class_docstr: ResNet head: AvgPool, 1x1.
class_docstr_tok: ["ResNet","head",":","AvgPool",",","1x1","."]
code: def __init__(self, w_in, num_classes):
      super(ResHead, self).__init__()
      self.avg_pool = gap2d(w_in)
      self.fc = linear(w_in, num_classes, bias=True)
  
imports: from pycls.core.config import cfg
  from pycls.models.blocks import activation, conv2d, conv2d_cx, gap2d, gap2d_cx, init_weights, linear, linear_cx, norm2d, norm2d_cx, pool2d, pool2d_cx
  from torch.nn import Module
label_desc: Use image node_id 1 to create a new ResHead object from inherited base classes: Module with example: obj = ResHead(w_in, num_classes)