class_docstr: Transform model to combine embeddings and features.
      
code: def __init__(self, in_dim, out_dim):
      super(Transform, self).__init__()
      init = np.sqrt(6.0 / (in_dim + out_dim))
      weight_attr = paddle.ParamAttr(
          initializer=nn.initializer.Uniform(low=-init, high=init)
      )
      self.linear = nn.Linear(in_dim, out_dim, weight_attr=weight_attr)
  
imports: import os
  import json
  import math
  import warnings
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from pgl.utils.shared_embedding import SharedEmbedding
  from models.score_funcs import TransEScore, RotatEScore, DistMultScore, ComplExScore, QuatEScore, OTEScore
  from models.init_func import InitFunction
  from utils import uniform, timer_wrapper
label_desc: Use image node_id 1 to create a new Transform object from inherited base classes: nn with example: obj = Transform(in_dim, out_dim)