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