class_docstr: Base class for Datasets.
docstr: Load dataset from HDF5 file at filepath.
  
  Args:
      source: Dataset, or path to HDF5 file containing dataset, from which
          to read attributes
      attributes: Optional list of attributes to copy. If None, all attributes
          will be copied.
      overwrite: Whether to overwrite attributes that already exist in this
          dataset.
docstr_tok: ["Load","dataset","from","HDF5","file","at","filepath",".","Args",":","source",":","Dataset",",","or","path","to","HDF5","file","containing","dataset",",","from","which","to","read","attributes","attributes",":","Optional","list","of","attributes","to","copy",".","If","None",",","all","attributes","will","be","copied",".","overwrite",":","Whether","to","overwrite","attributes","that","already","exist","in","this","dataset","."]
code: def read(
      self,
      source: Union[str, Path, "Dataset"],
      attributes: Optional[typing.Iterable[str]] = None,
      *,
      overwrite: bool = False,
  ) -> None:
      """Load dataset from HDF5 file at filepath.
  
      Args:
          source: Dataset, or path to HDF5 file containing dataset, from which
              to read attributes
          attributes: Optional list of attributes to copy. If None, all attributes
              will be copied.
          overwrite: Whether to overwrite attributes that already exist in this
              dataset.
      """
      if not isinstance(source, Dataset):
          source = Path(source).expanduser()
          source = Dataset.open(source, mode="r")
  
      source.write(self, attributes=attributes, overwrite=overwrite)
  
      source.close()
  
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 11 for calling the Dataset obj's underlying member method code with example usage: obj.read(source, attributes) without return types