class_docstr: A transformer for converting classification output probability
  tensors to class labels. It assumes the predictor is a callable
  that can be called with a `N`-tensor of data points `x` and produces
  an `N`-tensor of outputs.
code: def __init__(self, predictor):
      self.predictor = predictor
  
file_path: alibi/alibi/utils/wrappers.py
imports: import numpy
  from functools import singledispatch, update_wrapper
label_desc: Use image node_id 1 to create a new ArgmaxTransformer object  with example: obj = ArgmaxTransformer(predictor)