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Hi. The work on involution is awesome and I'd like to try them on medical imaging that requires 3D operation.
I was wondering if you could spare some time to implement the 3D version fo involution_cuda?
I found the involution_naive could not be extended to 3D because the torch.fold and torch.unfold only support 4d tensor.
In previous issues, authors also mentioned that the naive version was slower and consumed more memory. I guess that the problem will be aggravated for 3D version.
Looking forward to trying this new ops. Thank you.
The text was updated successfully, but these errors were encountered:
@memmelma and I implemented a pure PyTorch version of a 3D Involution which you could try out. However, the native PyTorch implementation is kinda GPU memory hungry due to the unfold operation, which was also pointed out by the author in issue #1. Very awesome work by the way @d-li14!
@memmelma and I implemented a pure PyTorch version of a 3D Involution which you could try out. However, the native PyTorch implementation is kinda GPU memory hungry due to the unfold operation, which was also pointed out by the author in issue #1. Very awesome work by the way @d-li14!
Hi. The work on involution is awesome and I'd like to try them on medical imaging that requires 3D operation.
I was wondering if you could spare some time to implement the 3D version fo involution_cuda?
I found the involution_naive could not be extended to 3D because the torch.fold and torch.unfold only support 4d tensor.
In previous issues, authors also mentioned that the naive version was slower and consumed more memory. I guess that the problem will be aggravated for 3D version.
Looking forward to trying this new ops. Thank you.
The text was updated successfully, but these errors were encountered: