var _Op_index = [...]uint8{0, 7, 22, 26, 30, 40, 55, 74, 93, 105, 117, 130, 142, 148, 155, 163, 173, 179}

func (i Op) String() string {
	i -= 1
	if i >= Op(len(_Op_index)-1) {
		return "Op(" + strconv.FormatInt(int64(i+1), 10) + ")"
	}
	return _Op_name[_Op_index[i]:_Op_index[i+1]]

	if i >= TargetType(len(_TargetType_index)-1) {
		return "TargetType(" + strconv.FormatInt(int64(i+1), 10) + ")"
	}
	return _TargetType_name[_TargetType_index[i]:_TargetType_index[i+1]]

var _scannerMetric_index = [...]uint8{0, 12, 24, 33, 41, 53, 65, 74, 77, 93, 98, 112, 127, 147, 157, 167, 186, 198, 208, 217, 232, 245, 249}

func (i scannerMetric) String() string {
	if i >= scannerMetric(len(_scannerMetric_index)-1) {
		return "scannerMetric(" + strconv.FormatInt(int64(i), 10) + ")"
	}
	return _scannerMetric_name[_scannerMetric_index[i]:_scannerMetric_index[i+1]]

func (i HandlerID) String() string {
	if i >= HandlerID(len(_HandlerID_index)-1) {
		return "HandlerID(" + strconv.FormatInt(int64(i), 10) + ")"
	}
	return _HandlerID_name[_HandlerID_index[i]:_HandlerID_index[i+1]]

      TFE_NewContext(opts.get(), status.get()), TFE_DeleteContext);
  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(

import static com.google.common.collect.testing.features.CollectionSize.ZERO;
import static com.google.common.collect.testing.features.ListFeature.SUPPORTS_ADD_WITH_INDEX;
import static com.google.common.collect.testing.features.ListFeature.SUPPORTS_REMOVE_WITH_INDEX;
import static com.google.common.collect.testing.features.ListFeature.SUPPORTS_SET;
import static java.util.Collections.emptyList;

namespace tensorflow {
namespace gradients {

/* Returns numerical grad inside `dtheta_approx` given `forward` model and
 * parameter specified by `input_index`.
 *
 * I.e. if y = <output of the forward model> and w = inputs[input_index],
 * this will calculate dy/dw numerically.
 *
 * `use_function` indicates whether to use graph mode(true) or eager(false).
 *

{"index":{"_index":"fess_user.role","_id":"YWRtaW4="}}
{"name":"admin"}
{"index":{"_index":"fess_user.role","_id":"Z3Vlc3Q="}}

  // 3. Replace worker1 with a new worker in server_def_0 and server_def_1.
  ReplaceTaskInServerDef(&server_def_0, /*task_index=*/1, "localhost", port);
  ReplaceTaskInServerDef(&server_def_1, /*task_index=*/1, "localhost", port);
  // 4. Start a new task to replace worker1.
  server_def_0.set_task_index(1);
  worker_server1.release();
  ASSERT_TRUE(tensorflow::GrpcServer::Create(

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