code: def __init__(self, input_size, output_size, act=None):
      super(GINConv, self).__init__()
      self.input_size = input_size
      self.output_size = output_size
  
      self.linear1 = nn.Linear(input_size, output_size, bias_attr=True)
      self.linear2 = nn.Linear(output_size, output_size, bias_attr=True)
  
      self.epsilon = self.create_parameter(
          shape=[1, 1],
          dtype="float32",
          default_initializer=nn.initializer.Constant(value=1.0),
      )
  
      if isinstance(act, str):
          act = getattr(F, act)
      self.activation = act
  
imports: import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import pgl
  from pgl.nn import functional
label_desc: Use image node_id 1 to create a new GINConv object from inherited base classes: nn with example: obj = GINConv(input_size, output_size, act)