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| author | Jean-Marc Valin <jmvalin@amazon.com> | 2023-09-28 23:11:59 +0300 |
|---|---|---|
| committer | Jean-Marc Valin <jmvalin@amazon.com> | 2023-09-28 23:15:03 +0300 |
| commit | 5fd10ee92112f6bfc62c599578f91717ab915d9b (patch) | |
| tree | cb68326020d7473d475e2e0b215d284fab2aeabb | |
| parent | 41c9e7ef60c00984293a4c8001726fdc752cef7d (diff) | |
LAR interpolation in adversarial training
| -rw-r--r-- | dnn/torch/fargan/adv_train_fargan.py | 6 |
1 files changed, 4 insertions, 2 deletions
diff --git a/dnn/torch/fargan/adv_train_fargan.py b/dnn/torch/fargan/adv_train_fargan.py index 23f5b2d0..5c5e974d 100644 --- a/dnn/torch/fargan/adv_train_fargan.py +++ b/dnn/torch/fargan/adv_train_fargan.py @@ -156,10 +156,12 @@ if __name__ == '__main__': optimizer.zero_grad() features = features.to(device) lpc = lpc.to(device) + lpc = lpc*(args.gamma**torch.arange(1,17, device=device)) + lpc = fargan.interp_lpc(lpc, 4) periods = periods.to(device) if True: target = target[:, :sequence_length*160] - lpc = lpc[:,:sequence_length,:] + lpc = lpc[:,:sequence_length*4,:] features = features[:,:sequence_length+4,:] periods = periods[:,:sequence_length+4] else: @@ -168,7 +170,7 @@ if __name__ == '__main__': features=features[::2,:] periods=periods[::2,:] target = target.to(device) - target = fargan.analysis_filter(target, lpc[:,:,:], gamma=args.gamma) + target = fargan.analysis_filter(target, lpc[:,:,:], nb_subframes=1, gamma=args.gamma) #nb_pre = random.randrange(1, 6) nb_pre = 2 |