if err != nil {
			t.Fatalf("failed to parse user unique, got error %v", err)
		}

		constraints := user.ParseUniqueConstraints()
		if len(constraints) != 1 {
			t.Fatalf("failed to find unique constraint, got %v", constraints)
		}

		for key := range constraints {
			if len(key) != 63 {
				t.Errorf("failed to find unique constraint, got %v", constraints)
			}
		}
	})

class OpDeleter {
 public:
  void operator()(TFE_Op* to_delete) const { TFE_DeleteOp(to_delete); }
};

using OpPtr = std::unique_ptr<TFE_Op, OpDeleter>;

class StatusDeleter {
 public:
  void operator()(TF_Status* to_delete) const { TF_DeleteStatus(to_delete); }
};

using StatusPtr = std::unique_ptr<TF_Status, StatusDeleter>;

class ExecutorDeleter {
 public:
  void operator()(TFE_Executor* to_delete) const {

// register/use filesystems.

namespace tensorflow {

using UniquePtrTo_TF_Status =
    ::std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)>;

Status ModularFileSystem::NewRandomAccessFile(
    const std::string& fname, TransactionToken* token,
    std::unique_ptr<RandomAccessFile>* result) {
  if (ops_->new_random_access_file == nullptr)
    return errors::Unimplemented(tensorflow::strings::StrCat(

In this case you will have to ensure that each operation ID is **unique** in some other way.

For example, you could make sure that each *path operation* has a tag, and then generate the operation ID based on the **tag** and the *path operation* **name** (the function name).

### Custom Generate Unique ID Function

  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());
  ASSERT_TRUE(worker_server1->Start().ok());

  server_def.set_task_index(2);
  std::unique_ptr<tensorflow::GrpcServer> worker_server2;

        throw new IllegalArgumentException(
            "overflowed computing offset(" + origin + ", " + distance + ")");
      }
    }
    return current;
  }

  /**
   * Returns the unique least value of type {@code C} that is greater than {@code value}, or {@code
   * null} if none exists. Inverse operation to {@link #previous}.
   *
   * @param value any value of type {@code C}

	unique, ok := columnType.Unique()
	if !ok || field.PrimaryKey {
		return nil // skip primary key
	}
	// By default, ColumnType's Unique is not affected by UniqueIndex, so we don't care about UniqueIndex.
	return m.RunWithValue(value, func(stmt *gorm.Statement) error {
		// We're currently only receiving boolean values on `Unique` tag,
		// so the UniqueConstraint name is fixed

                            problems,
                            BuilderProblem.Severity.WARNING,
                            "servers.server.id",
                            null,
                            "must be unique but found duplicate server with id " + server.getId());
                }
            }
        }

        List<Mirror> mirrors = settings.getMirrors();

        if (mirrors != null) {

  server_def.set_job_name("worker");
  server_def.set_task_index(0);
  std::unique_ptr<tensorflow::ServerInterface> w0;
  ASSERT_TRUE(
      factory->NewServer(server_def, ServerFactory::Options(), &w0).ok());
  ASSERT_TRUE(w0->Start().ok());
  server_def.set_task_index(1);
  std::unique_ptr<tensorflow::ServerInterface> w1;
  ASSERT_TRUE(

   |-->
  <servers>
    <!-- server
     | Specifies the authentication information to use when connecting to a particular server, identified by
     | a unique name within the system (referred to by the 'id' attribute below).
     |
     | NOTE: You should either specify username/password OR privateKey/passphrase, since these pairings are
     |       used together.
     |