An errors with running the preprocess.py

[dasstyx]

I'm trying to preprocess the VCTK dataset, and stuck on the 'Computing statistic quantities' step. When I copy from repo preprocessed_data files instead, the training run successful.

Firstly, there is a runtime error:

preprocessor.py

625: cont_lf0_lpf_norm = (cont_lf0_lpf - logf0s_mean_org) / logf0s_std_org
RuntimeWarning: invalid value encountered in true_divide

After applying a simple crutch to fix a value of logf0s_std_org, next error appear:

165: energy_mean = energy_scaler.mean_[0]
'StandardScaler' object has no attribute 'mean_'

win 10 conda python 3.6.15 all packages from the requirements.txt is installed

[dmzubr]

I'm trying to preprocess the VCTK dataset, and stuck on the 'Computing statistic quantities' step. When I copy from repo preprocessed_data files instead, the training run successful.

Firstly, there is a runtime error:

preprocessor.py

625: cont_lf0_lpf_norm = (cont_lf0_lpf - logf0s_mean_org) / logf0s_std_org
RuntimeWarning: invalid value encountered in true_divide

After applying a simple crutch to fix a value of logf0s_std_org, next error appear:

165: energy_mean = energy_scaler.mean_[0]
'StandardScaler' object has no attribute 'mean_'

win 10 conda python 3.6.15 all packages from the requirements.txt is installed

Faced the same problem.

What type of duration modeling do you use? Supervised or unsupervised?

• config/model.yaml -> duration_modeling.learn_alignment

It seems that preprocess pipeline contains actions for both.So - it missed some supervised (MFA outputs) artifacts.

[dasstyx]

I'm trying to preprocess the VCTK dataset, and stuck on the 'Computing statistic quantities' step. When I copy from repo preprocessed_data files instead, the training run successful. Firstly, there is a runtime error: preprocessor.py

625: cont_lf0_lpf_norm = (cont_lf0_lpf - logf0s_mean_org) / logf0s_std_org
RuntimeWarning: invalid value encountered in true_divide

After applying a simple crutch to fix a value of logf0s_std_org, next error appear:

165: energy_mean = energy_scaler.mean_[0]
'StandardScaler' object has no attribute 'mean_'

win 10 conda python 3.6.15 all packages from the requirements.txt is installed

Faced the same problem.

What type of duration modeling do you use? Supervised or unsupervised?

• config/model.yaml -> duration_modeling.learn_alignment

It seems that preprocess pipeline contains actions for both.So - it missed some supervised (MFA outputs) artifacts.

Unsupervised + liu2021

Yeah, I forgot to mention compute_f0_stats method, which produce an error when len(f0s) == 0. It's a bit weird.

God damnit, so I must use MFA anyway. Will try, thank you!