code: def get_shape(self):
      return self.temporal, self.height, self.width
  
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 3 for calling the MaskingGenerator3D obj's underlying member method code with example usage: obj.get_shape() and returns: self,  self,  self