Medix-AI/coqui-tts
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formatting for pylint

This commit is contained in:
Eren Golge 2019-08-16 14:22:35 +02:00
parent b22c7d4a29
commit 728b97da3a
2 changed files with 9 additions and 8 deletions
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3
config.json
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@ -78,6 +78,7 @@
"use_phonemes": true, // use phonemes instead of raw characters. It is suggested for better pronounciation. "use_phonemes": true, // use phonemes instead of raw characters. It is suggested for better pronounciation.
"phoneme_language": "en-us", // depending on your target language, pick one from https://github.com/bootphon/phonemizer#languages "phoneme_language": "en-us", // depending on your target language, pick one from https://github.com/bootphon/phonemizer#languages
"text_cleaner": "phoneme_cleaners", "text_cleaner": "phoneme_cleaners",
"use_speaker_embedding": false "use_speaker_embedding": false, // use speaker embedding to enable multi-speaker learning.
"style_wav_for_test": null // path to style wav file to be used in TacotronGST inference.
} }

14
train.py
View File

@ -190,7 +190,7 @@ def train(model, criterion, criterion_st, optimizer, optimizer_st, scheduler,
"LoaderTime:{:.2f} LR:{:.6f}".format( "LoaderTime:{:.2f} LR:{:.6f}".format(
num_iter, batch_n_iter, global_step, loss.item(), num_iter, batch_n_iter, global_step, loss.item(),
postnet_loss.item(), decoder_loss.item(), stop_loss.item(), postnet_loss.item(), decoder_loss.item(), stop_loss.item(),
grad_norm, grad_norm_st, avg_text_length, avg_spec_length, step_time, grad_norm, grad_norm_st, avg_text_length, avg_spec_length, step_time,
loader_time, current_lr), loader_time, current_lr),
flush=True) flush=True)
@ -259,9 +259,9 @@ def train(model, criterion, criterion_st, optimizer, optimizer_st, scheduler,
"AvgPostnetLoss:{:.5f} AvgDecoderLoss:{:.5f} " "AvgPostnetLoss:{:.5f} AvgDecoderLoss:{:.5f} "
"AvgStopLoss:{:.5f} EpochTime:{:.2f} " "AvgStopLoss:{:.5f} EpochTime:{:.2f} "
"AvgStepTime:{:.2f} AvgLoaderTime:{:.2f}".format(global_step, avg_total_loss, "AvgStepTime:{:.2f} AvgLoaderTime:{:.2f}".format(global_step, avg_total_loss,
avg_postnet_loss, avg_decoder_loss, avg_postnet_loss, avg_decoder_loss,
avg_stop_loss, epoch_time, avg_step_time, avg_stop_loss, epoch_time, avg_step_time,
avg_loader_time), avg_loader_time),
flush=True) flush=True)
# Plot Epoch Stats # Plot Epoch Stats
@ -539,12 +539,12 @@ def main(args): #pylint: disable=redefined-outer-name
if c.gradual_training is not None: if c.gradual_training is not None:
r, c.batch_size = gradual_training_scheduler(global_step, c) r, c.batch_size = gradual_training_scheduler(global_step, c)
c.r = r c.r = r
model.decoder._set_r(r) model.decoder.set_r(r)
print(" > Number of outputs per iteration:", model.decoder.r) print(" > Number of outputs per iteration:", model.decoder.r)
train_loss, global_step = train(model, criterion, criterion_st, train_loss, global_step = train(model, criterion, criterion_st,
optimizer, optimizer_st, scheduler, optimizer, optimizer_st, scheduler,
ap, global_step, epoch) ap, global_step, epoch)
val_loss = evaluate(model, criterion, criterion_st, ap, global_step, epoch) val_loss = evaluate(model, criterion, criterion_st, ap, global_step, epoch)
print( print(
" | > Training Loss: {:.5f} Validation Loss: {:.5f}".format( " | > Training Loss: {:.5f} Validation Loss: {:.5f}".format(