TFE_OpSetAttrShape(op.get(), "shape", dims, num_dims, status);
  TFE_OpSetAttrString(op.get(), "container", "", 0);
  // Use the special GUID for no buffer sharing
  //
  // TODO(allenl): Should we provide a better API for this? AFAIK this is the
  // only reasonable way to make variables with no aliasing using the eager C
  // API.
  std::string no_sharing = "cd2c89b7-88b7-44c8-ad83-06c2a9158347";

    std::vector<TensorHandlePtr> components, absl::Span<const int64_t> shape,
    TF_Status* status) {
  if (components.empty()) {
    TF_SetStatus(status, TF_INTERNAL,
                 "No components are provide for creating a ParallelTensor");
    return nullptr;
  }
  TFE_TensorHandleGetStatus(components[0].get(), status);
  if (!status->status.ok()) {
    return nullptr;
  }

// Initialize the POSIX filesystem.
//
// In general, the `TF_InitPlugin` symbol doesn't need to be exposed in a header
// file, since the plugin registration will look for the symbol in the DSO file
// that provides the filesystem functionality. However, the POSIX filesystem
// needs to be statically registered in some tests and utilities for building
// the API files at the time of creating the pip package. Hence, we need to

# limitations under the License.
#
# ==============================================================================
#
# Repacks libtensorflow tarballs into $DIR with provided $TARBALL_SUFFIX,
# and also repacks libtensorflow-src.jar into a standardized format.

# Helper function to copy a srcjar after moving any source files
# directly under the root to the "maven-style" src/main/java layout
#

setup_file() {
    bazel version  # Start the bazel server
}

# Do a bazel query specifically for the licenses checker. It searches for
# targets matching the provided query, which start with // or @ but not
# //tensorflow (so it looks for //third_party, //external, etc.), and then
# gathers the list of all packages (i.e. directories) which contain those
# targets.
license_query() {

  EXPECT_NE(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Even after the prevoiusly failed cluster update, another update and op
  // execution should work fine as long as the provided server_def is valid.
  TFE_ContextUpdateServerDef(ctx, 0, serialized.data(), serialized.size(),
                             status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  }
}

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 {

  // A vector to keep track of newly created `tf::Tensor` objects.
  std::vector<Tensor> all_input_tensors;
  // Update the vector with information from `input_tensors` if provided.
  if (input_tensors != nullptr) {
    // Note that we take the address of the elements in `all_input_tensors`
    // below. Allocate enough space so that no reallocation happens, which will
    // make the pointers invalid.

// * int is used as an index into arrays.
// * Deletion functions are safe to call on nullptr.
//
// Questions left to address:
// * Might at some point need a way for callers to provide their own Env.
// * Maybe add TF_TensorShape that encapsulates dimension info.
//
// Design decisions made:
// * Backing store for tensor memory has an associated deallocation

                      {x.get()}, absl::MakeSpan(outputs),
                      /*use_function=*/!std::get<2>(GetParam()));
  ASSERT_EQ(error::INVALID_ARGUMENT, s.code());
  ASSERT_EQ(
      "Provided null gradient_function for 'Neg'.\nIf the intent is to treat "
      "this op as non-differentiable consider using RegisterNotDifferentiable "
      "or NotDifferentiableGradientFunction.",
      s.message());