code: def augment_brightness_additive(
      data_sample,
      mu: float,
      sigma: float,
      per_channel: bool = True,
      p_per_channel: float = 1.0,
  ):
      if not per_channel:
          rnd_nb = np.random.normal(mu, sigma)
          for c in range(data_sample.shape[0]):
              if np.random.uniform() <= p_per_channel:
                  data_sample[c] += rnd_nb
      else:
          for c in range(data_sample.shape[0]):
              if np.random.uniform() <= p_per_channel:
                  rnd_nb = np.random.normal(mu, sigma)
                  data_sample[c] += rnd_nb
      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 10 for calling a global function with example usage: augment_brightness_additive(data_sample, mu, sigma, per_channel, p_per_channel) and returns: data_sample