code: def __init__(self, dim=768):
      super(DWConv, self).__init__()
      self.dwconv = nn.Conv2d(dim, dim, 3, 1, 1, bias=True, groups=dim)
  
imports: import math
  from functools import partial
  from typing import Optional
  import torch
  import torch.nn
  from pytorch_toolbelt.modules.interfaces import AbstractEncoder, FeatureMapsSpecification
  from pytorch_toolbelt.modules.activations import instantiate_activation_block, ACT_GELU
  from pytorch_toolbelt.modules.drop_path import DropPath
label_desc: Use image node_id 1 to create a new DWConv object from inherited base classes: nn with example: obj = DWConv(dim)