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AtenNonzeroOp, // creates a list of indices where a given tensor is nonzero
AtenIndexTensorOp, // currently only supports constant shape inputs / outputs & may not support boolean indices
AtenMaskedSelectOp, // no lowering. similar behavior to indexing with a boolean, but [flattens the output](https://discuss.pytorch.org/t/masked-select-vs-indexing-with-boolean-in-aten/33621/3)
All of the above ops decompose to indexing with a Boolean tensor
The key thing I can't figure out for these ops right now is that I really need a way to shorten something like
[0, 0, 1, 2, 0, 5, 8]
to
[1,2,5,8]
some kind of list filtering, basically.
If I have any one of the above ops, I would be able to decompose the rest to it. Indexing seems the most canonical choice.
Ops that need work:
All of the above ops decompose to indexing with a Boolean tensor
The key thing I can't figure out for these ops right now is that I really need a way to shorten something like
to
some kind of list filtering, basically.
If I have any one of the above ops, I would be able to decompose the rest to it. Indexing seems the most canonical choice.
How to implement bool indexing
I'm thinking just using a scf for loop to append to a list, then convert to a variable-length tensor. There are some nuances there and I should probably read this discussion with Ben and Quinn to figure it out https://discord.com/channels/973663919757492264/1172976577924050984/1220489866161295440
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