class_docstr: Wraps a Keras RNN/LSTM/GRU layer to make network state more consistent.
code: def build(self, input_shape):
      if len(input_shape) <= 2:
          input_shape = (input_shape[0],) + (None,) + input_shape[1:]
      self._layer.build(input_shape)
      self.built = True
  
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 13 for calling the RNNWrapper obj's underlying member method code with example usage: obj.build(input_shape) without return types