maskgct / config /svc /diffusion.json
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{
"base_config": "config/svc/base.json",
"model": {
"condition_encoder": {
"merge_mode": "add",
// Prosody Features
"use_f0": true,
"use_uv": true,
"use_energy": true,
// Quantization (0 for not quantization)
"input_melody_dim": 1,
"n_bins_melody": 256,
"output_melody_dim": 384,
"input_loudness_dim": 1,
"n_bins_loudness": 256,
"output_loudness_dim": 384,
// Semantic Features
"use_whisper": false,
"use_contentvec": false,
"use_wenet": false,
"use_mert": false,
"whisper_dim": 1024,
"contentvec_dim": 256,
"mert_dim": 256,
"wenet_dim": 512,
"content_encoder_dim": 384,
// Speaker Features
"output_singer_dim": 384,
"singer_table_size": 512,
"use_spkid": true
},
"diffusion": {
"scheduler": "ddpm",
"scheduler_settings": {
"num_train_timesteps": 1000,
"beta_start": 1.0e-4,
"beta_end": 0.02,
"beta_schedule": "linear"
},
// 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": 384
},
"unet2d": {
"in_channels": 1,
"out_channels": 1,
"down_block_types": [
"CrossAttnDownBlock2D",
"CrossAttnDownBlock2D",
"CrossAttnDownBlock2D",
"DownBlock2D"
],
"mid_block_type": "UNetMidBlock2DCrossAttn",
"up_block_types": [
"UpBlock2D",
"CrossAttnUpBlock2D",
"CrossAttnUpBlock2D",
"CrossAttnUpBlock2D"
],
"only_cross_attention": false
}
}
},
"train": {
// Basic settings
"batch_size": 64,
"gradient_accumulation_step": 1,
"max_epoch": -1,
// -1 means no limit
"save_checkpoint_stride": [
5,
20
],
// unit is epoch
"keep_last": [
3,
-1
],
// -1 means infinite, if one number will broadcast
"run_eval": [
false,
true
],
// if one number will broadcast
// Fix the random seed
"random_seed": 10086,
// Batchsampler
"sampler": {
"holistic_shuffle": true,
"drop_last": true
},
// Dataloader
"dataloader": {
"num_worker": 32,
"pin_memory": true
},
// Trackers
"tracker": [
"tensorboard"
// "wandb",
// "cometml",
// "mlflow",
],
// Optimizer
"optimizer": "AdamW",
"adamw": {
"lr": 4.0e-4
// nn model lr
},
// LR Scheduler
"scheduler": "ReduceLROnPlateau",
"reducelronplateau": {
"factor": 0.8,
"patience": 10,
// unit is epoch
"min_lr": 1.0e-4
}
},
"inference": {
"diffusion": {
"scheduler": "pndm",
"scheduler_settings": {
"num_inference_timesteps": 1000
}
}
}
}