code: def __call__(self, frames):
      sigma_y = sigma_x = random.uniform(
          self.sigma_min[1], self.sigma_max[1]
      )
      sigma_t = random.uniform(self.sigma_min[0], self.sigma_max[0])
      frames = gaussian_filter(
          frames, sigma=(0.0, sigma_t, sigma_y, sigma_x)
      )
      frames = torch.from_numpy(frames)
      return frames
  
imports: import logging
  import math
  import numpy
  import random
  import torch
  import torchvision
  import torchvision.transforms.functional
  from PIL import Image, ImageFilter
  from scipy.ndimage import gaussian_filter
  from torchvision import transforms
  from .rand_augment import rand_augment_transform
  from .random_erasing import RandomErasing
label_desc: Use image node_id 2 for calling the GaussianBlurVideo obj's underlying member method code with example usage: obj.__call__(frames) and returns: frames