class_docstr: Base class for RoI extractor.
  
  Args:
      roi_layer (:obj:`ConfigDict` or dict): Specify RoI layer type and
          arguments.
      out_channels (int): Output channels of RoI layers.
      featmap_strides (list[int]): Strides of input feature maps.
      init_cfg (:obj:`ConfigDict` or dict or list[:obj:`ConfigDict` or             dict], optional): Initialization config dict. Defaults to None.
class_docstr_tok: ["Base","class","for","RoI","extractor",".","Args",":","roi_layer","(",":","obj",":","`","ConfigDict","`","or","dict",")",":","Specify","RoI","layer","type","and","arguments",".","out_channels","(","int",")",":","Output","channels","of","RoI","layers",".","featmap_strides","(","list","[","int","]",")",":","Strides","of","input","feature","maps",".","init_cfg","(",":","obj",":","`","ConfigDict","`","or","dict","or","list","[",":","obj",":","`","ConfigDict","`","or","dict","]",",","optional",")",":","Initialization","config","dict",".","Defaults","to","None","."]
docstr: Extractor ROI feats.
  
  Args:
      feats (Tuple[Tensor]): Multi-scale features.
      rois (Tensor): RoIs with the shape (n, 5) where the first
          column indicates batch id of each RoI.
      roi_scale_factor (Optional[float]): RoI scale factor.
          Defaults to None.
  
  Returns:
      Tensor: RoI feature.
docstr_tok: ["Extractor","ROI","feats",".","Args",":","feats","(","Tuple","[","Tensor","]",")",":","Multi-scale","features",".","rois","(","Tensor",")",":","RoIs","with","the","shape","(","n",",","5",")","where","the","first","column","indicates","batch","id","of","each","RoI",".","roi_scale_factor","(","Optional","[","float","]",")",":","RoI","scale","factor",".","Defaults","to","None",".","Returns",":","Tensor",":","RoI","feature","."]
code: def forward(
      self,
      feats: Tuple[Tensor],
      rois: Tensor,
      roi_scale_factor: Optional[float] = None,
  ) -> Tensor:
      """Extractor ROI feats.
  
      Args:
          feats (Tuple[Tensor]): Multi-scale features.
          rois (Tensor): RoIs with the shape (n, 5) where the first
              column indicates batch id of each RoI.
          roi_scale_factor (Optional[float]): RoI scale factor.
              Defaults to None.
  
      Returns:
          Tensor: RoI feature.
      """
      pass
  
file_path: mmdetection/mmdet/models/roi_heads/roi_extractors/base_roi_extractor.py
imports: from abc import ABCMeta, abstractmethod
  from typing import List, Optional, Tuple
  import torch
  import torch.nn
  from mmcv import ops
  from mmengine.model import BaseModule
  from torch import Tensor
  from mmdet.utils import ConfigType, OptMultiConfig
label_desc: Use image node_id 5 for calling the BaseRoIExtractor obj's underlying member method code with example usage: obj.forward(feats, rois, roi_scale_factor) without return types