code: def test_channel_droput():
      img = np.ones((10, 10, 3), dtype=np.float32)
  
      aug = A.ChannelDropout(
          channel_drop_range=(1, 1), always_apply=True
      )  # Drop one channel
  
      transformed = aug(image=img)["image"]
  
      assert (
          sum(transformed[:, :, c].max() for c in range(img.shape[2]))
          == 2
      )
  
      aug = A.ChannelDropout(
          channel_drop_range=(2, 2), always_apply=True
      )  # Drop two channels
      transformed = aug(image=img)["image"]
  
      assert (
          sum(transformed[:, :, c].max() for c in range(img.shape[2]))
          == 1
      )
  
imports: import random
  from functools import partial
  import cv2
  import numpy
  import pytest
  import albumentations
  import albumentations.augmentations.functional
  import albumentations.augmentations.geometric.functional
  from albumentations.augmentations.blur.functional import gaussian_blur
  from .utils import get_dual_transforms, get_image_only_transforms, get_transforms
label_desc: Use image node_id 18 for calling a global function with example usage: test_channel_droput() without return types