Building TF 1.13.1 from source

Hi

I see that NVIDIA provides us with Tensorflow v1.13.1 binary wheel installers, but can it be built from source? I keep running into errors in 1.13.1 (fine in r1.12). What are the steps for building from source in 1.13.1? Without building from source, examples like label_image.cc can’t be run.

Thanks

Hi,

Could you share the error you meet with us?
In general, you should be able to build TensorFlow with the similar steps of this topic:
https://devtalk.nvidia.com/default/topic/1049100/general/tensorflow-installation-on-drive-px2-/post/5324624/#5324624

Thanks.

Sure. I keep getting the following error:

Execution platform: @bazel_tools//platforms:host_platform
In file included from external/eigen_archive/unsupported/Eigen/CXX11/../../../Eigen/Core:296:0,
                 from external/eigen_archive/unsupported/Eigen/CXX11/Tensor:14,
                 from ./third_party/eigen3/unsupported/Eigen/CXX11/Tensor:1,
                 from ./tensorflow/contrib/rnn/kernels/lstm_ops.h:19,
                 from tensorflow/contrib/rnn/kernels/lstm_ops.cc:22:
external/eigen_archive/unsupported/Eigen/CXX11/../../../Eigen/src/Core/products/GeneralBlockPanelKernel.h: In member function 'void Eigen::internal::gebp_kernel<LhsScalar, RhsScalar, Index, DataMapper, mr, nr, ConjugateLhs, ConjugateRhs>::operator()(const DataMapper&, const LhsScalar*, const RhsScalar*, Index, Index, Index, Eigen::internal::gebp_kernel<LhsScalar, RhsScalar, Index, DataMapper, mr, nr, ConjugateLhs, ConjugateRhs>::ResScalar, Index, Index, Index, Index) [with LhsScalar = Eigen::half; RhsScalar = Eigen::half; Index = long int; DataMapper = Eigen::internal::blas_data_mapper<Eigen::half, long int, 0, 0>; int mr = 2; int nr = 4; bool ConjugateLhs = false; bool ConjugateRhs = false]':
external/eigen_archive/unsupported/Eigen/CXX11/../../../Eigen/src/Core/products/GeneralBlockPanelKernel.h:1879:3: internal compiler error: in emit_move_insn, at expr.c:3698
   }
   ^
Please submit a full bug report,
with preprocessed source if appropriate.

I’m using bazel 0.21.0.

Hi,

This is a TensorFlow issue with gcc7.3.1:
https://github.com/tensorflow/tensorflow/issues/25323

It’s recommended to check with TensorFlower for a possible workaround first.
Thanks.