code: def create_conv2d_pad(in_chs, out_chs, kernel_size, **kwargs):
      padding = kwargs.pop("padding", "")
      kwargs.setdefault("bias", False)
      padding, is_dynamic = get_padding_value(
          padding, kernel_size, **kwargs
      )
      if is_dynamic:
          if is_exportable():
              assert not is_scriptable()
              return Conv2dSameExport(
                  in_chs, out_chs, kernel_size, **kwargs
              )
          else:
              return Conv2dSame(in_chs, out_chs, kernel_size, **kwargs)
      else:
          return nn.Conv2d(
              in_chs, out_chs, kernel_size, padding=padding, **kwargs
          )
  
imports: import collections.abc
  import math
  from functools import partial
  from itertools import repeat
  from typing import Tuple, Optional
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from .config import *
label_desc: Use image node_id 9 for calling a global function with example usage: create_conv2d_pad(in_chs, out_chs, kernel_size) and returns: nn, Conv2dSameExport, Conv2dSame