class_docstr: Adaptive version of the `EncodingStageInterface`.
  
  This class has the same functionality as the `EncodingStageInterface`, but in
  addition maintains a state, which is adaptive based on the values being
  compressed and can parameterize the way encoding functionality works. Note
  that this is useful only in case where the encoding is executed in multiple
  iterations.
  
  A typical implementation of this interface would be a wrapper of an
  implementation of `EncodingStageInterface, which uses the existing stateless
  transformations and adds state that controls some of the parameters returned
  by the `get_params` method.
  
  The important distinction is that in addition to `encoded_tensors`, the
  `encode` method of this class returns an additional dictionary of
  `state_update_tensors`. The `commutes_with_sum` property talks about summation
  of only the `encoded_tensors`. The `state_update_tensors` can be aggregated
  in more flexible ways, specified by the `state_update_aggregation_modes`
  property, before being passed to the `update_state` method.
  
  Each implementation should also be wrapped by `tf_style_encoding_stage` to
  ensure adherence to the TensorFlow style guide. The adherence is enforced by
  the `BaseEncodingStageTest` test class. See `test_utils.py` for more details.
docstr: Updates the state.
  
  This method updates the `state` based on the current value of `state`, and
  (potentially aggregated) `state_update_tesors`, returned by the `encode`
  method. This will typically happen at the end of a notion of iteration.
  
  Args:
    state: A dictionary of `Tensor` objects, representing the current state.
      The dictionary has the same structure as return dictionary of the
      `initial_state` method.
    state_update_tensors: A dictionary of `Tensor` objects, representing the
      `state_update_tensors` returned by the `encode` method and appropriately
      aggregated.
  
  Returns:
    A dictionary of `Tensor` objects, representing the updated `state`.
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code: def update_state(self, state, state_update_tensors):
      """Updates the state.
  
      This method updates the `state` based on the current value of `state`, and
      (potentially aggregated) `state_update_tesors`, returned by the `encode`
      method. This will typically happen at the end of a notion of iteration.
  
      Args:
        state: A dictionary of `Tensor` objects, representing the current state.
          The dictionary has the same structure as return dictionary of the
          `initial_state` method.
        state_update_tensors: A dictionary of `Tensor` objects, representing the
          `state_update_tensors` returned by the `encode` method and appropriately
          aggregated.
  
      Returns:
        A dictionary of `Tensor` objects, representing the updated `state`.
      """
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import enum
  import six
  import tensorflow
label_desc: Use image node_id 7 for calling the AdaptiveEncodingStageInterface obj's underlying member method code with example usage: obj.update_state(state, state_update_tensors) without return types