egs/svc/TransformerSVC/exp_config.json

{
    "base_config": "config/transformer.json",
    "model_type": "TransformerSVC",
    "dataset": [
        "m4singer",
        "opencpop",
        "opensinger",
        "svcc",
        "vctk"
    ],
    "dataset_path": {
        // TODO: Fill in your dataset path
        "m4singer": "[M4Singer dataset path]",
        "opencpop": "[Opencpop dataset path]",
        "opensinger": "[OpenSinger dataset path]",
        "svcc": "[SVCC dataset path]",
        "vctk": "[VCTK dataset path]"
    },
    // TODO: Fill in the output log path. The default value is "Amphion/ckpts/svc"
    "log_dir": "ckpts/svc",
    "preprocess": {
        // TODO: Fill in the output data path. The default value is "Amphion/data"
        "processed_dir": "data",
        // Config for features extraction
        "extract_mel": true,
        "extract_pitch": true,
        "extract_energy": true,
        "extract_whisper_feature": true,
        "extract_contentvec_feature": true,
        "extract_wenet_feature": false,
        "whisper_batch_size": 30, // decrease it if your GPU is out of memory
        "contentvec_batch_size": 1,
        // Fill in the content-based pretrained model's path
        "contentvec_file": "pretrained/contentvec/checkpoint_best_legacy_500.pt",
        "wenet_model_path": "pretrained/wenet/20220506_u2pp_conformer_exp/final.pt",
        "wenet_config": "pretrained/wenet/20220506_u2pp_conformer_exp/train.yaml",
        "whisper_model": "medium",
        "whisper_model_path": "pretrained/whisper/medium.pt",
        // Config for features usage
        "use_mel": true,
        "use_min_max_norm_mel": true,
        "use_frame_pitch": true,
        "use_frame_energy": true,
        "use_spkid": true,
        "use_whisper": true,
        "use_contentvec": true,
        "use_wenet": false,
        "n_mel": 100,
        "sample_rate": 24000
    },
    "model": {
        "condition_encoder": {
            // Config for features usage
            "use_whisper": true,
            "use_contentvec": true,
            "use_wenet": false,
            "whisper_dim": 1024,
            "contentvec_dim": 256,
            "wenet_dim": 512,
            "use_singer_encoder": false,
            "pitch_min": 50,
            "pitch_max": 1100
        },
        "transformer": {
            // 'conformer' or 'transformer'
            "type": "conformer",
            "input_dim": 384,
            "output_dim": 100,
            "n_heads": 2,
            "n_layers": 6,
            "filter_channels": 512,
            "dropout": 0.1,
        }
    },
    "train": {
        "batch_size": 64,
        "gradient_accumulation_step": 1,
        "max_epoch": -1, // -1 means no limit
        "save_checkpoint_stride": [
            50,
            50
        ],
        "keep_last": [
            5,
            -1
        ],
        "run_eval": [
            false,
            true
        ],
        "adamw": {
            "lr": 4.0e-4
        },
        "reducelronplateau": {
            "factor": 0.8,
            "patience": 10,
            "min_lr": 1.0e-4
        },
        "dataloader": {
            "num_worker": 8,
            "pin_memory": true
        },
        "sampler": {
            "holistic_shuffle": false,
            "drop_last": true
        }
    }
}