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.
class_docstr_tok: ["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","."]
docstr: Create and return a placeholder representing class labels.
  
  This method should respect context managers (e.g. "with tf.device")
  and should not just return a reference to a single pre-created
  placeholder.
docstr_tok: ["Create","and","return","a","placeholder","representing","class","labels",".","This","method","should","respect","context","managers","(","e.g",".","``","with","tf.device","''",")","and","should","not","just","return","a","reference","to","a","single","pre-created","placeholder","."]
code: def make_label_placeholder(self):
      """Create and return a placeholder representing class labels.
  
      This method should respect context managers (e.g. "with tf.device")
      and should not just return a reference to a single pre-created
      placeholder.
      """
  
      raise NotImplementedError(
          str(type(self)) + " does not implement "
          "make_label_placeholder"
      )
  
imports: from abc import ABCMeta
  import warnings
  import tensorflow
  from cleverhans import utils_tf
label_desc: Use image node_id 12 for calling the Model obj's underlying member method code with example usage: obj.make_label_placeholder() without return types