How to achieve tf.scatter_nd in pytorch? project for copynet

[henrye]

Oh, and I see below there’s a ScatterAdd function which would solve my issue of having repeated indices in the input sequence!

How to implement scatter add?

Hi, I need the function that does something like torch.Tensor.scatter_(dim, index, src). x = torch.Tensor([[9,10,11,12]]) id = torch.Tensor([[4,3,4,7]]) out = torch.zeros(1, 8).scatter_(1, id, x) When I run the code above, I got the output [0, 0, 0, 10, 11, 0, 0, 12]. While I expect the output to be [0, 0, 0, 10, 20, 0, 0, 12]. Note that the value in index 4 is 20 (9+11), not 11. Does anyone know how to implement scatter that add the source value to the tensor, not just cover it?