Hi,
I’m experimenting with torch.einsum and torch.as_strided to implement a convolution. Right now, my implementation uses approximately 6 times more memory than F.conv2d. I was wondering if the added memory consumption is from torch.as_strided copying data, or simply because my implementation is not as optimized as the CUDA kernel behind F.conv2d.
Also, I could not find documentation for as_strided, is it available somewhere ?
Thanks, Lucas