class_docstr: Base class for RoIHeads.
class_docstr_tok: ["Base","class","for","RoIHeads","."]
docstr: Perform forward propagation and loss calculation of the roi head on
  the features of the upstream network.
docstr_tok: ["Perform","forward","propagation","and","loss","calculation","of","the","roi","head","on","the","features","of","the","upstream","network","."]
code: def loss(
      self,
      x: Tuple[Tensor],
      rpn_results_list: InstanceList,
      batch_data_samples: SampleList,
  ):
      """Perform forward propagation and loss calculation of the roi head on
      the features of the upstream network."""
  
file_path: mmdetection/mmdet/models/roi_heads/base_roi_head.py
imports: from abc import ABCMeta, abstractmethod
  from typing import Tuple
  from mmengine.model import BaseModule
  from torch import Tensor
  from mmdet.registry import MODELS
  from mmdet.structures import SampleList
  from mmdet.utils import InstanceList, OptConfigType, OptMultiConfig
label_desc: Use image node_id 8 for calling the BaseRoIHead obj's underlying member method code with example usage: obj.loss(x, rpn_results_list, batch_data_samples) without return types