tensorflow::unwrap(tensor)->DebugString(),
                   " on to a parallel device. Pack non-parallel "
                   "tensors for each device into a parallel tensor explicitly.")
          .c_str());
  return nullptr;
}

// For TFE_CustomDevice::copy_tensor_from_device in the parallel device
// registration.
//
// Currently this is an error, and un-packing ParallelTensors must be performed

  vector<AbstractTensorHandle*> theta_inputs(inputs.size());
  for (int i{}; i < inputs.size(); ++i) {
    theta_inputs[i] = inputs[i];
  }

  AbstractTensorHandle* theta =
      theta_inputs[input_index];  // parameter we are grad checking

  // Convert from AbstractTensor to TF_Tensor.
  TF_Tensor* theta_tensor;
  TF_RETURN_IF_ERROR(GetValue(theta, &theta_tensor));

  TFE_DeleteOp(op);
  if (TF_GetCode(s) != TF_OK) return;
  std::vector<TFE_TensorHandle*> unwrapped_outputs;
  unwrapped_outputs.reserve(op_outputs.size());
  for (auto* handle : op_outputs) {
    unwrapped_outputs.push_back(handle);
  }
  for (int i = 0; i < *num_outputs; ++i) {
    auto logged_tensor = std::make_unique<LoggedTensor>(unwrapped_outputs[i]);
    outputs[i] = MakeLoggedTensorHandle(context, dev->device_name,

      /*set_stateful_from_nodes=*/true,
      /*copy_placeholder_attrs_from_nodes=*/true, body_nodes, input_tensors,
      output_tensors, output_names_vec, control_output_nodes,
      control_output_names_vec, description, &fdef);
  if (TF_GetCode(status) != TF_OK) {
    return nullptr;
  }

  // Dump the op creation stacktraces for debugging purpose.

  TFE_OpSetAttrType(op.get(), "dtype", type);
  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<std::string> summarized_devices = device_.SummarizeDeviceNames();
  for (int component_index = 0; component_index < tensors_.size();
       ++component_index) {
    // TODO(allenl): Add a C API for summarizing tensors. Currently custom
    // devices limiting themselves to a C API (for ABI compatibility) would need
    // to implement summarization for component tensors themselves.
    ImmediateExecutionTensorHandle* component =

    return nullptr;
  else
    return &tmp_dir;
}

namespace tensorflow {
namespace {

// TODO(vnvo2409): Refactor `gcs_filesystem_test` to remove unnecessary tests
// after porting all tests from
// `//tensorflow/core/platform/cloud:gcs_file_system_test`.
class GCSFilesystemTest : public ::testing::Test {
 public:
  void SetUp() override {
    root_dir_ = io::JoinPath(
        *GetTmpDir(),

  absl::Status cc_status;
  if (arg_tensor.dtype() != tensorflow::DT_RESOURCE) {
    cc_status = absl::InvalidArgumentError(
        absl::StrCat("Trying to obtain resource handle from Input[", index,
                     "], which is not type DT_RESOURCE."));
    status->status = cc_status;
    return nullptr;
  }
  const tensorflow::ResourceHandle& handle =

    ASSERT_TRUE(TF_GetCode(status.get()) == TF_INVALID_ARGUMENT)
        << TF_Message(status.get());
  }

  {
    // Try to extract the wrong number of components from a parallel tensor
    std::array<TFE_TensorHandle*, 1> correct_components{value_one.get()};
    TensorHandlePtr combined_value = CreatePerDeviceValues(
        context.get(), correct_components, device_name, status.get());

// If the flag is not used, no shared objects are loaded.
//
// Every filesystem provides support for accessing URIs of form
// `[<scheme>://]<path>` where `<scheme>` is optional (if missing, we are
// accessing local paths). This test suite tests exactly one scheme for each
// invocation. By default, we are testing all schemes available but this can be