class_docstr: An abstract interface for model wrappers that exposes model symbols
  needed for making an attack. This abstraction removes the dependency on
  any specific neural network package (e.g. Keras) from the core
  code of CleverHans. It can also simplify exposing the hidden features of a
  model when a specific package does not directly expose them.
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docstr: For compatibility with functions used as model definitions (taking
  an input tensor and returning the tensor giving the output
  of the model on that input).
docstr_tok: ["For","compatibility","with","functions","used","as","model","definitions","(","taking","an","input","tensor","and","returning","the","tensor","giving","the","output","of","the","model","on","that","input",")","."]
code: def __call__(self, *args, **kwargs):
      """
      For compatibility with functions used as model definitions (taking
      an input tensor and returning the tensor giving the output
      of the model on that input).
      """
  
      warnings.warn(
          "Model.__call__ is deprecated. "
          "The call is ambiguous as to whether the output should "
          "be logits or probabilities, and getting the wrong one "
          "can cause serious problems. "
          "The output actually is probabilities, which are a very "
          "dangerous thing to use as part of any interface for "
          "cleverhans, because softmax probabilities are prone "
          "to gradient masking."
          "On or after 2019-04-24, this method will change to raise "
          "an exception explaining why Model.__call__ should not be "
          "used."
      )
  
      return self.get_probs(*args, **kwargs)
  
imports: from abc import ABCMeta
  import warnings
  import tensorflow
  from cleverhans import utils_tf
label_desc: Use image node_id 2 for calling the Model obj's underlying member method code with example usage: obj.__call__() and returns: self