refac: remove trailing space and add custom theme
This commit is contained in:
parent
17acfee5d0
commit
a961141fe6
46
src/webui.py
46
src/webui.py
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@ -92,7 +92,7 @@ def generate_proxy(
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unload_tts()
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raise e
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return (
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outputs[0],
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gr.update(value=sample, visible=sample is not None),
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@ -131,7 +131,7 @@ def history_view_results( voice ):
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metadata, _ = read_generate_settings(f"{outdir}/{file}", read_latents=False)
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if metadata is None:
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continue
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values = []
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for k in HISTORY_HEADERS:
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v = file
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@ -185,7 +185,7 @@ def read_generate_settings_proxy(file, saveAs='.temp'):
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os.makedirs(outdir, exist_ok=True)
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with open(f'{outdir}/cond_latents.pth', 'wb') as f:
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f.write(latents)
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latents = f'{outdir}/cond_latents.pth'
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return (
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@ -229,7 +229,7 @@ def prepare_all_datasets( language, validation_text_length, validation_audio_len
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print("Processing:", voice)
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message = slice_dataset( voice, trim_silence=trim_silence, start_offset=slice_start_offset, end_offset=slice_end_offset, results=None, progress=progress )
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messages.append(message)
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for voice in voices:
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print("Processing:", voice)
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message = prepare_dataset( voice, use_segments=slice_audio, text_length=validation_text_length, audio_length=validation_audio_length, progress=progress )
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@ -239,7 +239,7 @@ def prepare_all_datasets( language, validation_text_length, validation_audio_len
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def prepare_dataset_proxy( voice, language, validation_text_length, validation_audio_length, skip_existings, slice_audio, trim_silence, slice_start_offset, slice_end_offset, progress=gr.Progress(track_tqdm=True) ):
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messages = []
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message = transcribe_dataset( voice=voice, language=language, skip_existings=skip_existings, progress=progress )
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messages.append(message)
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@ -355,7 +355,7 @@ def setup_gradio():
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voice_list_with_defaults = get_voice_list(append_defaults=True)
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voice_list = get_voice_list()
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result_voices = get_voice_list(args.results_folder)
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valle_models = get_valle_models()
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autoregressive_models = get_autoregressive_models()
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@ -371,7 +371,9 @@ def setup_gradio():
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arg = GENERATE_SETTINGS_ARGS[i]
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GENERATE_SETTINGS[arg] = None
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with gr.Blocks() as ui:
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with gr.Blocks(theme="freddyaboulton/dracula_revamped", css="footer { display: none!important}", title="Voice Clonning WebUI") as ui:
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gr.Markdown("## 🤗🎙️ Voice clonning ")
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gr.Markdown("Ai Voice clonning <a href='https://git.ecker.tech/terminator/ai-voice-cloning-terminator'>based on Tortoise</a>")
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with gr.Tab("Generate"):
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with gr.Row():
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with gr.Column():
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@ -402,7 +404,7 @@ def setup_gradio():
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outputs=GENERATE_SETTINGS["mic_audio"],
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)
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with gr.Column():
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preset = None
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preset = None
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GENERATE_SETTINGS["candidates"] = gr.Slider(value=1, minimum=1, maximum=6, step=1, label="Candidates", visible=args.tts_backend=="tortoise")
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GENERATE_SETTINGS["seed"] = gr.Number(value=0, precision=0, label="Seed", visible=args.tts_backend=="tortoise")
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@ -412,7 +414,7 @@ def setup_gradio():
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GENERATE_SETTINGS["diffusion_iterations"] = gr.Slider(value=30, minimum=0, maximum=512, step=1, label="Iterations", visible=args.tts_backend=="tortoise")
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GENERATE_SETTINGS["temperature"] = gr.Slider(value=0.95 if args.tts_backend=="vall-e" else 0.2, minimum=0, maximum=1, step=0.05, label="Temperature")
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show_experimental_settings = gr.Checkbox(label="Show Experimental Settings", visible=args.tts_backend=="tortoise")
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reset_generate_settings_button = gr.Button(value="Reset to Default")
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with gr.Column(visible=False) as col:
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@ -514,7 +516,7 @@ def setup_gradio():
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transcribe_button = gr.Button(value="Transcribe and Process")
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transcribe_all_button = gr.Button(value="Transcribe All")
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diarize_button = gr.Button(value="Diarize", visible=False)
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with gr.Row():
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slice_dataset_button = gr.Button(value="(Re)Slice Audio")
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prepare_dataset_button = gr.Button(value="(Re)Create Dataset")
