original_docstring: 
          Returns a scalar for the top of the a_ij function
          nodes: Info of the nodes after the W param matrix
          i,j: Nodes to consider
          
docstring: Returns a scalar for the top of the a_ij function
  nodes: Info of the nodes after the W param matrix
  i,j: Nodes to consider
docstring_tokens: Returns a scalar for the top of the a_ij function nodes : Info of the nodes after the W param matrix i j : Nodes to consider
code: def _get_top(self, nodes, i, j):
          """
          Returns a scalar for the top of the a_ij function
          nodes: Info of the nodes after the W param matrix
          i,j: Nodes to consider
          """
          cat = self.a(torch.cat((nodes[i], nodes[j]), dim=-1))
          x = torch.exp(self.activation(cat))
          return x
code_tokens: def _get_top ( self , nodes , i , j ) : cat = self . a ( torch . cat ( ( nodes [ i ] , nodes [ j ] ) , dim = - 1 ) ) x = torch . exp ( self . activation ( cat ) ) return x
short_docstring: Returns a scalar for the top of the a_ij function
  nodes: Info of the nodes after the W param matrix
  i,j: Nodes to consider
short_docstring_tokens: Returns a scalar for the top of the a_ij function nodes : Info of the nodes after the W param matrix i j : Nodes to consider
comment: """
          Returns a scalar for the top of the a_ij function
          nodes: Info of the nodes after the W param matrix
          i,j: Nodes to consider
          """