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I'm seeing myself always writing fftshift(fft(ifftshift(x))) because CUDA compatibility.
Maybe we should do the following:
ft(x) =fftshift(fft(ifftshift(x)))
functionplan_ft(x)
buffer1 =similar(x)
buffer2 =similar(x)
plan =plan_fft(x)
functionp(x)
ifftshift!(buffer, x)
fft!(buffer)
# or mul!(buffer, p, x)fftshift!(buffer2, buffer)
return buffer2
endreturn p
In that way, we have a naive method which works interactively and is still good in speed. Or we have an allocation free version which has also the planned FFT which is more efficient.
It would be breaking because we would need to change some code.
What do you think? For me it's just a bit sad to see that I barely use this package in differentiable, high-performance situations because it doesn't work with CUDA, AD, etc.
The text was updated successfully, but these errors were encountered:
Hi,
I'm seeing myself always writing
fftshift(fft(ifftshift(x)))
because CUDA compatibility.Maybe we should do the following:
In that way, we have a naive method which works interactively and is still good in speed. Or we have an allocation free version which has also the planned FFT which is more efficient.
It would be breaking because we would need to change some code.
What do you think? For me it's just a bit sad to see that I barely use this package in differentiable, high-performance situations because it doesn't work with CUDA, AD, etc.
The text was updated successfully, but these errors were encountered: