class_docstr: A Model that can be pickled because it contains no references to any
  Variables (e.g. it identifies Variables only by name).
  The Model must be able to find all of its Variables via get_vars
  for them to be pickled.
  Note that NoRefModel may have different Variable names after it is
  restored, e.g. if the unpickling is run with a different enclosing
  scope. NoRefModel will still work in these circumstances as long
  as get_params returns the same order of Variables after unpickling
  as it did before pickling.
  See also cleverhans.picklable_model for a different, complementary
  pickling strategy: models that can be pickled because they use *only*
  references to Variables and work regardless of Variable names.
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code: def __getstate__(self):
      # Serialize everything except the Variables
      out = self.__dict__.copy()
  
      # The base Model class adds this tf reference to self
      # We mustn't pickle anything tf, this will need to be
      # regenerated after the model is reloaded.
      if "_dummy_input" in out:
          del out["_dummy_input"]
  
      # Add the Variables
      sess = tf.get_default_session()
      if sess is None:
          raise RuntimeError(
              "NoRefModel requires a default " "TensorFlow session"
          )
      tf_variables = self.get_vars()
      out[VARS] = sess.run(tf_variables)
      out[VAR_NAMES] = [var.name for var in tf_variables]
      return out
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import warnings
  import joblib
  import tensorflow
  from cleverhans.model import Model
  from cleverhans.utils import ordered_union
  from cleverhans.utils import safe_zip
label_desc: Use image node_id 1 for calling the NoRefModel obj's underlying member method code with example usage: obj.__getstate__() and returns: out