class_docstr: Abstract base class for TF-Agents replay buffer.
  
  In eager mode, methods modify the buffer or return values directly. In graph
  mode, methods return ops that do so when executed.
class_docstr_tok: ["Abstract","base","class","for","TF-Agents","replay","buffer",".","In","eager","mode",",","methods","modify","the","buffer","or","return","values","directly",".","In","graph","mode",",","methods","return","ops","that","do","so","when","executed","."]
docstr: Creates and returns a dataset that returns entries from the buffer.
docstr_tok: ["Creates","and","returns","a","dataset","that","returns","entries","from","the","buffer","."]
code: def _as_dataset(
      self,
      sample_batch_size,
      num_steps,
      sequence_preprocess_fn,
      num_parallel_calls,
  ):
      """Creates and returns a dataset that returns entries from the buffer."""
      raise NotImplementedError
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import tensorflow
  from tf_agents.utils import common
  from tensorflow.python.data.util import nest
  from tensorflow.python.util import deprecation
label_desc: Use image node_id 14 for calling the ReplayBuffer obj's underlying member method code with example usage: obj._as_dataset(sample_batch_size, num_steps, sequence_preprocess_fn, num_parallel_calls) without return types