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bazel build failure of tensorflow with mkl and specific eigen3 flags #10157
Describe the problem
Bazel failed to build/compile tensor flow with mkl support
Source code / logs
I removed the MKL flag and now the compilation finished, however I wish to work with MKL support and I don't know how to confirm that the Eigen's code generation and compilation of tensorflow integrated successfully with my current project (which already uses MKL and 64bit integers as indexes).
I guess currently I don't have a better way to make sure it's OK besides using breakpoints inside Eigen source code and see if it calls the correct functions in MKL.
Regarding the bazel workspace, I didn't modify any file. Do I need to?
@drormeir I fixed this problem editing the file Eigen/src/Core/util/MKL_support.h
I added the following code at line 116:
and in my CMakeLists I did:
This problem is a conflict between MKL_INT and BLAS index type. In my case, the BLAS is using int as index and MKL_INT is a long long. I did this workaround and everything is working fine.
Also, I did a pull request to eigen repository. I`m waiting to be accepted.
It is not a bug in TensorFlow; it's a problem with Eigen.
When used in the MKL mode, Eigen's code defines
It is utterly confusing because the definition of
@gogo40 Your patch is unnecessary if you use short indices (
@drormeir if you use
On Jul 14, 2017 23:57, "Lukasz Janyst" ***@***.***> wrote: It is not a bug in TensorFlow; it's a problem with Eigen. When used in the MKL mode, Eigen's code defines BlasIndex to be whatever MKL_INT is: typedef MKL_INT BlasIndex; It is utterly confusing because the definition of MKL_INT varies depending on the size of indices you want to use in your program. However, instead of using the MKL's BLAS interface, which takes the size of MKL_INT into account, Eigen defines its own interface ( https://bitbucket.org/eigen/eigen/src/e7027de735d6450c8ede3ce2f65166 714c6aef50/Eigen/src/misc/blas.h?at=default&fileviewer=file-view-default) using only 32-bit long ints. This is the reason for the compilation errors you see. @gogo40 <https://github.com/gogo40> Your patch is unnecessary if you use short indices (-DMKL_LP64) and makes a significant chunk of the Eigen's unit tests fail if you use long indices (-DMKL_ILP64 -DEIGEN_BLAS_INDEX=int). This is because the implementation of BLAS in libmkl_intel_ilp64.so expects 64-bit long indices. @drormeir <https://github.com/drormeir> if you use -DMKL_LP64 instead of -DMKL_ILP64, TensorFlow will compile fine. I would not expect to see performance improvements though. — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#10157 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AYEDEa7uYfjj9T7CCpmXYlBFZat8h3jiks5sN9Y3gaJpZM4Nk8LC> .