71 lines
1.6 KiB
YAML
71 lines
1.6 KiB
YAML
model_name: "model_name"
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# If you want to use a specific dataset path, uncomment the following line.
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# Otherwise, the dataset path is `{dataset_root}/{model_name}`.
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# dataset_path: "your/dataset/path"
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resample:
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sampling_rate: 44100
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in_dir: "raw"
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out_dir: "wavs"
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preprocess_text:
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transcription_path: "esd.list"
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cleaned_path: ""
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train_path: "train.list"
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val_path: "val.list"
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config_path: "config.json"
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val_per_lang: 4
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max_val_total: 12
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clean: true
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bert_gen:
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config_path: "config.json"
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num_processes: 4
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device: "cuda"
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use_multi_device: false
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style_gen:
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config_path: "config.json"
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num_processes: 4
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device: "cuda"
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train_ms:
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env:
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MASTER_ADDR: "localhost"
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MASTER_PORT: 10086
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WORLD_SIZE: 1
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LOCAL_RANK: 0
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RANK: 0
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model_dir: "models" # The directory to save the model (for training), relative to `{dataset_root}/{model_name}`.
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config_path: "config.json"
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num_workers: 16
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spec_cache: True
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keep_ckpts: 1 # Set this to 0 to keep all checkpoints
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webui: # For `webui.py`, which is not supported yet in Style-Bert-VITS2.
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# 推理设备
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device: "cuda"
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# 模型路径
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model: "models/G_8000.pth"
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# 配置文件路径
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config_path: "config.json"
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# 端口号
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port: 7860
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# 是否公开部署，对外网开放
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share: false
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# 是否开启debug模式
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debug: false
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# 语种识别库，可选langid, fastlid
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language_identification_library: "langid"
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# server_fastapi's config
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server:
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port: 5000
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device: "cuda"
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language: "JP"
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limit: 100
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origins:
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- "*"
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