docstr: x = self.features(x)
  x = x.mean(3).mean(2)
  x = self.classifier(x)
  return x
docstr_tok: ["x","=","self.features","(","x",")","x","=","x.mean","(","3",")",".mean","(","2",")","x","=","self.classifier","(","x",")","return","x"]
code: def forward(self, x):
      """x = self.features(x)
      x = x.mean(3).mean(2)
      x = self.classifier(x)
      return x"""
      x2, x3, x4, x5 = None, None, None, None
      for stage in range(
          17
      ):  # https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.1/ppocr/modeling/backbones/det_mobilenet_v3.py
          x = self.features[stage](x)
          if stage == 3:  # if s == 2 and start_idx > 3
              x2 = x
          elif stage == 6:
              x3 = x
          elif stage == 12:
              x4 = x
          elif stage == 16:
              x5 = x
      return x2, x3, x4, x5
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the MobileNetV3 obj's underlying member method code with example usage: obj.forward(x) and returns: x2,  x3,  x4,  x5