code: def uncrop_masks(
      masks: paddle.Tensor,
      crop_box: List[int],
      orig_h: int,
      orig_w: int,
  ) -> paddle.Tensor:
      x0, y0, x1, y1 = crop_box
      if x0 == 0 and y0 == 0 and x1 == orig_w and y1 == orig_h:
          return masks
      # Coordinate transform masks
      pad_x, pad_y = orig_w - (x1 - x0), orig_h - (y1 - y0)
      pad = (x0, pad_x - x0, y0, pad_y - y0)
      return paddle.nn.functional.pad(masks, pad, value=0)
  
imports: import numpy
  import paddle
  import math
  from copy import deepcopy
  from itertools import product
  from typing import Any, Dict, Generator, ItemsView, List, Tuple
label_desc: Use image node_id 13 for calling a global function with example usage: uncrop_masks(masks, crop_box, orig_h, orig_w) and returns: paddle, masks