class_docstr: Distributed in memory tf.Variable store based on Reverb.
  
  This is just a client. The server needs to be consructed and held separately.
  
  **Note:** The container stores nests of variables in dedicated tables in a
  Reverb server. It is assumed that the server is running, the tables for
  variable container exist and are configured properly (i.e. it have signature
  defined and the `max_size=1`).
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docstr: Pulls values from a Reverb table and returns them as nested tensors.
docstr_tok: ["Pulls","values","from","a","Reverb","table","and","returns","them","as","nested","tensors","."]
code: def pull(self, table: Text = DEFAULT_TABLE) -> types.NestedTensor:
      """Pulls values from a Reverb table and returns them as nested tensors."""
      sample = self._tf_client.sample(
          table, data_dtypes=[self._dtypes[table]]
      )
      # The data is received in the form of a sequence. In the case of variable
      # container the sequence length is always one.
      return sample.data[0]
  
file_path: agents/tf_agents/experimental/distributed/reverb_variable_container.py
imports: from typing import Iterable, Text
  import tensorflow
  from tf_agents.typing import types
  from tf_agents.utils import common
  from tf_agents.utils import lazy_loader
  from tf_agents.utils import nest_utils
label_desc: Use image node_id 3 for calling the ReverbVariableContainer obj's underlying member method code with example usage: obj.pull(table) and returns: sample