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: Updates variables using values pulled from a Reverb table.
  
  Args:
    variables: Nested structure of variables.
    table: The name of the table.
  
  Raises:
    KeyError: If the table name is not provided during construction time.
    ValueError: If the nested structure of the variable does not match the
      signature of the table. This includes structural differences (excluding
      the type differences of sequences in nest), and type differences.
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code: def update(
      self, variables: types.NestedVariable, table: Text = DEFAULT_TABLE
  ) -> None:
      """Updates variables using values pulled from a Reverb table.
  
      Args:
        variables: Nested structure of variables.
        table: The name of the table.
  
      Raises:
        KeyError: If the table name is not provided during construction time.
        ValueError: If the nested structure of the variable does not match the
          signature of the table. This includes structural differences (excluding
          the type differences of sequences in nest), and type differences.
      """
      self._assign(variables, self.pull(table))
  
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 4 for calling the ReverbVariableContainer obj's underlying member method code with example usage: obj.update(variables, table) without return types