terminator/ai-voice-cloning-terminator
1
1
Fork 0
forked from mrq/ai-voice-cloning
Code Pull Requests Activity

when you have three separate machines running and you test one one, but you accidentally revert changes because you then test on another

Browse Source
This commit is contained in:
mrq 2023-03-09 03:26:18 +00:00
parent ef75dba995
commit 3b4f4500d1
1 changed files with 5 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

7
src/utils.py
View File

@ -1149,7 +1149,7 @@ def prepare_dataset( files, outdir, language=None, skip_existings=False, progres
continue continue
if match[0] not in previous_list: if match[0] not in previous_list:
previous_list.append(f'{match[0]}.wav') previous_list.append(f'{match[0].split("/")[-1]}.wav')
for file in enumerate_progress(files, desc="Iterating through voice files", progress=progress): for file in enumerate_progress(files, desc="Iterating through voice files", progress=progress):
basename = os.path.basename(file) basename = os.path.basename(file)
@ -1257,12 +1257,13 @@ def optimize_training_settings( **kwargs ):
settings['batch_size'] = lines settings['batch_size'] = lines
messages.append(f"Batch size is larger than your dataset, clamping batch size to: {settings['batch_size']}") messages.append(f"Batch size is larger than your dataset, clamping batch size to: {settings['batch_size']}")
"""
if lines % settings['batch_size'] != 0: if lines % settings['batch_size'] != 0:
settings['batch_size'] = int(lines / settings['batch_size']) settings['batch_size'] = int(lines / settings['batch_size'])
if settings['batch_size'] == 0: if settings['batch_size'] == 0:
settings['batch_size'] = 1 settings['batch_size'] = 1
messages.append(f"Batch size not neatly divisible by dataset size, adjusting batch size to: {settings['batch_size']}") messages.append(f"Batch size not neatly divisible by dataset size, adjusting batch size to: {settings['batch_size']}")
"""
if settings['gradient_accumulation_size'] == 0: if settings['gradient_accumulation_size'] == 0:
settings['gradient_accumulation_size'] = 1 settings['gradient_accumulation_size'] = 1
@ -1399,6 +1400,8 @@ def save_training_settings( **kwargs ):
if settings['gpus'] > get_device_count(): if settings['gpus'] > get_device_count():
settings['gpus'] = get_device_count() settings['gpus'] = get_device_count()
settings['optimizer'] = 'adamw' if settings['gpus'] == 1 else 'adamw_zero'
LEARNING_RATE_SCHEMES = ["MultiStepLR", "CosineAnnealingLR_Restart"] LEARNING_RATE_SCHEMES = ["MultiStepLR", "CosineAnnealingLR_Restart"]
if 'learning_rate_scheme' not in settings or settings['learning_rate_scheme'] not in LEARNING_RATE_SCHEMES: if 'learning_rate_scheme' not in settings or settings['learning_rate_scheme'] not in LEARNING_RATE_SCHEMES:
settings['learning_rate_scheme'] = LEARNING_RATE_SCHEMES[0] settings['learning_rate_scheme'] = LEARNING_RATE_SCHEMES[0]