absl::Span<AbstractTensorHandle*> grad_inputs) override {
    /* Given upstream grad U and a BiasAdd: A + bias, the gradients are:
     *
     *    dA = U
     *    dbias = reduceSum(U, dims = channel_dim)
     */

    AbstractTensorHandle* upstream_grad = grad_outputs[0];
    DCHECK(upstream_grad);

    // Recover data format from forward pass for gradient.
    std::string data_format;

#include <stdio.h>

#include <fstream>
#include <string>
#include <utility>

TempFile::TempFile(const std::string& temp_file_name, std::ios::openmode mode)
    : std::fstream(temp_file_name, mode), name_(temp_file_name) {}

TempFile::TempFile(TempFile&& rhs)
    : std::fstream(std::move(rhs)), name_(std::move(rhs.name_)) {}

TempFile::~TempFile() {
  std::fstream::close();
  std::remove(name_.c_str());
}

    RunMetadata run_metadata_proto;
    result = session->Run(run_options_proto, input_pairs, output_tensor_names,
                          target_oper_names, &outputs, &run_metadata_proto);

    // Serialize back to upstream client, who now owns the new buffer
    if (run_metadata != nullptr) {
      status->status = MessageToBuffer(run_metadata_proto, run_metadata);
      if (!status->status.ok()) return;
    }
  } else {

==============================================================================*/
#include "tensorflow/c/experimental/filesystem/plugins/gcs/ram_file_block_cache.h"

#include <cstring>
#include <memory>
#include <sstream>
#include <utility>

#include "absl/synchronization/mutex.h"
#include "tensorflow/c/experimental/filesystem/plugins/gcs/cleanup.h"

namespace tf_gcs_filesystem {

    /* Given upstream grad U and a mul op A*B, the gradients are:
     *
     *    dA = U * B
     *    dB = A * U
     *
     */

    AbstractTensorHandle* upstream_grad = grad_outputs[0];

    // Gradient for A
    std::string name = "Mul_Grad_A";
    TF_RETURN_IF_ERROR(Mul(ctx, upstream_grad, forward_inputs_[1],

  if (TF_GetCode(status) != TF_OK) return -1;
  auto stream = gcs_file->gcs_client.ReadObject(
      bucket, object, gcs::ReadRange(offset, offset + buffer_size));
  TF_SetStatusFromGCSStatus(stream.status(), status);
  if ((TF_GetCode(status) != TF_OK) &&
      (TF_GetCode(status) != TF_OUT_OF_RANGE)) {
    return -1;
  }
  int64_t read;
  auto content_length = stream.headers().find("content-length");

  // Load the library.
  TF_Status* status = TF_NewStatus();
  string lib_path =
      tensorflow::GetDataDependencyFilepath(tensorflow::io::JoinPath(
          "tensorflow", "c", "experimental", "stream_executor", "test",
          "test_pluggable_device.so"));
  TF_Library* lib = TF_LoadPluggableDeviceLibrary(lib_path.c_str(), status);
  TF_Code code = TF_GetCode(status);
  string status_msg(TF_Message(status));