class_docstr: A dataset for listing snapshot chunk files.
  
  It supports listing partially written snapshots. When a snapshot is being
  written, it returns the currently available chunk files.
class_docstr_tok: ["A","dataset","for","listing","snapshot","chunk","files",".","It","supports","listing","partially","written","snapshots",".","When","a","snapshot","is","being","written",",","it","returns","the","currently","available","chunk","files","."]
code: def __init__(self, snapshot_path: str):
      self._snapshot_path = snapshot_path
      variant_tensor = ged_ops.list_snapshot_chunks_dataset(
          snapshot_path, **self._flat_structure
      )
      super().__init__(variant_tensor)
  
imports: import multiprocessing
  import os
  import time
  from typing import Optional
  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 _ListSnapshotChunksDataset object from inherited base classes: dataset_ops with example: obj = _ListSnapshotChunksDataset(snapshot_path)