// Rename local device
  // This server def has the task index set to 0.
  string serialized = server_def.SerializeAsString();
  TFE_ContextSetServerDef(ctx, 0, serialized.data(), serialized.size(), status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  const string dev1_name =
      absl::StrCat("/job:", first_name, "/replica:0/task:0/device:CPU:0");

      TFE_NewContext(opts.get(), status.get()), TFE_DeleteContext);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

  std::vector<std::string> devices{
      "/job:localhost/replica:0/task:0/device:CPU:0",
      "/job:localhost/replica:0/task:0/device:CPU:1"};
  ParallelDevice parallel_device(std::move(devices));

struct TF_AttrBuilder : public tensorflow::AttrBuilder {
  using tensorflow::AttrBuilder::AttrBuilder;
  // The string buffers to make sure that any `attr_name` we pass into
  // `builder->Set()` will outlive the subsequent
  // `TF_AttrBuilderCheckCanRunOnDevice()` call(s) on the same `builder`.
  std::set<std::string> attr_names;
};

TF_AttrBuilder* TF_NewAttrBuilder(const char* op_name) {
  return new TF_AttrBuilder(op_name);

#include <dirent.h>
#include <errno.h>
#include <fcntl.h>
#include <limits.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <sys/mman.h>
#include <sys/stat.h>
#include <unistd.h>

#include "tensorflow/c/experimental/filesystem/filesystem_interface.h"

  if (ret) ret = attr_value->ParseFromArray(buffer->data, buffer->length);
  TF_DeleteBuffer(buffer);
  return ret;
}

std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def) {
  std::vector<std::pair<string, string>> grads;
  for (const tensorflow::GradientDef& grad : graph_def.library().gradient()) {
    grads.emplace_back(grad.function_name(), grad.gradient_func());
  }

  *result = outputs[0];
  return absl::OkStatus();
}
}  // namespace

Status GradientRegistry::Register(
    const string& op_name, GradientFunctionFactory gradient_function_factory) {
  auto iter = registry_.find(op_name);
  if (iter != registry_.end()) {
    const string error_msg = "Gradient already exists for op: " + op_name + ".";
    return errors::AlreadyExists(error_msg);
  }

  TFE_OpReset(reused_op.get(), "Identity", custom_device_name, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  ASSERT_EQ(tensorflow::string(TFE_OpGetDevice(reused_op.get(), status.get())),
            tensorflow::string(custom_device_name));
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  TFE_OpReset(reused_op.get(), "Identity",

limitations under the License.
==============================================================================*/

#include "tensorflow/c/eager/dlpack.h"

#include <string>

#include "include/dlpack/dlpack.h"  // from @dlpack
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"

class NamedParallelDevice {
 public:
  NamedParallelDevice(const std::string& name,
                      std::unique_ptr<ParallelDevice> parallel_device)
      : device_name_(name), parallel_device_(std::move(parallel_device)) {}
  const std::string& name() const { return device_name_; }
  const ParallelDevice& device() const { return *parallel_device_; }

 private:
  std::string device_name_;
  std::unique_ptr<ParallelDevice> parallel_device_;
};

    std::random_device rd;
    std::mt19937 gen(rd());
    std::uniform_int_distribution<> distribution;
    std::string rng_val = std::to_string(distribution(gen));
    return tensorflow::io::JoinPath(std::string(test_dir), rng_val);
  } else {
    return "";
  }
}

static std::string* GetTmpDir() {
  static std::string tmp_dir = InitializeTmpDir();
  if (tmp_dir == "")
    return nullptr;
  else
    return &tmp_dir;
}