code: def _new_pad_before_conv(x, padding):
      if isinstance(padding, str):
          return x, padding.lower()
      elif isinstance(padding, int):
          return x, padding
      else:
          # if symmetric padding is used, use torch's padding in conv function
          if all(pad[0] == pad[1] for pad in padding):
              return x, [pad[0] for pad in padding]
          pad_list = [
              item for sublist in padding for item in sublist[::-1]
          ][::-1]
          return torch.nn.functional.pad(x, pad_list), "valid"
  
imports: from typing import Optional, Tuple, Union, Sequence
  import torch
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from .None import backend_version
  from ivy.functional.ivy.layers import _get_embed_dim, _handle_padding, _deconv_length
label_desc: Use image node_id 5 for calling a global function with example usage: _new_pad_before_conv(x, padding) and returns: x,  padding, x,  padding, torch,  str, x,  unknown