class_docstr: Network class For TensorFlow.
  
  A Network contains connectivity information by inputs/outputs.
  When a Network is built, it appears as a subgraph in the computation
  graphs, scoped by the Network name. All Networks built with the same
  model share the same parameters, i.e same inputs yield to same outputs.
class_docstr_tok: ["Network","class","For","TensorFlow",".","A","Network","contains","connectivity","information","by","inputs\/outputs",".","When","a","Network","is","built",",","it","appears","as","a","subgraph","in","the","computation","graphs",",","scoped","by","the","Network","name",".","All","Networks","built","with","the","same","model","share","the","same","parameters",",","i.e","same","inputs","yield","to","same","outputs","."]
docstr: Tensor input of the Network.
  
  Returns:
      tf.Tensor: Input.
docstr_tok: ["Tensor","input","of","the","Network",".","Returns",":","tf.Tensor",":","Input","."]
code: def input(self):
      """Tensor input of the Network.
  
      Returns:
          tf.Tensor: Input.
  
      """
      return self._inputs[0]
  
imports: import abc
  from collections import namedtuple
  import warnings
  import tensorflow
  from garage.tf.models.module import Module
label_desc: Use image node_id 2 for calling the Network obj's underlying member method code with example usage: obj.input() and returns: self