forked from mrq/ai-voice-cloning
blame mrq/ai-voice-cloning#122
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@ -35,7 +35,7 @@ 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.utils.audio import load_audio, load_voice, load_voices, get_voice_dir, get_voices
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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, get_device_vram
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from tortoise.utils.device import get_device_name, set_device_name, get_device_count, get_device_vram, do_gc
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MODELS['dvae.pth'] = "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/3704aea61678e7e468a06d8eea121dba368a798e/.models/dvae.pth"
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@ -1547,13 +1547,6 @@ def get_dataset_list(dir="./training/"):
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def get_training_list(dir="./training/"):
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return sorted([f'./training/{d}/train.yaml' for d in os.listdir(dir) if os.path.isdir(os.path.join(dir, d)) and "train.yaml" in os.listdir(os.path.join(dir, d)) ])
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def do_gc():
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gc.collect()
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try:
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torch.cuda.empty_cache()
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except Exception as e:
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pass
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def pad(num, zeroes):
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return str(num).zfill(zeroes+1)
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@ -301,6 +301,7 @@ def setup_gradio():
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result_voices = get_voice_list("./results/")
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autoregressive_models = get_autoregressive_models()
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dataset_list = get_dataset_list()
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training_list = get_training_list()
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global GENERATE_SETTINGS_ARGS
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GENERATE_SETTINGS_ARGS = list(inspect.signature(generate_proxy).parameters.keys())[:-1]
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@ -492,8 +493,7 @@ def setup_gradio():
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with gr.Tab("Run Training"):
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with gr.Row():
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with gr.Column():
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training_list = get_training_list()
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training_configs = gr.Dropdown(label="Training Configuration", choices=training_list, value=training_list[0])
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training_configs = gr.Dropdown(label="Training Configuration", choices=training_list, value=training_list[0] if len(training_list) else "")
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refresh_configs = gr.Button(value="Refresh Configurations")
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training_output = gr.TextArea(label="Console Output", interactive=False, max_lines=8)
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verbose_training = gr.Checkbox(label="Verbose Console Output", value=True)
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