code: def _forward_impl(self, x: Tensor) -> Tensor:
      # See note [TorchScript super()]
      x = self.conv1(x)
      x = self.maxpool(x)
      x = self.stage2(x)
      x = self.stage3(x)
      x = self.stage4(x)
      x = self.conv5(x)
      x = x.mean([2, 3])  # global pool
      x = self.fc(x)
      return x
  
file_path: deep-learning-for-image-processing/pytorch_classification/Test7_shufflenet/model.py
imports: from typing import List, Callable
  import torch
  from torch import Tensor
  import torch.nn
label_desc: Use image node_id 2 for calling the ShuffleNetV2 obj's underlying member method code with example usage: obj._forward_impl(x) and returns: x