class_docstr: Passes input through the layer without changes. Can be
  useful while defining residual networks in the network.
  
  Parameters
  ----------
  {BaseLayer.name}
  
  Methods
  -------
  {BaseLayer.Methods}
  
  Attributes
  ----------
  {BaseLayer.Attributes}
class_docstr_tok: ["Passes","input","through","the","layer","without","changes",".","Can","be","useful","while","defining","residual","networks","in","the","network",".","Parameters","--","--","--","--","--","{","BaseLayer.name","}","Methods","--","--","--","-","{","BaseLayer.Methods","}","Attributes","--","--","--","--","--","{","BaseLayer.Attributes","}"]
code: def get_output_shape(self, input_shape):
      return tf.TensorShape(input_shape)
  
imports: import re
  import copy
  import types
  import string
  import inspect
  from functools import partial
  from collections import OrderedDict, defaultdict
  import six
  import numpy
  import tensorflow
  from neupy.exceptions import LayerConnectionError
  from neupy.core.properties import Property, TypedListProperty
  from neupy.utils import as_tuple, tf_utils
  from neupy.layers.graph import BaseGraph, make_one_if_possible
label_desc: Use image node_id 1 for calling the Identity obj's underlying member method code with example usage: obj.get_output_shape(input_shape) and returns: tf