code: def __init__(self, in_ch=3, init_ch=32, bottleneck=True):
      super(StemBlock, self).__init__()
      self.stem_1 = conv_bn(in_ch, init_ch, 3, 2, 1)
      mid_ch = int(init_ch // 2) if bottleneck else init_ch
      self.stem_2a = conv_bn(init_ch, mid_ch, 1, 1, 0)
      self.stem_2b = SeparableConv(mid_ch, init_ch, 2, 1)
      self.stem_2p = nn.MaxPool2d(kernel_size=2, stride=2)
      self.stem_3 = conv_bn(init_ch * 2, init_ch, 1, 1, 0)
  
imports: from __future__ import absolute_import, division, print_function
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new StemBlock object from inherited base classes: nn with example: obj = StemBlock(in_ch, init_ch, bottleneck)