code: def get_padding_2d(
      kernel_size: Tuple[int, int], dilation: Tuple[int, int]
  ) -> Tuple[int, int]:
      paddings = (
          get_padding(kernel_size[0], dilation[0]),
          get_padding(kernel_size[1], dilation[1]),
      )
      return paddings
  
imports: from typing import List, Optional, Tuple
  import torch
  import torch.nn
  from einops import rearrange
  from nemo.collections.asr.parts.utils.activations import Snake
  from nemo.collections.tts.parts.utils.helpers import mask_sequence_tensor
  from nemo.core.classes.common import typecheck
  from nemo.core.classes.module import NeuralModule
  from nemo.core.neural_types.elements import EncodedRepresentation, Index, LengthsType, VoidType
  from nemo.core.neural_types.neural_type import NeuralType
  from nemo.utils import logging
label_desc: Use image node_id 2 for calling a global function with example usage: get_padding_2d(kernel_size, dilation) and returns: paddings