code: def __init__(
      self,
      input_size=37,
      num_channels=1024,
      num_res_blocks=1,
      dropout=0.25,
      bn_track=True,
  ):
      super(Scaler, self).__init__()
      self.blocks = nn.ModuleList()
      self.pre = nn.Linear(input_size, num_channels)
      for _ in range(num_res_blocks):
          self.blocks.append(
              ResBlock(
                  num_channels,
                  input_size,
                  dropout=dropout,
                  use_bn=True,
                  bn_track=bn_track,
              )
          )
      self.out = nn.Linear(num_channels, 1)
  
file_path: insightface/body/human_pose/ambiguity_aware/lib/models/scaler.py
imports: import torch
  import torch.nn
  from lib.models.building_blocks import ResBlock
label_desc: Use image node_id 1 to create a new Scaler object from inherited base classes: nn with example: obj = Scaler(input_size, num_channels, num_res_blocks, dropout, bn_track)