defer resolution of mkl to a cmake wrapper library#11298
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anderspapitto wants to merge 1 commit intopytorch:masterfrom
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defer resolution of mkl to a cmake wrapper library#11298anderspapitto wants to merge 1 commit intopytorch:masterfrom
anderspapitto wants to merge 1 commit intopytorch:masterfrom
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this is a fix that's needed for building extensions with a pre-packaged pytorch. Consider the scenario where (1) pytorch is compiled and packaged on machine A (2) the package is downloaded and installed on machine B (3) an extension is compiled on machine B, using the downloaded package Before this patch, stage (1) would embed absolute paths to the system installation of mkl into the generated Caffe2Config.cmake, leading to failures in stage (3) if mkl was not at the same location on B as on A. After this patch, only a reference to the wrapper library is embedded, which is re-resolved on machine B. We are already using a similar approach for cuda.
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zdevito
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Sep 6, 2018
Summary: this is a fix that's needed for building extensions with a pre-packaged pytorch. Consider the scenario where (1) pytorch is compiled and packaged on machine A (2) the package is downloaded and installed on machine B (3) an extension is compiled on machine B, using the downloaded package Before this patch, stage (1) would embed absolute paths to the system installation of mkl into the generated Caffe2Config.cmake, leading to failures in stage (3) if mkl was not at the same location on B as on A. After this patch, only a reference to the wrapper library is embedded, which is re-resolved on machine B. We are already using a similar approach for cuda. Testing: built a package on jenkins, downloaded locally and compiled an extension. Works with this patch, fails without. Pull Request resolved: pytorch/pytorch#11298 Differential Revision: D9683150 Pulled By: anderspapitto fbshipit-source-id: 06a80c3cd2966860ce04f76143b358de15f94aa4
petrex
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Sep 6, 2018
* upstream/master: (26 commits) cudnn 7 upgrade with spatialBN fix (pytorch#11291) Ignore FuseGraph Call on Windows (pytorch#11015) defer resolution of mkl to a cmake wrapper library (pytorch#11298) Cleanup dependency of distributed flags (pytorch#11221) Move minimal wrapdim functionality to core, remove THTensor include i… (pytorch#11283) Change includes from ATen/Storage.h to ATen/core/Storage.h (pytorch#11217) Fix scalar tensor assert in fusion compiler (pytorch#10952) Add dead code elimination pass (pytorch#10101) Distributed Data Parallel CPU module for C10D (pytorch#11168) Back out "[pt1][tensor] Add strides to caffe2::Tensor" Fix conv gradient conversion (pytorch#11312) Bag of clang tidy fixes for torch/csrc/ and torch/csrc/autograd (pytorch#11050) Sparse tensor printing; add NotImplemented autograd fn (pytorch#10181) Add convertToCaffe2Proto to python API fix doc for functional.dropout* (pytorch#10417) typo fix Tranpose2D -> Transpose2D (pytorch#11281) Remove THFinalizer Forward declarations of needed curand functions (pytorch#10911) nomnigraph - simplify core graph API and test (pytorch#11256) Small fixes to cppdocs for sync script (pytorch#11300) ...
PenghuiCheng
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Sep 11, 2018
Summary: this is a fix that's needed for building extensions with a pre-packaged pytorch. Consider the scenario where (1) pytorch is compiled and packaged on machine A (2) the package is downloaded and installed on machine B (3) an extension is compiled on machine B, using the downloaded package Before this patch, stage (1) would embed absolute paths to the system installation of mkl into the generated Caffe2Config.cmake, leading to failures in stage (3) if mkl was not at the same location on B as on A. After this patch, only a reference to the wrapper library is embedded, which is re-resolved on machine B. We are already using a similar approach for cuda. Testing: built a package on jenkins, downloaded locally and compiled an extension. Works with this patch, fails without. Pull Request resolved: pytorch#11298 Differential Revision: D9683150 Pulled By: anderspapitto fbshipit-source-id: 06a80c3cd2966860ce04f76143b358de15f94aa4
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this is a fix that's needed for building extensions with a
pre-packaged pytorch. Consider the scenario where
(1) pytorch is compiled and packaged on machine A
(2) the package is downloaded and installed on machine B
(3) an extension is compiled on machine B, using the downloaded package
Before this patch, stage (1) would embed absolute paths to the system
installation of mkl into the generated Caffe2Config.cmake, leading to
failures in stage (3) if mkl was not at the same location on B as on
A. After this patch, only a reference to the wrapper library is
embedded, which is re-resolved on machine B.
We are already using a similar approach for cuda.
Testing: built a package on jenkins, downloaded locally and compiled an extension. Works with this patch, fails without.