"//tensorflow/core:test_main",
    ],
)

tf_cc_test(
    name = "parallel_device_remote_test",
    srcs = ["parallel_device_remote_test.cc"],
    # TODO(b/136478427): Enable global heap checking when servers shut down
    # cleanly.
    args = ["--heap_check="],
    deps = [
        ":parallel_device",
        ":parallel_device_testlib",
        "//tensorflow/c:c_api",
        "//tensorflow/c:c_api_experimental",

  string serialized_server_def_0 = server_def_0.SerializeAsString();
  string serialized_server_def_1 = server_def_1.SerializeAsString();

  // Create two worker tasks.
  server_def_0.set_task_index(1);
  std::unique_ptr<tensorflow::GrpcServer> worker_server1;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(
                  server_def_0, tensorflow::Env::Default(), &worker_server1)
                  .ok());

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

// -----------------------------------------------------------------------------
// Dynamic cluster API.

// Update an existing context with a new set of servers defined in a ServerDef
// proto. Servers can be added to and removed from the list of remote workers
// in the context. A New set of servers identified by the ServerDef must be up
// when the context is updated.
//
// This API is for experimental usage and may be subject to change.

  // Create two worker tasks.
  server_def_0.set_task_index(1);
  std::unique_ptr<tensorflow::GrpcServer> worker_server1;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(
                  server_def_0, tensorflow::Env::Default(), &worker_server1)
                  .ok());
  ASSERT_TRUE(worker_server1->Start().ok());
  server_def_0.set_task_index(2);
  std::unique_ptr<tensorflow::GrpcServer> worker_server2;

// 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,
                                                   int keep_alive_secs,

  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 {

# 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::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());

  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());