const std::string& fname, TransactionToken* token,
    std::unique_ptr<RandomAccessFile>* result) {
  if (ops_->new_random_access_file == nullptr)
    return errors::Unimplemented(tensorflow::strings::StrCat(
        "Filesystem for ", fname, " does not support NewRandomAccessFile()"));

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  auto file = std::make_unique<TF_RandomAccessFile>();

    if (BlockNotStale(entry->second)) {
      return entry->second;
    } else {
      // Remove the stale block and continue.
      RemoveFile_Locked(key.first);
    }
  }

  // Insert a new empty block, setting the bookkeeping to sentinel values
  // in order to update them as appropriate.
  auto new_entry = std::make_shared<Block>();
  lru_list_.push_front(key);
  lra_list_.push_front(key);

  auto client_job = cluster->add_job();
  client_job->set_name("localhost");
  int client_port = tensorflow::testing::PickUnusedPortOrDie();
  client_job->mutable_tasks()->insert(
      {0, strings::StrCat("localhost:", client_port)});
  server_def.set_job_name("localhost");
  auto serialized = server_def.SerializeAsString();
  TFE_ContextSetServerDef(ctx, 0, serialized.data(), serialized.size(), status);

//     core and the plugin.
//     * For example, `TF_InitGraph` function receives
//       `TP_OptimizerRegistrationParams*` as input with `struct_size`
//       populated by core. The plugin is responsible for setting
//       `struct_size` as well, along with all other fields.
//     * Refer to "TensorFlow Versioning Strategy" section at
//       https://github.com/tensorflow/community/pull/257/files.

// A tensorflow.ServerDef specifies remote workers (in addition to the current
// workers name). Operations created in this context can then be executed on
// any of these remote workers by setting an appropriate device.
//
// If the following is set, all servers identified by the
// ServerDef must be up when the context is created.
TF_CAPI_EXPORT extern void TFE_ContextSetServerDef(TFE_Context* ctx,

limitations under the License.
==============================================================================*/
#include "tensorflow/c/eager/gradients.h"

#include "absl/strings/str_cat.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/eager/gradients_internal.h"

                                                    TF_Status* status);

// Get configuration key and value using coordination service.
// The config key must be set before getting its value. Getting value of
// non-existing config keys will result in errors.
// If `timeout_in_ms=0`, this call will block until the key-value is set or the
// worker shuts down.

            "//tensorflow/core/config:flags",
            "//tensorflow/core/distributed_runtime:server_lib",
            "//tensorflow/core/kernels:logging_ops",
            "@com_google_absl//absl/strings",
        ],
    }),
    alwayslink = 1,
)

cc_library(
    name = "logging",
    srcs = ["logging.cc"],
    hdrs = ["logging.h"],
    visibility = ["//visibility:public"],
    deps = [

just getting started, GitHub has a
[how-to](https://help.github.com/articles/using-pull-requests/).

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are

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

// A simple logging device to test custom device registration.
#include <memory>

#include "absl/strings/match.h"
#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/c_api_test_util.h"