code: def _apply_motion_blur(tens, count):
      tens = to_tensor(tens, override_checks=True)
  
      tens_t = tens.clone()
      imshape = tens_t.shape
      size = 15
      kernel_motion_blur = np.zeros((size, size))
      kernel_motion_blur[int((size - 1) / 2), :] = np.ones(size)
      kernel_motion_blur = kernel_motion_blur / size
  
      i = imshape[1] * 3 // 4 - 10 * count
  
      while i <= imshape[1]:
          tens_t[:, i:, :] = cv.filter2D(
              tens_t[:, i:, :], -1, kernel_motion_blur
          )
          tens_t[:, : imshape[1] - i, :] = cv.filter2D(
              tens_t[:, : imshape[1] - i, :], -1, kernel_motion_blur
          )
          i += imshape[1] // 25 - count
          count += 1
  
      return to_tensor(tens_t, override_checks=True)
  
imports: import cv2
  import random
  import math
  import numpy
  from ..coreten import Tensor, to_tensor
  from ..annotations import Tuple, Union
  from ..color import to_hls, to_rgb, to_bgr, to_hsv, to_gray, to_lab
label_desc: Use image node_id 21 for calling a global function with example usage: _apply_motion_blur(tens, count) and returns: to_tensor