code: def augment_brightness_multiplicative(
      data_sample, multiplier_range=(0.5, 2), per_channel=True
  ):
      multiplier = np.random.uniform(
          multiplier_range[0], multiplier_range[1]
      )
      if not per_channel:
          data_sample *= multiplier
      else:
          for c in range(data_sample.shape[0]):
              multiplier = np.random.uniform(
                  multiplier_range[0], multiplier_range[1]
              )
              data_sample[c] *= multiplier
      return data_sample
  
imports: from typing import List, Tuple, Union, Callable
  import collections
  import numbers
  import random
  import numpy
  import scipy
  import scipy.ndimage
  import SimpleITK
  from scipy.ndimage.filters import gaussian_filter, gaussian_gradient_magnitude
  from skimage.transform import resize
label_desc: Use image node_id 12 for calling a global function with example usage: augment_brightness_multiplicative(data_sample, multiplier_range, per_channel) and returns: data_sample