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@ -534,7 +536,7 @@ def setup_gradio():
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TRAINING_SETTINGS["learning_rate"] = gr.Slider(label="Learning Rate", value=1e-5, minimum=0, maximum=1e-4, step=1e-6)
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TRAINING_SETTINGS["mel_lr_weight"] = gr.Slider(label="Mel LR Ratio", value=1.00, minimum=0, maximum=1)
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TRAINING_SETTINGS["text_lr_weight"] = gr.Slider(label="Text LR Ratio", value=0.01, minimum=0, maximum=1)
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with gr.Row(visible=args.tts_backend=="tortoise"):
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lr_schemes = list(LEARNING_RATE_SCHEMES.keys())
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TRAINING_SETTINGS["learning_rate_scheme"] = gr.Radio(lr_schemes, label="Learning Rate Scheme", value=lr_schemes[0], type="value")
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@ -567,7 +569,7 @@ def setup_gradio():
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TRAINING_SETTINGS["source_model"] = gr.Dropdown( choices=autoregressive_models, label="Source Model", type="value", value=autoregressive_models[0], visible=args.tts_backend=="tortoise" )
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TRAINING_SETTINGS["resume_state"] = gr.Textbox(label="Resume State Path", placeholder="./training/${voice}/finetune/training_state/${last_state}.state", visible=args.tts_backend=="tortoise")
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TRAINING_SETTINGS["voice"] = gr.Dropdown( choices=dataset_list, label="Dataset", type="value", value=dataset_list[0] if len(dataset_list) else "" )
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with gr.Row():
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@ -585,9 +587,9 @@ def setup_gradio():
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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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keep_x_past_checkpoints = gr.Slider(label="Keep X Previous States", minimum=0, maximum=8, value=0, step=1)
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with gr.Row():
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training_graph_x_min = gr.Number(label="X Min", precision=0, value=0)
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training_graph_x_max = gr.Number(label="X Max", precision=0, value=0)
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@ -598,8 +600,8 @@ def setup_gradio():
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start_training_button = gr.Button(value="Train")
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stop_training_button = gr.Button(value="Stop")
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reconnect_training_button = gr.Button(value="Reconnect")
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with gr.Column():
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training_loss_graph = gr.LinePlot(label="Training Metrics",
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x="it", # x="epoch",
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@ -658,7 +660,7 @@ def setup_gradio():
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EXEC_SETTINGS['results_folder'] = gr.Textbox(label="Results Folder", value=args.results_folder)
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# EXEC_SETTINGS['tts_backend'] = gr.Dropdown(TTSES, label="TTS Backend", value=args.tts_backend if args.tts_backend else TTSES[0])
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if args.tts_backend=="vall-e":
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with gr.Column():
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EXEC_SETTINGS['valle_model'] = gr.Dropdown(choices=valle_models, label="VALL-E Model Config", value=args.valle_model if args.valle_model else valle_models[0])
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@ -668,7 +670,7 @@ def setup_gradio():
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EXEC_SETTINGS['diffusion_model'] = gr.Dropdown(choices=diffusion_models, label="Diffusion Model", value=args.diffusion_model if args.diffusion_model else diffusion_models[0])
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EXEC_SETTINGS['vocoder_model'] = gr.Dropdown(VOCODERS, label="Vocoder", value=args.vocoder_model if args.vocoder_model else VOCODERS[-1])
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EXEC_SETTINGS['tokenizer_json'] = gr.Dropdown(tokenizer_jsons, label="Tokenizer JSON Path", value=args.tokenizer_json if args.tokenizer_json else tokenizer_jsons[0])
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EXEC_SETTINGS['training_default_halfp'] = TRAINING_SETTINGS['half_p']
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EXEC_SETTINGS['training_default_bnb'] = TRAINING_SETTINGS['bitsandbytes']
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@ -718,7 +720,7 @@ def setup_gradio():
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exec_inputs = list(EXEC_SETTINGS.values())
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for k in EXEC_SETTINGS:
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EXEC_SETTINGS[k].change( fn=update_args_proxy, inputs=exec_inputs )
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EXEC_SETTINGS['autoregressive_model'].change(
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fn=update_autoregressive_model,
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inputs=EXEC_SETTINGS['autoregressive_model'],
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@ -790,7 +792,7 @@ def setup_gradio():
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],
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outputs=GENERATE_SETTINGS['voice'],
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)
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GENERATE_SETTINGS['emotion'].change(
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fn=lambda value: gr.update(visible=value == "Custom"),
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inputs=GENERATE_SETTINGS['emotion'],
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@ -944,7 +946,7 @@ def setup_gradio():
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],
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outputs=prepare_dataset_output
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)
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training_refresh_dataset.click(
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lambda: gr.update(choices=get_dataset_list()),
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inputs=None,
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@ -966,7 +968,7 @@ def setup_gradio():
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if os.path.isfile('./config/generate.json'):
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ui.load(import_generate_settings_proxy, inputs=None, outputs=generate_settings)
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if args.check_for_updates:
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ui.load(check_for_updates)
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