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 __call__(self, x):
      pred = np.atleast_2d(self.predictor(x))
      return np.argmax(pred, axis=1)
  
file_path: alibi/alibi/utils/wrappers.py
imports: import numpy
  from functools import singledispatch, update_wrapper
label_desc: Use image node_id 2 for calling the ArgmaxTransformer obj's underlying member method code with example usage: obj.__call__(x) and returns: np