class_docstr: AnyNet stage (sequence of blocks w/ the same output shape).
class_docstr_tok: ["AnyNet","stage","(","sequence","of","blocks","w\/","the","same","output","shape",")","."]
code: def forward(self, x):
      for block in self.children():
          x = block(x)
      return x
  
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, SE
  from torch.nn import Module
label_desc: Use image node_id 2 for calling the AnyStage obj's underlying member method code with example usage: obj.forward(x) and returns: x