code: def forward(self, image, mask, mask_features):
      if not self.cat_outputs:
          return self.hrnet.compute_hrnet_feats(
              image, mask_features, return_list=True
          )
  
      outputs = list(self.hrnet(image, mask, mask_features))
      if self.pyramid_on:
          outputs = self.downsize(outputs[0])
      return outputs
  
file_path: carefree-learn/cflearn/api/cv/third_party/iharm/model/backboned/hrnet.py
imports: import torch.nn
  from .ih_model import IHModelWithBackbone
  from ..modifiers import LRMult
  from ..modeling.hrnet_ocr import HighResolutionNet
  from ..modeling.basic_blocks import MaxPoolDownSize
label_desc: Use image node_id 2 for calling the HRNetBB obj's underlying member method code with example usage: obj.forward(image, mask, mask_features) and returns: outputs, self