code: def __init__(
      self,
      in_chs_left,
      out_chs_left,
      in_chs_right,
      out_chs_right,
      pad_type="",
  ):
      super(ReductionCell0, self).__init__()
      self.conv_prev_1x1 = ActConvBn(
          in_chs_left, out_chs_left, 1, stride=1, padding=pad_type
      )
      self.conv_1x1 = ActConvBn(
          in_chs_right, out_chs_right, 1, stride=1, padding=pad_type
      )
  
      self.comb_iter_0_left = BranchSeparables(
          out_chs_right, out_chs_right, 5, 2, pad_type
      )
      self.comb_iter_0_right = BranchSeparables(
          out_chs_right, out_chs_right, 7, 2, pad_type
      )
  
      self.comb_iter_1_left = create_pool2d(
          "max", 3, 2, padding=pad_type
      )
      self.comb_iter_1_right = BranchSeparables(
          out_chs_right, out_chs_right, 7, 2, pad_type
      )
  
      self.comb_iter_2_left = create_pool2d(
          "avg", 3, 2, count_include_pad=False, padding=pad_type
      )
      self.comb_iter_2_right = BranchSeparables(
          out_chs_right, out_chs_right, 5, 2, pad_type
      )
  
      self.comb_iter_3_right = create_pool2d(
          "avg", 3, 1, count_include_pad=False, padding=pad_type
      )
  
      self.comb_iter_4_left = BranchSeparables(
          out_chs_right, out_chs_right, 3, 1, pad_type
      )
      self.comb_iter_4_right = create_pool2d(
          "max", 3, 2, padding=pad_type
      )
  
imports: from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.layers import ConvNormAct, create_conv2d, create_pool2d, create_classifier
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 1 to create a new ReductionCell0 object from inherited base classes: nn with example: obj = ReductionCell0(in_chs_left, out_chs_left, in_chs_right, out_chs_right, pad_type)