code: def __init__(
      self,
      dw_ksize,
      expand_ksize,
      project_ksize,
      num_repeat,
      in_channels,
      out_channels,
      expand_ratio,
      id_skip,
      strides,
      se_ratio,
      swish,
      dilated,
  ):
      super().__init__()
      layers = [
          MixBlock(
              dw_ksize,
              expand_ksize,
              project_ksize,
              in_channels,
              out_channels,
              expand_ratio,
              id_skip,
              strides,
              se_ratio,
              swish,
              dilated,
          )
      ]
  
      for _ in range(num_repeat - 1):
          layers.append(
              MixBlock(
                  dw_ksize,
                  expand_ksize,
                  project_ksize,
                  in_channels,
                  out_channels,
                  expand_ratio,
                  id_skip,
                  [1, 1],
                  se_ratio,
                  swish,
                  dilated,
              )
          )
      self.layers = nn.Sequential(*layers)
  
imports: import torch.nn
  from .layers import Flatten
  from .layers import SEModule
  from .layers import Swish
  from .mdconv import MDConv
  from .utils import MixnetDecoder
  from .utils import round_filters
label_desc: Use image node_id 1 to create a new MixModule object from inherited base classes: nn with example: obj = MixModule(dw_ksize, expand_ksize, project_ksize, num_repeat, in_channels, out_channels, expand_ratio, id_skip, strides, se_ratio, swish, dilated)