class_docstr: Base class for Datasets.
code: def _init_bind(
      self,
      data_name: Optional[str] = None,
      identifiers: Optional[Tuple[str, ...]] = None,
  ):
      if self.bind.file.mode == "r+":
          if "type_id" not in self.info:
              self.info["type_id"] = self.type_id
          if "data_name" not in self.info:
              self.info["data_name"] = data_name or self.__data_name__
          if "identifiers" not in self.info:
              self.info["identifiers"] = (
                  identifiers or self.__identifiers__
              )
  
imports: import typing
  from dataclasses import dataclass
  from pathlib import Path
  from types import MappingProxyType
  from typing import Any, ClassVar, Generic, List, Literal, Optional, Tuple, Type, TypeVar, Union, cast, get_origin
  from typing_extensions import dataclass_transform
  from pennylane.data.base import hdf5
  from pennylane.data.base.attribute import AttributeInfo, DatasetAttribute
  from pennylane.data.base.hdf5 import HDF5Any, HDF5Group, h5py
  from pennylane.data.base.mapper import MapperMixin, match_obj_type
  from pennylane.data.base.typing_util import UNSET, T
label_desc: Use image node_id 13 for calling the Dataset obj's underlying member method code with example usage: obj._init_bind(data_name, identifiers) without return types