code: def _compute_pad_size_3d(
      size_dhw: Tuple[int, int, int], patch_size: Tuple[int, int, int]
  ) -> Tuple[int, int, int]:
      pad_size = [
          (patch_size[i] - size_dhw[i] % patch_size[i]) % patch_size[i]
          for i in range(3)
      ]
      return pad_size[0], pad_size[1], pad_size[2]
  
imports: from functools import partial
  from typing import Any, Callable, List, Optional, Tuple
  import torch
  import torch.nn.functional
  from torch import nn, Tensor
  from ...transforms._presets import VideoClassification
  from ...utils import _log_api_usage_once
  from .._api import register_model, Weights, WeightsEnum
  from .._meta import _KINETICS400_CATEGORIES
  from .._utils import _ovewrite_named_param, handle_legacy_interface
  from ..swin_transformer import PatchMerging, SwinTransformerBlock
label_desc: Use image node_id 3 for calling a global function with example usage: _compute_pad_size_3d(size_dhw, patch_size) and returns: pad_size,  pad_size,  pad_size