class_docstr: ResStage composes sequential blocks that make up a ResNet. These blocks could be,
  for example, Residual blocks, Non-Local layers, or Squeeze-Excitation layers.
  
  ::
  
  
                                      Input
                                         ↓
                                     ResBlock
                                         ↓
                                         .
                                         .
                                         .
                                         ↓
                                     ResBlock
  
  The builder can be found in `create_res_stage`.
docstr: Args:
      res_blocks (torch.nn.module_list): ResBlock module(s).
docstr_tok: ["Args",":","res_blocks","(","torch.nn.module_list",")",":","ResBlock","module","(","s",")","."]
code: def __init__(self, res_blocks: nn.ModuleList) -> nn.Module:
      """
      Args:
          res_blocks (torch.nn.module_list): ResBlock module(s).
      """
      super().__init__()
      self.res_blocks = res_blocks
  
imports: from typing import Callable, List, Tuple, Union
  import numpy
  import torch
  import torch.nn
  from pytorchvideo.layers.utils import set_attributes
  from pytorchvideo.models.head import create_res_basic_head, create_res_roi_pooling_head
  from pytorchvideo.models.net import DetectionBBoxNetwork, Net
  from pytorchvideo.models.stem import create_acoustic_res_basic_stem, create_res_basic_stem
label_desc: Use image node_id 1 to create a new ResStage object from inherited base classes: nn with example: obj = ResStage(res_blocks)