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: import random
  import numpy
  import paddle
  from paddle.nn.functional import avg_pool2d, avg_pool3d
  from typing import List, Tuple, Union, Callable
  from copy import deepcopy
  from scipy.ndimage import map_coordinates, fourier_gaussian
  from scipy.ndimage.filters import gaussian_filter, gaussian_gradient_magnitude
  from scipy.ndimage.morphology import grey_dilation
  from skimage.transform import resize
  from scipy.ndimage.measurements import label
label_desc: Use image node_id 11 for calling a global function with example usage: augment_brightness_multiplicative(data_sample, multiplier_range, per_channel) and returns: data_sample