def set_tf_cuda_version(environ_cp):
  """Set TF_CUDA_VERSION."""
  ask_cuda_version = (
      'Please specify the CUDA SDK version you want to use. '
      '[Leave empty to default to CUDA %s]: ') % _DEFAULT_CUDA_VERSION
  tf_cuda_version = get_from_env_or_user_or_default(environ_cp,
                                                    'TF_CUDA_VERSION',

build:mkl_aarch64_threadpool -c opt

# CUDA: This config refers to building CUDA op kernels with nvcc.
build:cuda --repo_env TF_NEED_CUDA=1
build:cuda --crosstool_top=@local_config_cuda//crosstool:toolchain
build:cuda --@local_config_cuda//:enable_cuda

# CUDA: This config refers to building CUDA op kernels with clang.
build:cuda_clang --config=cuda
# Enable TensorRT optimizations https://developer.nvidia.com/tensorrt

*   Move `layers_dense_variational_impl.py` to `layers_dense_variational.py`.

## Known Bugs

*   Using XLA:GPU with CUDA 9 and CUDA 9.1 results in garbage results and/or
    `CUDA_ILLEGAL_ADDRESS` failures.

    Google discovered in mid-December 2017 that the PTX-to-SASS compiler in CUDA
    9 and CUDA 9.1 sometimes does not properly compute the carry bit when

  TF_DeleteTensor(t);
  EXPECT_TRUE(deallocator_called);
}

TEST(CAPI, LibraryLoadFunctions) {
  // TODO(b/73318067): Fix linking for the GPU test generated by the
  // tf_cuda_cc_test() bazel rule and remove the next line.
  if (!GPUDeviceName().empty()) return;

#if !defined(TENSORFLOW_NO_SHARED_OBJECTS)
  {
    // Load the library.
    TF_Status* status = TF_NewStatus();

github.com/pkg/xattr
https://github.com/pkg/xattr
----------------------------------------------------------------
Copyright (c) 2012 Dave Cheney. All rights reserved.
Copyright (c) 2014 Kuba Podgórski. All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met: