code: def __call__(self, x):
      h = x - self.norm
      h, projection1 = self.block1(h)
      h, projection2 = self.block2(h, down_sampling=True)
      h, projection3 = self.block3(h, down_sampling=True)
      h, projection4 = self.block4(h, down_sampling=True)
      h, projection5 = self.block5(h, down_sampling=True)
      return (
          projection1,
          projection2,
          projection3,
          projection4,
          projection5,
      )
  
file_path: carefree-learn/cflearn/api/cv/third_party/hed.py
imports: import os
  import torch
  import numpy
  import torch.nn
  from ....parameters import OPT
label_desc: Use image node_id 2 for calling the ControlNetHED_Apache2 obj's underlying member method code with example usage: obj.__call__(x) and returns: projection1,  projection2,  projection3,  projection4,  projection5