code: def __init__(self, config):
      super(PretrainBondLength, self).__init__()
      log.info("Using pretrain bond length")
      hidden_size = config.emb_dim
      self.bond_length_pred_linear = nn.Sequential(
          L.Linear(hidden_size * 2, hidden_size // 2),
          L.batch_norm_1d(hidden_size // 2),
          nn.Swish(),
          L.Linear(hidden_size // 2, hidden_size // 4),
          L.batch_norm_1d(hidden_size // 4),
          nn.Swish(),
          L.Linear(hidden_size // 4, 1),
      )
      self.loss = nn.SmoothL1Loss(reduction="none")
  
imports: import os
  import sys
  import math
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import pgl.nn
  from pgl.utils.logger import log
  import models.conv
  import models.mol_encoder
  import models.layers
label_desc: Use image node_id 1 to create a new PretrainBondLength object from inherited base classes: paddle.nn with example: obj = PretrainBondLength(config)