code: def gen_mask(self, image_size, mask_size, mask_type, patch_size):
      # output: mask as a list with indices for missing patches
      action_list = [[0, 1], [0, -1], [1, 0], [-1, 0]]
      assert image_size[0] == image_size[1]
      img_size_patch = image_size[0] // patch_size
  
      # drop masked patches
      mask = torch.zeros(
          (image_size[0], image_size[1]), dtype=torch.float
      )
  
      if mask_type == "random":
          x = torch.randint(0, img_size_patch, ())
          y = torch.randint(0, img_size_patch, ())
          for i in range(mask_size):
              r = torch.randint(0, len(action_list), ())
              x = torch.clamp(
                  x + action_list[r][0], min=0, max=img_size_patch - 1
              )
              y = torch.clamp(
                  y + action_list[r][1], min=0, max=img_size_patch - 1
              )
              x_offset = x * patch_size
              y_offset = y * patch_size
              mask[
                  x_offset : x_offset + patch_size,
                  y_offset : y_offset + patch_size,
              ] = 1
      else:
          assert mask_type == "row"
          count = 0
          for x in reversed(range(img_size_patch)):
              for y in reversed(range(img_size_patch)):
                  if count < mask_size:
                      count += 1
                      x_offset = x * patch_size
                      y_offset = y * patch_size
                      mask[
                          x_offset : x_offset + patch_size,
                          y_offset : y_offset + patch_size,
                      ] = 1
      return mask
  
imports: import random
  import numpy
  import torch
  from PIL import Image, ImageFilter, ImageOps
  from torch.utils.data import Dataset
  from nemo.collections.multimodal.data.common.data_samplers import SharedEpoch
  from nemo.collections.vision.data.megatron.autoaugment import ImageNetPolicy
  from nemo.collections.vision.data.megatron.image_folder import ImageFolder
label_desc: Use image node_id 2 for calling the InpaintingTransform obj's underlying member method code with example usage: obj.gen_mask(image_size, mask_size, mask_type, patch_size) and returns: mask