// Fetch and see that the new value is returned.
  TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, num_dims, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(dims[0], returned_dims[0]);
  EXPECT_EQ(dims[1], returned_dims[1]);

  // Try to set 'unknown' with unknown rank on the shape and see that
  // it doesn't change.

  const std::string new_dirpath = GetURIForPath("parent/path/that/is/extended");
  status = env_->RecursivelyCreateDir(new_dirpath);
  if (!status.ok())
    GTEST_SKIP() << "RecursivelyCreateDir() not supported: " << status;

  const std::string path = GetURIForPath("parent/path/that");
  int64_t undeleted_files = 0;
  int64_t undeleted_dirs = 0;

    if (TF_GetCode(status.get()) != TF_OK) {
      ADD_FAILURE() << tag << " -- " << TF_Message(status.get());
      continue;
    }
    TFE_DeleteTensorHandle(hdevice2);

    // Ensure that the contents are the same!
    TF_Tensor* tcopy = TFE_TensorHandleResolve(hcopy, status.get());
    TFE_DeleteTensorHandle(hcopy);
    if (TF_GetCode(status.get()) != TF_OK) {
      ADD_FAILURE() << tag;
      continue;

# unsupported flags to replace the release flags in your build command.
# However, please note that the old toolchain is no longer officially supported
# by TensorFlow and the unsupported configs will be removed soon b/299962977. We
# strongly recommend that you migrate to Clang as your compiler for TensorFlow
# Linux builds. Instructions are available in the official documentation:

///
/// The following data structures incorporate a `void*` that is opaque to
/// TensorFlow but can be used by each filesystem plugin to represent internal
/// data.
///
/// We prefer to have these structures instead of passing `void*` into
/// method signatures to have some type of type safety: for example, operations
/// that are only valid on random access files have a `TF_RandomAccessFile`
/// argument.
///

  elif is_windows():
    default_cc_opt_flags = '/arch:AVX'
  else:
    # On all other platforms, no longer use `-march=native` as this can result
    # in instructions that are too modern being generated. Users that want
    # maximum performance should compile TF in their environment and can pass
    # `-march=native` there.
    # See https://github.com/tensorflow/tensorflow/issues/45744 and duplicates

alias(
    name = "is_cuda_compiler_clang",
    actual = if_oss(
        "@local_config_cuda//:is_cuda_compiler_clang",
        "@local_config_cuda//cuda:TRUE",
    ),
)

# Config setting that is satisfied when CUDA device code should be compiled
# with nvcc. It does not imply that CUDA support has been enabled.
alias(
    name = "is_cuda_compiler_nvcc",

  }

  // Verify that stack traces of func is copied to graph function library.
  ASSERT_NE(func_stack_traces, nullptr);
  EXPECT_EQ(func_stack_traces->size(), 4);
  EXPECT_EQ(func_stack_traces->at("neg")->ToString({}), kNegStackToString);
  EXPECT_EQ(func_stack_traces->at("feed")->ToString({}), kFeedStackToString);

  // Verify that stack traces of grad_func is copied to graph function library.

// Get the number of operations that have `*oper` as a control input.
// Note that this number can change when new operations are added to
// the graph.
TF_CAPI_EXPORT extern int TF_OperationNumControlOutputs(TF_Operation* oper);

// Get the list of operations that have `*oper` as a control input.
// `control_outputs` must point to an array of length at least