class_docstr: Wraps a Keras RNN/LSTM/GRU layer to make network state more consistent.
code: def from_config(cls, config, custom_objects=None):
      internal_layer = tf.keras.layers.deserialize(
          config.pop("layer"), custom_objects=custom_objects
      )
      layer = cls(internal_layer, **config)
      return layer
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tf_agents.utils import common
label_desc: Use image node_id 7 for calling the RNNWrapper obj's underlying member method code with example usage: obj.from_config(cls, config, custom_objects) and returns: layer