File size: 4,336 Bytes
8c92a11 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 |
{
"base_config": "config/comosvc.json",
"model_type": "DiffComoSVC",
"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
"log_dir": "[Your path to save logs and checkpoints]",
"preprocess": {
// TODO: Fill in the output data path
"processed_dir": "[Your path to save processed 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": {
"teacher_model_path":"[Your_teacher_model_checkpoint].bin",
"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
},
"comosvc":{
"distill": false,
// conformer encoder
"input_dim": 384,
"output_dim": 100,
"n_heads": 2,
"n_layers": 6,
"filter_channels":512,
"dropout":0.1,
// karras diffusion
"P_mean": -1.2,
"P_std": 1.2,
"sigma_data": 0.5,
"sigma_min": 0.002,
"sigma_max": 80,
"rho": 7,
"n_timesteps": 40,
},
"diffusion": {
// Diffusion steps encoder
"step_encoder": {
"dim_raw_embedding": 128,
"dim_hidden_layer": 512,
"activation": "SiLU",
"num_layer": 2,
"max_period": 10000
},
// Diffusion decoder
"model_type": "bidilconv",
// bidilconv, unet2d, TODO: unet1d
"bidilconv": {
"base_channel": 384,
"n_res_block": 20,
"conv_kernel_size": 3,
"dilation_cycle_length": 4,
// specially, 1 means no dilation
"conditioner_size": 100
}
}
},
"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
}
},
"inference": {
"comosvc": {
"inference_steps": 40
}
}
} |