class_docstr: Seq2Seq model for sequence processing in O(n log n) time.
docstr: Body of Neural Shuffle-Exchange network.
  
  Args:
    features: dictionary of inputs and targets
docstr_tok: ["Body","of","Neural","Shuffle-Exchange","network",".","Args",":","features",":","dictionary","of","inputs","and","targets"]
code: def body(self, features):
      """Body of Neural Shuffle-Exchange network.
  
      Args:
        features: dictionary of inputs and targets
      """
  
      inputs = tf.squeeze(features["inputs"], axis=2)
      logits = shuffle_network(inputs, self._hparams)
      return tf.expand_dims(logits, axis=2)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 6 for calling the ShuffleNetwork obj's underlying member method code with example usage: obj.body(features) and returns: tf