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 _USE_EXPORT_CONV and is_exportable():
              # older PyTorch ver needed this to export same padding reasonably
              assert (
                  not is_scriptable()
              )  # Conv2DSameExport does not work with jit
              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
          )
  
file_path: pytorch-image-models/timm/layers/conv2d_same.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from typing import Tuple, Optional
  from .config import is_exportable, is_scriptable
  from .padding import pad_same, pad_same_arg, get_padding_value
label_desc: Use image node_id 2 for calling a global function with example usage: create_conv2d_pad(in_chs, out_chs, kernel_size) and returns: nn, Conv2dSameExport, Conv2dSame