code: def __init__(self, config, with_efeat=True):
      super(LiteGEMConv, self).__init__()
      log.info("layer_type is %s" % self.__class__.__name__)
      self.config = config
      self.with_efeat = with_efeat
  
      self.aggr = self.config.aggr
      self.learn_t = self.config.learn_t
      self.learn_p = self.config.learn_p
      self.init_t = self.config.init_t
      self.init_p = self.config.init_p
  
      self.eps = 1e-7
  
      self.emb_dim = self.config.emb_dim
  
      if self.with_efeat:
          self.bond_encoder = getattr(
              ME, self.config.bond_enc_type, ME.BondEncoder
          )(emb_dim=self.emb_dim)
  
      self.concat = config.concat
      if self.concat:
          self.fc_concat = Linear(self.emb_dim * 3, self.emb_dim)
  
      assert self.aggr in ["softmax_sg", "softmax", "power"]
  
      channels_list = [self.emb_dim]
      for i in range(1, self.config.mlp_layers):
          channels_list.append(self.emb_dim * 2)
      channels_list.append(self.emb_dim)
  
      self.mlp = MLP(
          channels_list, norm=self.config.norm, last_lin=True
      )
  
      if self.learn_t and self.aggr == "softmax":
          self.t = self.create_parameter(
              shape=[
                  1,
              ],
              dtype="float32",
              default_initializer=nn.initializer.Constant(
                  value=self.init_t
              ),
          )
      else:
          self.t = self.init_t
  
      if self.learn_p:
          self.p = self.create_parameter(
              shape=[
                  1,
              ],
              dtype="float32",
              default_initializer=nn.initializer.Constant(
                  value=self.init_p
              ),
          )
  
imports: import numpy
  import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import paddle.distributed
  import pgl
  import pgl.nn
  from pgl.nn import functional
  from pgl.utils.logger import log
  import models.mol_encoder
label_desc: Use image node_id 1 to create a new LiteGEMConv object from inherited base classes: paddle.nn with example: obj = LiteGEMConv(config, with_efeat)