code: def __init__(
      self, linear_size, p_dropout=0.5, spectral_norm=False, use_bn=True
  ):
      super(Linear, self).__init__()
      self.l_size = linear_size
  
      self.use_bn = use_bn
      self.relu = nn.ReLU(inplace=True)
      self.dropout = nn.Dropout(p_dropout)
  
      self.w1 = nn.Linear(self.l_size, self.l_size)
      self.batch_norm1 = nn.BatchNorm1d(self.l_size)
  
      self.w2 = nn.Linear(self.l_size, self.l_size)
      self.batch_norm2 = nn.BatchNorm1d(self.l_size)
      if spectral_norm:
          self.w1 = nn.utils.spectral_norm(self.w1)
          self.w2 = nn.utils.spectral_norm(self.w2)
  
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 1 to create a new Linear object from inherited base classes: nn with example: obj = Linear(linear_size, p_dropout, spectral_norm, use_bn)