class_docstr: Implementation of LightGCN
  
  This is an implementation of the paper LightGCN: Simplifying 
  and Powering Graph Convolution Network for Recommendation 
  (https://dl.acm.org/doi/10.1145/3397271.3401063).
class_docstr_tok: ["Implementation","of","LightGCN","This","is","an","implementation","of","the","paper","LightGCN",":","Simplifying","and","Powering","Graph","Convolution","Network","for","Recommendation","(","https",":","\/\/dl.acm.org\/doi\/10.1145\/3397271.3401063",")","."]
code: def __init__(self, input_size, output_size, act=None):
      super(LightGCNConv, self).__init__()
      self.input_size = input_size
      self.output_size = output_size
  
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 LightGCNConv object from inherited base classes: nn with example: obj = LightGCNConv(input_size, output_size, act)