// Create `worker_1` using single host server def `worker_1_server_def`.
  tensorflow::ServerDef worker_1_server_def =
      CreateSingleHostServerDef(cluster_server_def, 1);
  worker_1_server_def.set_task_index(1);
  worker_1_server_def.set_job_name("worker");

  std::unique_ptr<tensorflow::GrpcServer> worker_server1;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(worker_1_server_def,

  tensorflow::ServerDef server_def_0 = GetServerDef(3);
  server_def_0.mutable_default_session_config()->set_isolate_session_state(
      false);
  tensorflow::ServerDef server_def_1 =
      ReplaceTaskInServerDef(server_def_0, /*task_index=*/0);

  // These server defs have task index set to 0.
  string serialized_server_def_0 = server_def_0.SerializeAsString();

  tensorflow::mutex lock;
};

#if !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
struct TF_Server {
  TF_Server(std::unique_ptr<tensorflow::ServerInterface> server);

  const tensorflow::string target;
  std::unique_ptr<tensorflow::ServerInterface> server;
};
#endif  // !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)

namespace tensorflow {

  tensorflow::ServerDef server_def = GetServerDef("worker", 3);

  // This server def has the task index set to 0.
  std::string serialized = server_def.SerializeAsString();

  server_def.set_task_index(1);
  std::unique_ptr<tensorflow::GrpcServer> worker_server1;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(
                  server_def, tensorflow::Env::Default(), &worker_server1)
                  .ok());

# limitations under the License.
# ==============================================================================

setup_file() {
    bazel version  # Start the bazel server

    # Fixes "fatal: detected dubious ownership in repository" for Docker.
    git config --system --add safe.directory '*'
    git config --system protocol.file.allow always

        "//tensorflow/c/eager:c_api_experimental",
        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
        "//tensorflow/core/distributed_runtime/rpc:grpc_server_lib",
    ],

  // on cluster configurations provided in `server_def`; otherwise, update
  // existing context state with the provided `server_def`. Contexts created
  // on remote tasks will be considered stale and garbage collected after
  // `keep_alive_secs` of inactivity.
  virtual Status SetOrUpdateServerDef(const ServerDef& server_def,
                                      bool reset_context, int keep_alive_secs,

  tensorflow::ServerDef server_def = GetServerDef(3);

  // This server def has the task index set to 0.
  string serialized = server_def.SerializeAsString();

  server_def.set_task_index(1);
  std::unique_ptr<tensorflow::GrpcServer> worker_server1;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(
                  server_def, tensorflow::Env::Default(), &worker_server1)
                  .ok());

// TF_Server functions ----------------------------------------------

#if !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
TF_Server::TF_Server(std::unique_ptr<tensorflow::ServerInterface> server)
    : target(server->target()), server(std::move(server)) {}
#endif  // !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)

TF_Server* TF_NewServer(const void* proto, size_t proto_len,

read/write/executions.

### Running a TensorFlow server

TensorFlow is a platform for distributed computing, and as such there is a
TensorFlow server (`tf.train.Server`). The TensorFlow server is intended for
internal communication only. It is not built for use in untrusted environments
or networks.

For performance reasons, the default TensorFlow server does not include any