I finally figured out how to fix gr.Dropdown.change, so a lot of dumb UI decisions are fixed and makes sense
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7d1936adad
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bbc2d26289
58
src/utils.py
58
src/utils.py
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@ -38,11 +38,13 @@ MODELS['dvae.pth'] = "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/370
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args = None
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tts = None
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tts_loading = False
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webui = None
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voicefixer = None
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whisper_model = None
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training_process = None
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def generate(
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text,
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delimiter,
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@ -70,15 +72,17 @@ def generate(
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global args
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global tts
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if not tts:
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# should check if it's loading or unloaded, and load it if it's unloaded
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raise Exception("TTS is uninitialized or still initializing...")
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do_gc()
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unload_whisper()
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unload_voicefixer()
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if not tts:
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# should check if it's loading or unloaded, and load it if it's unloaded
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if tts_loading:
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raise Exception("TTS is still initializing...")
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load_tts()
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do_gc()
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if voice != "microphone":
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voices = [voice]
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else:
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@ -365,13 +369,15 @@ def cancel_generate():
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def compute_latents(voice, voice_latents_chunks, progress=gr.Progress(track_tqdm=True)):
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global tts
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global args
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if not tts:
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raise Exception("TTS is uninitialized or still initializing...")
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unload_whisper()
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unload_voicefixer()
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if not tts:
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if tts_loading:
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raise Exception("TTS is still initializing...")
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load_tts()
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voice_samples, conditioning_latents = load_voice(voice, load_latents=False)
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if voice_samples is None:
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@ -953,10 +959,13 @@ def reset_generation_settings():
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f.write(json.dumps({}, indent='\t') )
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return import_generate_settings()
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def read_generate_settings(file, read_latents=True, read_json=True):
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def read_generate_settings(file, read_latents=True):
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j = None
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latents = None
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if isinstance(file, list) and len(file) == 1:
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file = file[0]
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if file is not None:
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if hasattr(file, 'name'):
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file = file.name
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@ -981,24 +990,33 @@ def read_generate_settings(file, read_latents=True, read_json=True):
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if "time" in j:
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j["time"] = "{:.3f}".format(j["time"])
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return (
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j,
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latents,
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)
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def load_tts(restart=False):
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def load_tts( restart=False, model=None ):
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global args
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global tts
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if restart:
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unload_tts()
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if model:
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args.autoregressive_model = model
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print(f"Loading TorToiSe... (using model: {args.autoregressive_model})")
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tts_loading = True
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try:
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tts = TextToSpeech(minor_optimizations=not args.low_vram, autoregressive_model_path=args.autoregressive_model)
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except Exception as e:
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tts = TextToSpeech(minor_optimizations=not args.low_vram)
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load_autoregressive_model(args.autoregressive_model)
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tts_loading = False
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get_model_path('dvae.pth')
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print("Loaded TorToiSe, ready for generation.")
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@ -1015,17 +1033,24 @@ def unload_tts():
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tts = None
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do_gc()
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def reload_tts():
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setup_tortoise(restart=True)
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def reload_tts( model=None ):
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load_tts( restart=True, model=model )
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def update_autoregressive_model(autoregressive_model_path):
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if not autoregressive_model_path or not os.path.exists(autoregressive_model_path):
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return
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args.autoregressive_model = autoregressive_model_path
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save_args_settings()
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print(f'Stored autoregressive model to settings: {autoregressive_model_path}')
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global tts
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if not tts:
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raise Exception("TTS is uninitialized or still initializing...")
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if tts_loading:
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raise Exception("TTS is still initializing...")
