class_docstr: Base class for mask heads used in One-Stage Instance Segmentation.
class_docstr_tok: ["Base","class","for","mask","heads","used","in","One-Stage","Instance","Segmentation","."]
docstr: Calculate the loss based on the features extracted by the mask
  head.
docstr_tok: ["Calculate","the","loss","based","on","the","features","extracted","by","the","mask","head","."]
code: def loss_by_feat(self, *args, **kwargs):
      """Calculate the loss based on the features extracted by the mask
      head."""
      pass
  
file_path: mmdetection/mmdet/models/dense_heads/base_mask_head.py
imports: from abc import ABCMeta, abstractmethod
  from typing import List, Tuple, Union
  from mmengine.model import BaseModule
  from torch import Tensor
  from mmdet.structures import SampleList
  from mmdet.utils import InstanceList, OptInstanceList, OptMultiConfig
  from ..utils import unpack_gt_instances
label_desc: Use image node_id 2 for calling the BaseMaskHead obj's underlying member method code with example usage: obj.loss_by_feat() without return types