I was [looking for something like this a couple of months back](https://discuss.tvm.apache.org/t/reshape-in-place-using-relay/6856), but to avail.
It would be useful to have, I'm just unsure what changes would be needed. In a sense we have in-place operations when we fuse conv2d+relu layers (afaik), since we apply the ReLU on the accumulated value when it is ready. Doing this requires a specialised pass (though I haven't read the code for it). One could in-principle do something similar with your use-case. But it's more interesting to consider what a general solution would look like, that could be easily used at the Python `te.compute` expression level. --- [Visit Topic](https://discuss.tvm.apache.org/t/supporting-in-place-operations/7871/2) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/75ae421b5d9f70a48ff5ad65d3da98af6763255933242c4e1706ec2eead42e15).
