forked from mrq/ai-voice-cloning
finally added model refresh button, also searches in the training folder for outputted models so you don't even need to copy them
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1e0fec4358
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f6d0b66e10
12
src/utils.py
12
src/utils.py
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@ -838,7 +838,17 @@ def get_autoregressive_models(dir="./models/finetunes/"):
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if os.path.exists(halfp):
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if os.path.exists(halfp):
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base.append(halfp)
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base.append(halfp)
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return base + sorted([f'{dir}/{d}' for d in os.listdir(dir) if d[-4:] == ".pth" ])
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additionals = sorted([f'{dir}/{d}' for d in os.listdir(dir) if d[-4:] == ".pth" ])
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found = []
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for training in os.listdir(f'./training/'):
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if not os.path.isdir(f'./training/{training}/') or not os.path.isdir(f'./training/{training}/models/'):
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continue
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#found = found + sorted([ f'./training/{training}/model/{d}' for d in os.listdir(f'./training/{training}/models/') if d[-8:] == "_gpt.pth" ])
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models = sorted([ int(d[:-8]) for d in os.listdir(f'./training/{training}/models/') if d[-8:] == "_gpt.pth" ])
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found = found + [ f'./training/{training}/model/{d}_gpt.pth' for d in models ]
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#found.append(f'./training/{training}/model/{models[-1]}_gpt.pth')
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return base + additionals + found
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def get_dataset_list(dir="./training/"):
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def get_dataset_list(dir="./training/"):
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return sorted([d for d in os.listdir(dir) if os.path.isdir(os.path.join(dir, d)) and len(os.listdir(os.path.join(dir, d))) > 0 and "train.txt" in os.listdir(os.path.join(dir, d)) ])
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return sorted([d for d in os.listdir(dir) if os.path.isdir(os.path.join(dir, d)) and len(os.listdir(os.path.join(dir, d))) > 0 and "train.txt" in os.listdir(os.path.join(dir, d)) ])
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28
src/webui.py
28
src/webui.py
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@ -343,8 +343,9 @@ def setup_gradio():
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voice_list = get_voice_list(append_defaults=True)
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voice_list = get_voice_list(append_defaults=True)
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voice = gr.Dropdown(choices=voice_list, label="Voice", type="value", value=voice_list[0]) # it'd be very cash money if gradio was able to default to the first value in the list without this shit
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voice = gr.Dropdown(choices=voice_list, label="Voice", type="value", value=voice_list[0]) # it'd be very cash money if gradio was able to default to the first value in the list without this shit
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mic_audio = gr.Audio( label="Microphone Source", source="microphone", type="filepath" )
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mic_audio = gr.Audio( label="Microphone Source", source="microphone", type="filepath" )
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refresh_voices = gr.Button(value="Refresh Voice List")
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voice_latents_chunks = gr.Slider(label="Voice Chunks", minimum=1, maximum=64, value=1, step=1)
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voice_latents_chunks = gr.Slider(label="Voice Chunks", minimum=1, maximum=64, value=1, step=1)
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with gr.Row():
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refresh_voices = gr.Button(value="Refresh Voice List")
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recompute_voice_latents = gr.Button(value="(Re)Compute Voice Latents")
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recompute_voice_latents = gr.Button(value="(Re)Compute Voice Latents")
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def update_baseline_for_latents_chunks( voice ):
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def update_baseline_for_latents_chunks( voice ):
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@ -524,7 +525,26 @@ def setup_gradio():
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autoregressive_models = get_autoregressive_models()
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autoregressive_models = get_autoregressive_models()
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autoregressive_model_dropdown = gr.Dropdown(choices=autoregressive_models, label="Autoregressive Model", value=args.autoregressive_model if args.autoregressive_model else autoregressive_models[0])
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autoregressive_model_dropdown = gr.Dropdown(choices=autoregressive_models, label="Autoregressive Model", value=args.autoregressive_model if args.autoregressive_model else autoregressive_models[0])
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whisper_model_dropdown = gr.Dropdown(["tiny", "tiny.en", "base", "base.en", "small", "small.en", "medium", "medium.en", "large"], label="Whisper Model", value=args.whisper_model)
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whisper_model_dropdown = gr.Dropdown(["tiny", "tiny.en", "base", "base.en", "small", "small.en", "medium", "medium.en", "large"], label="Whisper Model", value=args.whisper_model)
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with gr.Row():
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autoregressive_models_update_button = gr.Button(value="Refresh Model List")
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gr.Button(value="Check for Updates").click(check_for_updates)
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gr.Button(value="(Re)Load TTS").click(
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reload_tts,
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inputs=autoregressive_model_dropdown,
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outputs=None
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)
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def update_model_list_proxy( val ):
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autoregressive_models = get_autoregressive_models()
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if val not in autoregressive_models:
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val = autoregressive_models[0]
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return gr.update( choices=autoregressive_models, value=val )
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autoregressive_models_update_button.click(
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update_model_list_proxy,
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inputs=autoregressive_model_dropdown,
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outputs=autoregressive_model_dropdown,
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)
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autoregressive_model_dropdown.change(
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autoregressive_model_dropdown.change(
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fn=update_autoregressive_model,
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fn=update_autoregressive_model,
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@ -537,12 +557,6 @@ def setup_gradio():
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outputs=None
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outputs=None
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)
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)
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gr.Button(value="Check for Updates").click(check_for_updates)
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gr.Button(value="(Re)Load TTS").click(
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reload_tts,
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inputs=autoregressive_model_dropdown,
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outputs=None
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)
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for i in exec_inputs:
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for i in exec_inputs:
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i.change( fn=update_args, inputs=exec_inputs )
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i.change( fn=update_args, inputs=exec_inputs )
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