class_docstr: Implement the standardisation with mean and standard deviation.
class_docstr_tok: ["Implement","the","standardisation","with","mean","and","standard","deviation","."]
code: def __repr__(self):
      return (
          f"StandardisationMeanStd(mean={self.mean}, std={self.std}, apply_fit={self.apply_fit}, "
          f"apply_predict={self.apply_predict})"
      )
  
file_path: adversarial-robustness-toolbox/art/preprocessing/standardisation_mean_std/numpy.py
imports: import logging
  from typing import Optional, Tuple, Union
  import numpy
  from art.config import ART_NUMPY_DTYPE
  from art.preprocessing.preprocessing import Preprocessor
  from art.preprocessing.standardisation_mean_std.utils import broadcastable_mean_std
label_desc: Use image node_id 5 for calling the StandardisationMeanStd obj's underlying member method code with example usage: obj.__repr__() and returns: str, self, str, self, str, self, str, self, str