code: def __init__(self, input_size, output_size, act=None):
      super(GraphSageMeanConv, self).__init__()
      self.aggr_func = "reduce_mean"
  
      self.self_linear = nn.Linear(input_size, output_size)
      self.neigh_linear = nn.Linear(input_size, output_size)
  
      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 GraphSageMeanConv object from inherited base classes: nn with example: obj = GraphSageMeanConv(input_size, output_size, act)