code: def conv3x3(
      in_planes: int,
      out_planes: int,
      stride: int = 1,
      groups: int = 1,
      dilation: int = 1,
  ) -> nn.Conv2d:
      """3x3 convolution with padding"""
      return nn.Conv2d(
          in_planes,
          out_planes,
          kernel_size=3,
          stride=stride,
          padding=dilation,
          groups=groups,
          bias=False,
          dilation=dilation,
      )
  
imports: from functools import partial
  from typing import Any, Callable, List, Optional, Type, Union
  import torch
  import torch.nn
  from torch import Tensor
  from ..transforms._presets import ImageClassification
  from ..utils import _log_api_usage_once
  from ._api import register_model, Weights, WeightsEnum
  from ._meta import _IMAGENET_CATEGORIES
  from ._utils import _ovewrite_named_param, handle_legacy_interface
label_desc: Use image node_id 1 for calling a global function with example usage: conv3x3(in_planes, out_planes, stride, groups, dilation) and returns: nn