class_docstr: An RNN cell base class that can implement a stack or queue.
    
class_docstr_tok: ["An","RNN","cell","base","class","that","can","implement","a","stack","or","queue","."]
docstr: The NeuralStackCell maintains a tuple of state values.
  
  Returns:
    (controller_state.shape,
     read_values.shape,
     memory_values.shape,
     read_strengths.shape,
     write_strengths.shape)
docstr_tok: ["The","NeuralStackCell","maintains","a","tuple","of","state","values",".","Returns",":","(","controller_state.shape",",","read_values.shape",",","memory_values.shape",",","read_strengths.shape",",","write_strengths.shape",")"]
code: def state_size(self):
      """The NeuralStackCell maintains a tuple of state values.
  
      Returns:
        (controller_state.shape,
         read_values.shape,
         memory_values.shape,
         read_strengths.shape,
         write_strengths.shape)
      """
      return (
          tf.TensorShape([self._num_units]),
          tf.TensorShape([self._num_read_heads, self._embedding_size]),
          tf.TensorShape([self._memory_size, self._embedding_size]),
          tf.TensorShape([1, self._memory_size, 1]),
          tf.TensorShape([self._num_write_heads, self._memory_size, 1]),
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_layers
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the NeuralStackCell obj's underlying member method code with example usage: obj.state_size() and returns: tf,  tf,  tf,  tf,  tf