class_docstr: Represents the output of a classification head.
  
  Either classes or scores or both must be set.
  
  The classes `Tensor` must provide string labels, not integer class IDs.
  
  If only classes is set, it is interpreted as providing top-k results in
  descending order.
  
  If only scores is set, it is interpreted as providing a score for every class
  in order of class ID.
  
  If both classes and scores are set, they are interpreted as zipped, so each
  score corresponds to the class at the same index.  Clients should not depend
  on the order of the entries.
class_docstr_tok: ["Represents","the","output","of","a","classification","head",".","Either","classes","or","scores","or","both","must","be","set",".","The","classes","`","Tensor","`","must","provide","string","labels",",","not","integer","class","IDs",".","If","only","classes","is","set",",","it","is","interpreted","as","providing","top-k","results","in","descending","order",".","If","only","scores","is","set",",","it","is","interpreted","as","providing","a","score","for","every","class","in","order","of","class","ID",".","If","both","classes","and","scores","are","set",",","they","are","interpreted","as","zipped",",","so","each","score","corresponds","to","the","class","at","the","same","index",".","Clients","should","not","depend","on","the","order","of","the","entries","."]
code: def classes(self):
      return self._classes
  
imports: import abc
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.keras.saving.utils_v1 import signature_def_utils
  from tensorflow.python.saved_model import signature_def_utils
label_desc: Use image node_id 3 for calling the ClassificationOutput obj's underlying member method code with example usage: obj.classes() and returns: self