code: def forward(self, x):
      x = x.view(x.size(0), -1)
      # pre-processing
      y = self.w1(x)
      y = self.batch_norm1(y)
      y = self.relu(y)
      y = self.dropout(y)
  
      # linear layers
      for i in range(self.num_stage):
          y = self.linear_stages[i](y)
  
      # y = self.w2(y)
      # y should be features, and x is reshaped inputs
      # namely x, joints_sc for LinearModelAfter
      return y, x
  
file_path: insightface/body/human_pose/ambiguity_aware/lib/models/simple_model.py
imports: from __future__ import absolute_import
  from __future__ import print_function
  import torch.nn
label_desc: Use image node_id 2 for calling the LinearModelBefore obj's underlying member method code with example usage: obj.forward(x) and returns: y,  x