docstr: emb_dim (int): node embedding dimensionality
docstr_tok: ["emb_dim","(","int",")",":","node","embedding","dimensionality"]
code: def __init__(self, emb_dim):
      """
      emb_dim (int): node embedding dimensionality
      """
  
      super(GINConv, self).__init__()
  
      self.mlp = nn.Sequential(
          nn.Linear(emb_dim, emb_dim),
          nn.BatchNorm1D(emb_dim),
          nn.ReLU(),
          nn.Linear(emb_dim, emb_dim),
      )
  
      self.eps = self.create_parameter(
          shape=[1, 1],
          dtype="float32",
          default_initializer=nn.initializer.Constant(value=0),
      )
  
      self.bond_encoder = BondEncoder(emb_dim=emb_dim)
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  import pgl
  import pgl.nn
  import pgl.nn.functional
  from mol_encoder import AtomEncoder, BondEncoder
label_desc: Use image node_id 1 to create a new GINConv object from inherited base classes: paddle.nn with example: obj = GINConv(emb_dim)