Awesome
Alias-Free-Torch
Simple torch module implementation of Alias-Free GAN.
This repository including
-
Alias-Free GAN style lowpass sinc filter @filter.py
-
Alias-Free GAN style up/downsample @resample.py
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Alias-Free activation @act.py
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and test codes @./test
Note: Since this repository is unofficial, filter and upsample could be different with official implementation.
Still working! If you notice some error or typo, please open new issue!
v0.0.6 is TESTED
UPDATE: You can download alias-free-torch from pip
python -m pip install alias-free-torch
Requirements
Due to torch.kaiser_window and torch.i0 are implemeted after 1.7.0, our repository need torch>=1.7.0.
- Pytorch>=1.7.0
For custom torch users, pip will not check torch version.
TODO
- 2d sinc filter
- 2d resample
- devide 1d and 2d modules
- pip packaging
- rewrite upsample
- Upsample pad size issue
- (Upsample) support calculation for [B,C,T/(H,W)] (now only supports [B,T/(H,W)] or [B,1,T/(H,W)])
- set filter as register buffer
- (Downsample & Filter) support calculation for [B,C,T/(H,W)] (now only supports [B,T/(H,W)] or [B,1,T/(H,W)])
- provide loadable ckpt for lower version of torch
- documentation
Test results 1d
| Filter sine | Filter noise |
|---|---|
 |  |
| upsample | downsample |
|---|---|
 |  |
 |  |
Test results 2d
| Filter L1 norm sine | Filter noise |
|---|---|
 |  |
| upsample | downsample |
|---|---|
 |  |
 |  |
References
- Alias-Free GAN
- adefossez/julius
- A. V. Oppenheim and R. W. Schafer. Discrete-Time Signal Processing. Pearson, International Edition, 3rd edition, 2010
Acknowledgement
This work is done at MINDsLab Inc.
Thanks to teammates at MINDsLab Inc.