for (int i = 0; i < noutputs; ++i) {
    output_names[i] = c_output_names[i];
  }
  std::vector<string> target_oper_names(ntargets);
  for (int i = 0; i < ntargets; ++i) {
    target_oper_names[i] = c_target_oper_names[i];
  }
  TF_Run_Helper(s->session, nullptr, run_options, input_pairs, output_names,
                c_outputs, target_oper_names, run_metadata, status);
}

void TF_PRunSetup(TF_DeprecatedSession* s,

}

TFE_TensorHandle* CopyTensorFromLoggingDevice(TFE_Context* context,
                                              TFE_TensorHandle* tensor,
                                              const char* target_device_name,
                                              TF_Status* status,
                                              void* device_info) {
  TF_SetStatus(status, TF_INTERNAL,

TFE_TensorHandle* CopyTensorFromParallelDevice(TFE_Context* context,
                                               TFE_TensorHandle* tensor,
                                               const char* target_device_name,
                                               TF_Status* status,
                                               void* device_info) {
  ParallelTensor* parallel_tensor = reinterpret_cast<ParallelTensor*>(

  // If target is a directory return TF_FAILED_PRECONDITION.
  // Target might be missing, so don't error in that case.
  struct stat st;
  if (stat(dst, &st) != 0) {
    if (errno != ENOENT) {
      TF_SetStatusFromIOError(status, errno, dst);
      return;
    }
  } else if (S_ISDIR(st.st_mode)) {
    TF_SetStatus(status, TF_FAILED_PRECONDITION, "target path is a directory");
    return;
  }

  if (op_reg_data->shape_inference_fn == nullptr) {
    status->status =
        InvalidArgument("No shape inference function exists for op '",
                        node_def.op(), "', did you forget to define it?");
    return;
  }

  status->status = c.Run(op_reg_data->shape_inference_fn);
  if (!status->status.ok()) return;

  // Set output_shapes.
  TF_ShapeAndTypeList* output_shapes_result =

  std::string translated_target = TranslateName(target);
  ops_->rename_file(filesystem_.get(), translated_src.c_str(),
                    translated_target.c_str(), plugin_status.get());
  return StatusFromTF_Status(plugin_status.get());
}

Status ModularFileSystem::CopyFile(const std::string& src,
                                   const std::string& target,

  Status status = env_->CreateDir(dirpath);
  if (!status.ok()) GTEST_SKIP() << "CreateDir() not supported: " << status;

  const std::string target_path = GetURIForPath("a_dir/another_dir");
  EXPECT_EQ(env_->CreateDir(target_path).code(), Code::OK);

  status = env_->DeleteDir(target_path);
  EXPECT_PRED2(UnimplementedOrReturnsCode, status, Code::OK);
}

TEST_P(ModularFileSystemTest, TestDeleteDirectoryDoesNotExist) {

  TF_Output fetches[] = {dxy_dx, dxy_dy};
  TF_Tensor* fetchValues[] = {nullptr, nullptr};

  TF_SessionRun(sess, nullptr /* run_options */, feeds, feedValues, 2, fetches,
                fetchValues, 2, nullptr /* target_opers */, 0,
                nullptr /* run_metadata */, s_);
  TF_DeleteTensor(feedValues[0]);
  TF_DeleteTensor(feedValues[1]);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  TF_DeleteSession(sess, s_);

    if (sources_set.find(target_id) != sources_set.end()) {
      auto tensor = targets[i];
      sources_that_are_targets.insert(
          std::make_pair(target_id, TapeTensor(tensor)));
    }
  }

  TF_RETURN_IF_ERROR(GradientTape::ComputeGradient(
      vspace, target_tensor_ids, source_tensor_ids, sources_that_are_targets,
      output_gradients, result, /*build_default_zeros_grads*/ false));

      ImmediateExecutionTensorHandle* handle,
      const tensorflow::string& target_device_name,
      ImmediateExecutionTensorHandle** result) override {
    TF_Status status;
    handle->Ref();
    TFE_TensorHandle* result_handle = device_.copy_tensor_from_device(
        context_, tensorflow::wrap(handle), target_device_name.c_str(), &status,
        info_);
    handle->Unref();