code: def __init__(self, stem_filters, num_filters=42):
      super(CellStem0, self).__init__()
      self.num_filters = num_filters
      self.stem_filters = stem_filters
      self.conv_1x1 = nn.Sequential()
      self.conv_1x1.add_module("relu", nn.ReLU())
      self.conv_1x1.add_module(
          "conv",
          nn.Conv2d(
              self.stem_filters,
              self.num_filters,
              1,
              stride=1,
              bias=False,
          ),
      )
      self.conv_1x1.add_module(
          "bn",
          nn.BatchNorm2d(
              self.num_filters, eps=0.001, momentum=0.1, affine=True
          ),
      )
  
      self.comb_iter_0_left = BranchSeparables(
          self.num_filters, self.num_filters, 5, 2, 2
      )
      self.comb_iter_0_right = BranchSeparablesStem(
          self.stem_filters, self.num_filters, 7, 2, 3, bias=False
      )
  
      self.comb_iter_1_left = nn.MaxPool2d(3, stride=2, padding=1)
      self.comb_iter_1_right = BranchSeparablesStem(
          self.stem_filters, self.num_filters, 7, 2, 3, bias=False
      )
  
      self.comb_iter_2_left = nn.AvgPool2d(
          3, stride=2, padding=1, count_include_pad=False
      )
      self.comb_iter_2_right = BranchSeparablesStem(
          self.stem_filters, self.num_filters, 5, 2, 2, bias=False
      )
  
      self.comb_iter_3_right = nn.AvgPool2d(
          3, stride=1, padding=1, count_include_pad=False
      )
  
      self.comb_iter_4_left = BranchSeparables(
          self.num_filters, self.num_filters, 3, 1, 1, bias=False
      )
      self.comb_iter_4_right = nn.MaxPool2d(3, stride=2, padding=1)
  
imports: import torch
  import torch.nn
  import torch.utils.model_zoo
label_desc: Use image node_id 1 to create a new CellStem0 object from inherited base classes: nn with example: obj = CellStem0(stem_filters, num_filters)