class_docstr: History storage module of GNNAutoScale.
  
  Args:
      
      num_embs (int): Usually the same with number of nodes in a graph.
  
      emb_dims (int): Should be set as the hidden size of gnn models. 
code: def __init__(self, num_embs, emb_dim):
      super().__init__()
  
      self.num_embs = num_embs
      self.emb_dim = emb_dim
  
      numpy_data = np.zeros(
          (self.num_embs, self.emb_dim), dtype="float32"
      )
      self.emb = paddle.to_tensor(
          numpy_data, place=paddle.CUDAPinnedPlace()
      )
  
imports: import numpy
  import paddle
  from pgl.utils.logger import log
label_desc: Use image node_id 1 to create a new History object from inherited base classes: paddle.nn with example: obj = History(num_embs, emb_dim)