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It will be great to return the index locations from the scatter operations like torch_scatter: `from torch_scatter import scatter_max
src = torch.Tensor([[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]]) index = torch.tensor([[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]]) out = src.new_zeros((2, 6))
out, argmax = scatter_max(src, index, out=out) ` https://pytorch-scatter.readthedocs.io/en/1.3.0/functions/max.html
Is this an upcoming feature ?
The text was updated successfully, but these errors were encountered:
There's no plan to add this at the moment. A scatter_argmax might be doable, but I'm curious what would you use it for?
scatter_argmax
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this is used in some graphs architecture to speed up computation (one call instead of 2) and not available in mlx-graphs repo https://github.com/mlx-graphs/mlx-graphs/blob/4619d97ade4a788d1fe20b4d08b994ad56ee5ca0/mlx_graphs/utils/scatter.py#L10
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It will be great to return the index locations from the scatter operations like torch_scatter:
`from torch_scatter import scatter_max
src = torch.Tensor([[2, 0, 1, 4, 3], [0, 2, 1, 3, 4]])
index = torch.tensor([[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]])
out = src.new_zeros((2, 6))
out, argmax = scatter_max(src, index, out=out)
`
https://pytorch-scatter.readthedocs.io/en/1.3.0/functions/max.html
Is this an upcoming feature ?
The text was updated successfully, but these errors were encountered: