【发布时间】:2017-05-22 15:42:33
【问题描述】:
在 TensorFlow 1.1 与我正在进行的 Ubuntu 16 上的 C++ 项目的集成工作中...我想包括对 MKL 和 64 位整数的支持。 在实例化直接调用 MKL 的模板结构时,我在 Eigen 库中遇到了编译问题:
In file included from /usr/local/include/eigen3/unsupported/Eigen/CXX11/../../../Eigen/Core:526:0,
from /usr/local/include/eigen3/unsupported/Eigen/CXX11/Tensor:14,
from /home/drormeirovich/projects/tensorflow/third_party/eigen3/unsupported/Eigen/CXX11/Tensor:1,
from /home/drormeirovich/projects/tensorflow/tensorflow/core/framework/tensor.h:19,
from /home/drormeirovich/projects/tensorflow/tensorflow/cc/framework/ops.h:21,
from /home/drormeirovich/projects/tensorflow/tensorflow/cc/client/client_session.h:24,
from /home/drormeirovich/projects/my_project.cpp:10:
/usr/local/include/eigen3/unsupported/Eigen/CXX11/../../../Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h: In static member function ‘static void Eigen::internal::general_matrix_matrix_product<Index, double, LhsStorageOrder, ConjugateLhs, double, RhsStorageOrder, ConjugateRhs, 0>::run(Index, Index, Index, const double*, Index, const double*, Index, double*, Index, double, Eigen::internal::level3_blocking<double, double>&, Eigen::internal::GemmParallelInfo<Index>*)’:
/usr/local/include/eigen3/unsupported/Eigen/CXX11/../../../Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h:103:173: error: cannot convert ‘char*’ to ‘CBLAS_LAYOUT’ for argument ‘1’ to ‘void cblas_dgemm(CBLAS_LAYOUT, CBLAS_TRANSPOSE, CBLAS_TRANSPOSE, long long int, long long int, long long int, double, const double*, long long int, const double*, long long int, double, double*, long long int)’
BLASPREFIX##gemm(&transa, &transb, &m, &n, &k, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \
^
/usr/local/include/eigen3/unsupported/Eigen/CXX11/../../../Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h:106:1: note: in expansion of macro ‘GEMM_SPECIALIZATION’
GEMM_SPECIALIZATION(double, d, double, cblas_d)
^
有关更多详细信息...我在此集成问题上的全部进展都在此链接中:
https://docs.google.com/document/d/1VFTdPJy59QTCTHO8NHMNmnO8AOoQhNXgWixas9KmLLM/edit?usp=drivesdk
我是否必须从 Eigen3 中移除对 MKL 的支持?
任何帮助将不胜感激......
【问题讨论】:
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也许尝试更新版本的 TF?我上周在启用 MKL 的情况下成功地从头构建了一个版本 -- github.com/yaroslavvb/tensorflow-community-wheels/issues/21
-
我今天从github克隆了最新版本的tensorflow。我的编译问题在我自己的项目中(不是在 tensorflow 构建期间)
标签: c++ ubuntu tensorflow intel-mkl eigen3