oops
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src/utils.py
12
src/utils.py
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@ -34,7 +34,7 @@ from datetime import timedelta
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from tortoise.api import TextToSpeech, MODELS, get_model_path, pad_or_truncate
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from tortoise.api import TextToSpeech, MODELS, get_model_path, pad_or_truncate
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from tortoise.utils.audio import load_audio, load_voice, load_voices, get_voice_dir
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from tortoise.utils.audio import load_audio, load_voice, load_voices, get_voice_dir
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from tortoise.utils.text import split_and_recombine_text
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from tortoise.utils.text import split_and_recombine_text
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from tortoise.utils.device import get_device_name, set_device_name, get_device_count
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from tortoise.utils.device import get_device_name, set_device_name, get_device_count, get_device_vram
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MODELS['dvae.pth'] = "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/3704aea61678e7e468a06d8eea121dba368a798e/.models/dvae.pth"
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MODELS['dvae.pth'] = "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/3704aea61678e7e468a06d8eea121dba368a798e/.models/dvae.pth"
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@ -1278,6 +1278,8 @@ def optimize_training_settings( **kwargs ):
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messages.append(f"Batch size is not evenly divisible by the gradient accumulation size, adjusting gradient accumulation size to: {settings['gradient_accumulation_size']}")
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messages.append(f"Batch size is not evenly divisible by the gradient accumulation size, adjusting gradient accumulation size to: {settings['gradient_accumulation_size']}")
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print("VRAM", get_device_vram())
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iterations = calc_iterations(epochs=settings['epochs'], lines=lines, batch_size=settings['batch_size'])
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iterations = calc_iterations(epochs=settings['epochs'], lines=lines, batch_size=settings['batch_size'])
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if settings['epochs'] < settings['print_rate']:
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if settings['epochs'] < settings['print_rate']:
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@ -1306,7 +1308,7 @@ def optimize_training_settings( **kwargs ):
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else:
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else:
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messages.append("Half Precision requested. Please note this is ! EXPERIMENTAL !")
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messages.append("Half Precision requested. Please note this is ! EXPERIMENTAL !")
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if not os.path.exists(get_halfp_model_path()):
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if not os.path.exists(get_halfp_model_path()):
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convert_to_halfp()
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convert_to_halfp()
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messages.append(f"For {settings['epochs']} epochs with {lines} lines in batches of {settings['batch_size']}, iterating for {iterations} steps ({int(iterations / settings['epochs'])} steps per epoch)")
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messages.append(f"For {settings['epochs']} epochs with {lines} lines in batches of {settings['batch_size']}, iterating for {iterations} steps ({int(iterations / settings['epochs'])} steps per epoch)")
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@ -1828,10 +1830,12 @@ def import_generate_settings(file="./config/generate.json"):
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res = []
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res = []
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if GENERATE_SETTINGS_ARGS is not None:
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if GENERATE_SETTINGS_ARGS is not None:
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for k in GENERATE_SETTINGS_ARGS:
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for k in GENERATE_SETTINGS_ARGS:
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res.append(defaults[k] if not settings or settings[k] is None else settings[k])
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if k not in defaults:
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continue
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res.append(defaults[k] if not settings or k not in settings or not settings[k] is None else settings[k])
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else:
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else:
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for k in defaults:
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for k in defaults:
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res.append(defaults[k] if not settings or settings[k] is None else settings[k])
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res.append(defaults[k] if not settings or k not in settings or not settings[k] is None else settings[k])
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return tuple(res)
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return tuple(res)
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@ -1 +1 @@
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Subproject commit cc36c0997c8711889ef8028002fc9e41abd5c5f0
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Subproject commit bbeee40ab3ee39dd16a1ebd2388bf82402776664
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