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load_tts( model=autoregressive_model_path )
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return # redundant to proceed onward
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print(f"Loading model: {autoregressive_model_path}")
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@ -1099,6 +1124,9 @@ def unload_whisper():
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do_gc()
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def update_whisper_model(name, progress=None):
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if not name:
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return
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global whisper_model
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if whisper_model:
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unload_whisper()
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82
src/webui.py
82
src/webui.py
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@ -82,7 +82,6 @@ def run_generation(
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outputs[0],
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gr.update(value=sample, visible=sample is not None),
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gr.update(choices=outputs, value=outputs[0], visible=len(outputs) > 1, interactive=True),
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gr.update(visible=len(outputs) > 1),
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gr.update(value=stats, visible=True),
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)
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@ -170,6 +169,8 @@ def read_generate_settings_proxy(file, saveAs='.temp'):
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latents = f'{outdir}/cond_latents.pth'
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print(j, latents)
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return (
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gr.update(value=j, visible=j is not None),
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gr.update(visible=j is not None),
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@ -244,12 +245,6 @@ def update_voices():
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def history_copy_settings( voice, file ):
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return import_generate_settings( f"./results/{voice}/{file}" )
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def update_model_settings( autoregressive_model, whisper_model ):
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update_autoregressive_model(autoregressive_model)
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update_whisper_model(whisper_model)
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save_args_settings()
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def setup_gradio():
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global args
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global ui
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@ -318,19 +313,30 @@ def setup_gradio():
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generation_results = gr.Dataframe(label="Results", headers=["Seed", "Time"], visible=False)
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source_sample = gr.Audio(label="Source Sample", visible=False)
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output_audio = gr.Audio(label="Output")
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candidates_list = gr.Dropdown(label="Candidates", type="value", visible=False)
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output_pick = gr.Button(value="Select Candidate", visible=False)
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candidates_list = gr.Dropdown(label="Candidates", type="value", visible=False, choices=[""], value="")
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# output_pick = gr.Button(value="Select Candidate", visible=False)
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def change_candidate( val ):
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if not val:
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return
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print(val)
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return val
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candidates_list.change(
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fn=change_candidate,
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inputs=candidates_list,
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outputs=output_audio,
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)
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with gr.Tab("History"):
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with gr.Row():
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with gr.Column():
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history_info = gr.Dataframe(label="Results", headers=list(history_headers.keys()))
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with gr.Row():
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with gr.Column():
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history_voices = gr.Dropdown(choices=get_voice_list("./results/"), label="Voice", type="value")
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history_view_results_button = gr.Button(value="View Files")
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result_voices = get_voice_list("./results/")
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history_voices = gr.Dropdown(choices=result_voices, label="Voice", type="value", value=result_voices[0])
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with gr.Column():
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history_results_list = gr.Dropdown(label="Results",type="value", interactive=True)
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history_view_result_button = gr.Button(value="View File")
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history_results_list = gr.Dropdown(label="Results",type="value", interactive=True, value="")
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with gr.Column():
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history_audio = gr.Audio()
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history_copy_settings_button = gr.Button(value="Copy Settings")
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@ -407,10 +413,10 @@ def setup_gradio():
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gr.Checkbox(label="Low VRAM", value=args.low_vram),
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gr.Checkbox(label="Embed Output Metadata", value=args.embed_output_metadata),
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gr.Checkbox(label="Slimmer Computed Latents", value=args.latents_lean_and_mean),
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gr.Checkbox(label="Voice Fixer", value=args.voice_fixer),
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gr.Checkbox(label="Use Voice Fixer on Generated Output", value=args.voice_fixer),
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gr.Checkbox(label="Use CUDA for Voice Fixer", value=args.voice_fixer_use_cuda),
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gr.Checkbox(label="Force CPU for Conditioning Latents", value=args.force_cpu_for_conditioning_latents),
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gr.Checkbox(label="Defer TTS Load", value=args.defer_tts_load),
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gr.Checkbox(label="Do Not Load TTS On Startup", value=args.defer_tts_load),
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gr.Textbox(label="Device Override", value=args.device_override),
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]
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with gr.Column():
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@ -421,12 +427,28 @@ def setup_gradio():
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gr.Slider(label="Ouptut Volume", minimum=0, maximum=2, value=args.output_volume),
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]
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autoregressive_model_dropdown = gr.Dropdown(get_autoregressive_models(), label="Autoregressive Model", value=args.autoregressive_model)
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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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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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save_settings_button = gr.Button(value="Save Settings")
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autoregressive_model_dropdown.change(
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fn=update_autoregressive_model,
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inputs=autoregressive_model_dropdown,
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outputs=None
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)
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whisper_model_dropdown.change(
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fn=update_whisper_model,
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inputs=whisper_model_dropdown,
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outputs=None
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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(reload_tts)
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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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i.change( fn=update_args, inputs=exec_inputs )
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@ -457,7 +479,7 @@ def setup_gradio():
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experimental_checkboxes,
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]
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history_view_results_button.click(
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history_voices.change(
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fn=history_view_results,
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inputs=history_voices,
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outputs=[
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@ -465,7 +487,7 @@ def setup_gradio():
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history_results_list,
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]
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)
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history_view_result_button.click(
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history_results_list.change(
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fn=lambda voice, file: f"./results/{voice}/{file}",
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inputs=[
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history_voices,
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@ -531,20 +553,14 @@ def setup_gradio():
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]
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)
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output_pick.click(
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lambda x: x,
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inputs=candidates_list,
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outputs=output_audio,
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)
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submit.click(
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lambda: (gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)),
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outputs=[source_sample, candidates_list, output_pick, generation_results],
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lambda: (gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)),
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outputs=[source_sample, candidates_list, generation_results],
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)
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submit_event = submit.click(run_generation,
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inputs=input_settings,
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outputs=[output_audio, source_sample, candidates_list, output_pick, generation_results],
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outputs=[output_audio, source_sample, candidates_list, generation_results],
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)
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@ -603,14 +619,6 @@ def setup_gradio():
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outputs=save_yaml_output #console_output
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)
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save_settings_button.click(update_model_settings,
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inputs=[
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autoregressive_model_dropdown,
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whisper_model_dropdown,
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],
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outputs=None
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)
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if os.path.isfile('./config/generate.json'):
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ui.load(import_generate_settings, inputs=None, outputs=input_settings)
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