class_docstr: AnyNet head: optional conv, AvgPool, 1x1.
class_docstr_tok: ["AnyNet","head",":","optional","conv",",","AvgPool",",","1x1","."]
code: def complexity(cx, w_in, head_width, num_classes):
      if head_width > 0:
          cx = conv2d_cx(cx, w_in, head_width, 1)
          cx = norm2d_cx(cx, head_width)
          w_in = head_width
      cx = gap2d_cx(cx, w_in)
      cx = linear_cx(cx, w_in, num_classes, bias=True)
      return cx
  
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, SE
  from torch.nn import Module
label_desc: Use image node_id 3 for calling the AnyHead obj's underlying member method code with example usage: obj.complexity(cx, w_in, head_width, num_classes) and returns: cx