updated vall-e training template to use path-based speakers because it would just have a batch/epoch size of 1 otherwise; revert hardcoded 'spit processed dataset to this path' from my training rig to spit it out in a sane spot
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@ -23,7 +23,7 @@ dataset:
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max_prompts: 3
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max_prompts: 3
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prompt_duration: 3.0
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prompt_duration: 3.0
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sample_type: speaker
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sample_type: path
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tasks_list: ["tts"] # ["tts", "ns", "sr", "tse", "cse", "nse", "tts"]
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tasks_list: ["tts"] # ["tts", "ns", "sr", "tse", "cse", "nse", "tts"]
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12
src/utils.py
12
src/utils.py
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@ -2662,11 +2662,11 @@ def prepare_dataset( voice, use_segments=False, text_length=0, audio_length=0, p
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if culled or args.tts_backend != "vall-e":
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if culled or args.tts_backend != "vall-e":
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continue
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continue
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# os.makedirs(f'{indir}/valle/', exist_ok=True)
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os.makedirs(f'{indir}/valle/', exist_ok=True)
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os.makedirs(f'./training/valle/data/{voice}/', exist_ok=True)
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#os.makedirs(f'./training/valle/data/{voice}/', exist_ok=True)
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#phn_file = f'{indir}/valle/{file.replace(f".{extension}",".phn.txt")}'
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phn_file = f'{indir}/valle/{file.replace(f".{extension}",".phn.txt")}'
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phn_file = f'./training/valle/data/{voice}/{file.replace(f".{extension}",".phn.txt")}'
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#phn_file = f'./training/valle/data/{voice}/{file.replace(f".{extension}",".phn.txt")}'
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if not os.path.exists(phn_file):
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if not os.path.exists(phn_file):
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jobs['phonemize'][0].append(phn_file)
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jobs['phonemize'][0].append(phn_file)
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jobs['phonemize'][1].append(normalized)
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jobs['phonemize'][1].append(normalized)
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@ -2676,8 +2676,8 @@ def prepare_dataset( voice, use_segments=False, text_length=0, audio_length=0, p
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print("Phonemized:", file, normalized, text)
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print("Phonemized:", file, normalized, text)
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"""
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"""
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#qnt_file = f'{indir}/valle/{file.replace(f".{extension}",".qnt.pt")}'
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qnt_file = f'{indir}/valle/{file.replace(f".{extension}",".qnt.pt")}'
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qnt_file = f'./training/valle/data/{voice}/{file.replace(f".{extension}",".qnt.pt")}'
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#qnt_file = f'./training/valle/data/{voice}/{file.replace(f".{extension}",".qnt.pt")}'
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if 'error' not in result:
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if 'error' not in result:
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if not quantize_in_memory and not os.path.exists(path):
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if not quantize_in_memory and not os.path.exists(path):
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message = f"Missing segment, skipping... {file}"
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message = f"Missing segment, skipping... {file}"
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@ -411,7 +411,7 @@ def setup_gradio():
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GENERATE_SETTINGS["num_autoregressive_samples"] = gr.Slider(value=16, minimum=2, maximum=2048 if args.tts_backend=="vall-e" else 512, step=1, label="Samples", visible=args.tts_backend!="bark")
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GENERATE_SETTINGS["num_autoregressive_samples"] = gr.Slider(value=16, minimum=2, maximum=2048 if args.tts_backend=="vall-e" else 512, step=1, label="Samples", visible=args.tts_backend!="bark")
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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["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=0.1, label="Temperature")
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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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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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reset_generate_settings_button = gr.Button(value="Reset to Default")
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