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","."]
code: def __init__(self):
      self._inputs = None
      self._outputs = None
  
imports: import abc
  from collections import namedtuple
  import warnings
  import tensorflow
  from garage.tf.models.module import Module
label_desc: Use image node_id 1 to create a new Network object  with example: obj = Network()