class_docstr: Reverb ReplayBuffer exposed as a TF-Agents replay buffer.
class_docstr_tok: ["Reverb","ReplayBuffer","exposed","as","a","TF-Agents","replay","buffer","."]
docstr: Returns the number of frames in the replay buffer.
  
  **Note:** This might return inconsistent result if there are pending
  reads/writes are running on the particular table in parallel on the Reverb
  server side.
  
  Returns:
    The number of observations stored in `self._table_name` table of the
    Reverb server.
docstr_tok: ["Returns","the","number","of","frames","in","the","replay","buffer",".","*","*","Note",":","*","*","This","might","return","inconsistent","result","if","there","are","pending","reads\/writes","are","running","on","the","particular","table","in","parallel","on","the","Reverb","server","side",".","Returns",":","The","number","of","observations","stored","in","`","self._table_name","`","table","of","the","Reverb","server","."]
code: def _num_frames(self):
      """Returns the number of frames in the replay buffer.
  
      **Note:** This might return inconsistent result if there are pending
      reads/writes are running on the particular table in parallel on the Reverb
      server side.
  
      Returns:
        The number of observations stored in `self._table_name` table of the
        Reverb server.
      """
      return self.get_table_info().current_size
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import gin
  import tensorflow.compat.v2
  from tf_agents.replay_buffers import replay_buffer
  from tf_agents.typing import types
  from tf_agents.utils import lazy_loader
label_desc: Use image node_id 6 for calling the ReverbReplayBuffer obj's underlying member method code with example usage: obj._num_frames() and returns: self