code: def __call__(self, *args, **kwargs):
      assert len(args) + len(kwargs) <= len(
          self.inputs
      ), "Too many arguments provided"
      feed_dict = {}
      # Update feed dict with givens.
      for inpt in self.givens:
          feed_dict[inpt] = adjust_shape(
              inpt, feed_dict.get(inpt, self.givens[inpt])
          )
      # Update the args
      for inpt, value in zip(self.inputs, args):
          self._feed_input(feed_dict, inpt, value)
      for inpt_name, value in kwargs.items():
          self._feed_input(
              feed_dict, self.input_names[inpt_name], value
          )
      results = get_session().run(
          self.outputs_update, feed_dict=feed_dict
      )[:-1]
      return results
  
imports: import numpy
  import tensorflow
  import copy
  import os
  import functools
  import collections
  import multiprocessing
label_desc: Use image node_id 3 for calling the _Function obj's underlying member method code with example usage: obj.__call__() and returns: results