Implementation discrepancies with paper

[NeuronAppreciator]

Hi,

I'm trying to manually implement this in another language. Can you confirm this codebase is the one that produced the results in "Speech Denoising without Clean Training Data: a Noise2Noise Approach"? There are a few discrepancies I've noticed so far:

• A model complexity of (45//1.414) would seem to result in 31 encoder channels (and 62 for deeper ones), rather than 32 as described.
• The complex batchnorm module seems to implement batchnorm separately on real and imaginary components of the complex number, rather than using the whitening approach described in “Deep complex networks"
• Similarly the masking process seems to multiply real and imaginary components of the spectrogram separately rather than using complex multiplication.

I appreciate any insight you may have about these points.