code: def reversed_padding_repeated_twice(
      conv_module: Union[nn.Conv1d, nn.Conv2d, nn.Conv3d]
  ):
      if isinstance(conv_module.padding, str):
          _reversed_padding_repeated_twice = [0, 0] * len(
              conv_module.kernel_size
          )
          if conv_module.padding == "same":
              for d, k, i in zip(
                  conv_module.dilation,
                  conv_module.kernel_size,
                  range(len(conv_module.kernel_size) - 1, -1, -1),
              ):
                  total_padding = d * (k - 1)
                  left_pad = total_padding // 2
                  _reversed_padding_repeated_twice[2 * i] = left_pad
                  _reversed_padding_repeated_twice[2 * i + 1] = (
                      total_padding - left_pad
                  )
      else:
          _reversed_padding_repeated_twice = _reverse_repeat_tuple(
              conv_module.padding, 2
          )
  
      return _reversed_padding_repeated_twice
  
imports: from typing import Dict, Union, Tuple, Callable, Optional
  from collections.abc import Iterable
  from itertools import repeat
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from .target_space import TargetType
label_desc: Use image node_id 3 for calling a global function with example usage: reversed_padding_repeated_twice(conv_module) and returns: _reversed_padding_repeated_twice