class_docstr: A dataset for one chunk file from a tf.data distributed snapshot.
class_docstr_tok: ["A","dataset","for","one","chunk","file","from","a","tf.data","distributed","snapshot","."]
code: def __init__(
      self, chunk_file: str, element_spec: Any, compression: str
  ):
      self._chunk_file = chunk_file
      self._element_spec = element_spec
      variant_tensor = ged_ops.snapshot_chunk_dataset(
          chunk_file, compression=compression, **self._flat_structure
      )
      super().__init__(variant_tensor)
  
imports: import multiprocessing
  import os
  import time
  from typing import Any, Callable, Optional, Union
  from absl import logging
  from google.protobuf import message
  from google.protobuf import text_format
  from tensorflow.core.protobuf import snapshot_pb2
  from tensorflow.python.data.experimental.service import _pywrap_snapshot_utils
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import structured_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.ops import gen_experimental_dataset_ops
  from tensorflow.python.platform import gfile
  from tensorflow.python.saved_model import nested_structure_coder
label_desc: Use image node_id 1 to create a new _SnapshotChunkDataset object from inherited base classes: dataset_ops with example: obj = _SnapshotChunkDataset(chunk_file, element_spec, compression)