docstr: assuming input size 8x8
docstr_tok: ["assuming","input","size","8x8"]
code: def __init__(self, C, num_classes):
      """assuming input size 8x8"""
      super(AuxiliaryHeadTinyImageNet, self).__init__()
      self.features = nn.Sequential(
          nn.ReLU(inplace=False),
          # image size = 2 x 2
          nn.AvgPool2d(5, stride=3, padding=0, count_include_pad=False),
          nn.Conv2d(C, 128, 1, bias=False),
          nn.BatchNorm2d(128),
          nn.ReLU(inplace=False),
          nn.Conv2d(128, 768, 2, bias=False),
          nn.BatchNorm2d(768),
          nn.ReLU(inplace=False),
      )
      self.classifier = nn.Linear(768, num_classes)
  
imports: from operations import *
  from .utils import drop_path
label_desc: Use image node_id 1 to create a new AuxiliaryHeadTinyImageNet object from inherited base classes: nn with example: obj = AuxiliaryHeadTinyImageNet(C, num_classes)