class_docstr: Utility for training shadow models and generating shadow-datasets for membership inference attacks in scikit-learn,
  PyTorch and TensorFlow v2.
code: def _default_random_record(self) -> np.ndarray:
      return self._rng.random(self._input_shape)
  
file_path: adversarial-robustness-toolbox/art/attacks/inference/membership_inference/shadow_models.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import math
  from functools import reduce
  from typing import Callable, Tuple, TYPE_CHECKING, List, Optional, Sequence
  import numpy
label_desc: Use image node_id 3 for calling the ShadowModels obj's underlying member method code with example usage: obj._default_random_record() and returns: self