com/conda-forge/pytorch-cpu-feedstock/issues/180. MKL follows the F2C convention for returning single precision floats as doubles and uses the G77 convention for returning complex valued scalars. OpenBLAS does the opposite. There is a check for this already, but it's done only when the Generic BLAS vendor code path is used and this PR moves that code to `Dependencies.cmake` to make it work when the BLAS vendor is OpenBLAS and others Pull Request resolved: https://github.com/pytorch/pytorch/pull/143846 Approved by: https://github.com/rgommers, https://github.com/atalman |
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| .. | ||
| External | ||
| Modules | ||
| Modules_CUDA_fix | ||
| public | ||
| Allowlist.cmake | ||
| BLAS_ABI.cmake | ||
| BuildVariables.cmake | ||
| Caffe2Config.cmake.in | ||
| cmake_uninstall.cmake.in | ||
| Codegen.cmake | ||
| DebugHelper.cmake | ||
| Dependencies.cmake | ||
| FlatBuffers.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 | ||