}
}

static int GetChildren(const TF_Filesystem* filesystem, const char* path,
                       char*** entries, TF_Status* status) {
  struct dirent** dir_entries = nullptr;
  /* we don't promise entries would be sorted */
  int num_entries =
      scandir(path, &dir_entries, RemoveSpecialDirectoryEntries, nullptr);
  if (num_entries < 0) {
    TF_SetStatusFromIOError(status, errno, path);
  } else {

        `use_dynamic_shape` to enable dynamic shape support. The default is to
        disable dynamic shape support. Add `dynamic_shape_profile_strategy` for
        selecting a dynamic shape profile strategy. The default is profile
        strategy is `Range`.
    *   Issue a warning when function get_tensorrt_rewriter_config is used.

*   TF XLA

        "//tensorflow/c:tf_status",
        "//tensorflow/c/experimental/filesystem:filesystem_interface",
    ],
)

# Since building pip package and API tests require a filesystem, we provide a
# static registration target that they should link against.
cc_library(
    name = "posix_filesystem_static",
    srcs = ["posix_filesystem_static.cc"],
    visibility = ["//visibility:public"],
    deps = [

  Raises:
    UserInputError: if an environment variable is set, but it cannot be
      interpreted as a boolean indicator, assume that the user has made a
      scripting error, and will continue to provide invalid input.
      Raise the error to avoid infinitely looping.
  """
  if not question:
    question = 'Do you wish to build TensorFlow with {} support?'.format(
        query_item)
  if not yes_reply:

# Tensorflow to the default, however test coverage wasn't enough to catch the
# errors.
# There is ongoing work on Bazel team's side to provide support for transitive
# shared libraries. As part of migrating to transitive shared libraries, we
# hope to provide a better mechanism for control over symbol exporting, and
# then tackle this issue again.
#

// from the forward computation and calls a vector-jacobian product function
// (also known as adjoint function) to compute, given downstream gradients,
// upstream gradients.
//
// TODO(apassos) provide concrete template instantiations for TFE_TensorHandle
// specialization, which is blocked by quite a few things needing to loop back
// into python now.
template <typename Gradient, typename BackwardFunction, typename TapeTensor>