Medix-AI/coqui-tts
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coqui-tts
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LR and time loggin on TB, checkpoint fix

This commit is contained in:
Eren Golge 2018-01-26 02:33:20 -08:00
parent 191e2b3f1e
commit 2eca96bfbb
2 changed files with 14 additions and 6 deletions
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4
config.json
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@ -11,7 +11,7 @@
"embedding_size": 256, "embedding_size": 256,
"text_cleaner": "english_cleaners", "text_cleaner": "english_cleaners",
"epochs": 200, "epochs": 2000,
"lr": 0.01, "lr": 0.01,
"lr_patience": 2, "lr_patience": 2,
"lr_decay": 0.5, "lr_decay": 0.5,
@ -20,7 +20,7 @@
"power": 1.5, "power": 1.5,
"r": 5, "r": 5,
"save_step": 1, "save_step": 200,
"data_path": "/data/shared/KeithIto/LJSpeech-1.0", "data_path": "/data/shared/KeithIto/LJSpeech-1.0",
"output_path": "result", "output_path": "result",
"log_dir": "/home/erogol/projects/TTS/logs/" "log_dir": "/home/erogol/projects/TTS/logs/"

16
train.py
View File

@ -42,7 +42,7 @@ def main(args):
pickle.dump(c, open(tmp_path, "wb")) pickle.dump(c, open(tmp_path, "wb"))
# setup tensorboard # setup tensorboard
LOG_DIR = c.log_dir LOG_DIR = OUT_PATH
tb = SummaryWriter(LOG_DIR) tb = SummaryWriter(LOG_DIR)
# Ctrl+C handler to remove empty experiment folder # Ctrl+C handler to remove empty experiment folder
@ -101,7 +101,7 @@ def main(args):
lr_scheduler = ReduceLROnPlateau(optimizer, factor=c.lr_decay, lr_scheduler = ReduceLROnPlateau(optimizer, factor=c.lr_decay,
patience=c.lr_patience, verbose=True) patience=c.lr_patience, verbose=True)
epoch_time = 0
for epoch in range(c.epochs): for epoch in range(c.epochs):
dataloader = DataLoader(dataset, batch_size=c.batch_size, dataloader = DataLoader(dataset, batch_size=c.batch_size,
@ -166,14 +166,20 @@ def main(args):
optimizer.step() optimizer.step()
time_per_step = time.time() - start_time step_time = time.time() - start_time
epoch_time += step_time
progbar.update(i+1, values=[('total_loss', loss.data[0]), progbar.update(i+1, values=[('total_loss', loss.data[0]),
('linear_loss', linear_loss.data[0]), ('linear_loss', linear_loss.data[0]),
('mel_loss', mel_loss.data[0])]) ('mel_loss', mel_loss.data[0])])
tb.add_scalar('Train/TotalLoss', loss.data[0], current_step) tb.add_scalar('Train/TotalLoss', loss.data[0], current_step)
tb.add_scalar('Train/LinearLoss', linear_loss.data[0], current_step) tb.add_scalar('Train/LinearLoss', linear_loss.data[0],
current_step)
tb.add_scalar('Train/MelLoss', mel_loss.data[0], current_step) tb.add_scalar('Train/MelLoss', mel_loss.data[0], current_step)
tb.add_scalar('LearningRate', optimizer.param_groups[0]['lr'],
current_step)
tb.add_scalar('Time/StepTime', step_time, current_step)
if current_step % c.save_step == 0: if current_step % c.save_step == 0:
checkpoint_path = 'checkpoint_{}.pth.tar'.format(current_step) checkpoint_path = 'checkpoint_{}.pth.tar'.format(current_step)
@ -188,6 +194,8 @@ def main(args):
checkpoint_path) checkpoint_path)
print("\n | > Checkpoint is saved : {}".format(checkpoint_path)) print("\n | > Checkpoint is saved : {}".format(checkpoint_path))
lr_scheduler.step(loss.data[0]) lr_scheduler.step(loss.data[0])
tb.add_scalar('Time/EpochTime', epoch_time, epoch)
epoch_time = 0
if __name__ == '__main__': if __name__ == '__main__':