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fkodom / fft-conv-pytorch

Implementation of 1D, 2D, and 3D FFT convolutions in PyTorch. Much faster than direct convolutions for large kernel sizes.
MIT License
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Propagation of error becomes large very fast #4

Closed dwromero closed 3 years ago

dwromero commented 3 years ago

Hi fkodom, I was trying to experiment with your fftconv implementation but I saw that just after 2 layers the error becomes quite large. Is it due to a malinterpretation of your code from my part? Might it be that the FFT + IFFT simply introduce too much error when concatenated?

Thank you in advance for your help! :) David

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SOLUTION: The problem is that the convolution was growing very largely, for which a difference of 1e-3 was not that big. In short the method works fantastically good :)

fkodom commented 3 years ago

Sorry for the delay here -- was away from work for a few days. Glad you figured it out!