class_docstr: Inception depthwise convolution
      
class_docstr_tok: ["Inception","depthwise","convolution"]
code: def forward(self, x):
      x_id, x_hw, x_w, x_h = torch.split(x, self.split_indexes, dim=1)
      return torch.cat(
          (
              x_id,
              self.dwconv_hw(x_hw),
              self.dwconv_w(x_w),
              self.dwconv_h(x_h),
          ),
          dim=1,
      )
  
imports: from functools import partial
  import torch
  import torch.nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import trunc_normal_, DropPath, to_2tuple, get_padding, SelectAdaptivePool2d
  from ._builder import build_model_with_cfg
  from ._manipulate import checkpoint_seq
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 2 for calling the InceptionDWConv2d obj's underlying member method code with example usage: obj.forward(x) and returns: torch