class_docstr: Stage of ResNet.
class_docstr_tok: ["Stage","of","ResNet","."]
code: def __init__(self, w_in, w_out, stride, d, w_b=None, groups=1):
      super(ResStage, self).__init__()
      for i in range(d):
          b_stride = stride if i == 0 else 1
          b_w_in = w_in if i == 0 else w_out
          trans_fun = get_trans_fun(cfg.RESNET.TRANS_FUN)
          res_block = ResBlock(
              b_w_in, w_out, b_stride, trans_fun, w_b, groups
          )
          self.add_module("b{}".format(i + 1), res_block)
  
imports: from pycls.core.config import cfg
  from pycls.models.blocks import activation, conv2d, conv2d_cx, gap2d, gap2d_cx, init_weights, linear, linear_cx, norm2d, norm2d_cx, pool2d, pool2d_cx
  from torch.nn import Module
label_desc: Use image node_id 1 to create a new ResStage object from inherited base classes: Module with example: obj = ResStage(w_in, w_out, stride, d, w_b, groups)