Spaces:
Running
on
A10G
Running
on
A10G
| defaults: | |
| - base | |
| - _self_ | |
| project: vq-gan-pretrain | |
| # Lightning Trainer | |
| trainer: | |
| accelerator: gpu | |
| devices: auto | |
| precision: bf16-mixed | |
| max_steps: 1_000_000 | |
| val_check_interval: 5000 | |
| strategy: ddp_find_unused_parameters_true | |
| sample_rate: 44100 | |
| hop_length: 512 | |
| num_mels: 128 | |
| n_fft: 2048 | |
| win_length: 2048 | |
| # Dataset Configuration | |
| train_dataset: | |
| _target_: torch.utils.data.ConcatDataset | |
| datasets: | |
| - _target_: fish_speech.datasets.vqgan.VQGANDataset | |
| filelist: data/gigaspeech/vq_train_filelist.txt | |
| sample_rate: ${sample_rate} | |
| hop_length: ${hop_length} | |
| slice_frames: 512 | |
| - _target_: fish_speech.datasets.vqgan.VQGANDataset | |
| filelist: data/sft/vq_train_filelist.txt | |
| sample_rate: ${sample_rate} | |
| hop_length: ${hop_length} | |
| slice_frames: 512 | |
| val_dataset: | |
| _target_: fish_speech.datasets.vqgan.VQGANDataset | |
| filelist: data/sft/vq_val_filelist.txt | |
| sample_rate: ${sample_rate} | |
| hop_length: ${hop_length} | |
| data: | |
| _target_: fish_speech.datasets.vqgan.VQGANDataModule | |
| train_dataset: ${train_dataset} | |
| val_dataset: ${val_dataset} | |
| num_workers: 4 | |
| batch_size: 32 | |
| val_batch_size: 32 | |
| # Model Configuration | |
| model: | |
| _target_: fish_speech.models.vqgan.VQGAN | |
| sampling_rate: ${sample_rate} | |
| weight_adv: 0.2 | |
| weight_vq: 1.0 | |
| weight_mel: 1.0 | |
| freeze_encoder: false | |
| encoder: | |
| _target_: fish_speech.models.vqgan.modules.wavenet.WaveNet | |
| input_channels: ${num_mels} | |
| residual_channels: 768 | |
| residual_layers: 20 | |
| dilation_cycle: 4 | |
| quantizer: | |
| _target_: fish_speech.models.vqgan.modules.fsq.DownsampleFiniteScalarQuantize | |
| input_dim: 768 | |
| n_codebooks: 1 | |
| n_groups: 2 | |
| levels: [8, 5, 5, 5] | |
| decoder: | |
| _target_: fish_speech.models.vqgan.modules.wavenet.WaveNet | |
| output_channels: ${num_mels} | |
| residual_channels: 768 | |
| residual_layers: 20 | |
| dilation_cycle: 4 | |
| condition_channels: 768 | |
| discriminator: | |
| _target_: fish_speech.models.vqgan.modules.discriminator.Discriminator | |
| vocoder: | |
| _target_: fish_speech.models.vqgan.modules.firefly.FireflyBase | |
| ckpt_path: null # You may download the pretrained vocoder and set the path here | |
| encode_mel_transform: | |
| _target_: fish_speech.models.vqgan.spectrogram.LogMelSpectrogram | |
| sample_rate: ${sample_rate} | |
| n_fft: ${n_fft} | |
| hop_length: ${hop_length} | |
| win_length: ${win_length} | |
| n_mels: ${num_mels} | |
| f_min: 0.0 | |
| f_max: 8000.0 | |
| gt_mel_transform: | |
| _target_: fish_speech.models.vqgan.spectrogram.LogMelSpectrogram | |
| sample_rate: ${sample_rate} | |
| n_fft: ${n_fft} | |
| hop_length: ${hop_length} | |
| win_length: ${win_length} | |
| n_mels: ${num_mels} | |
| optimizer: | |
| _target_: torch.optim.AdamW | |
| _partial_: true | |
| lr: 1e-4 | |
| betas: [0.8, 0.99] | |
| eps: 1e-5 | |
| weight_decay: 0.01 | |
| lr_scheduler: | |
| _target_: torch.optim.lr_scheduler.LambdaLR | |
| _partial_: true | |
| lr_lambda: | |
| _target_: fish_speech.scheduler.get_cosine_schedule_with_warmup_lr_lambda | |
| _partial_: true | |
| num_warmup_steps: 100 | |
| num_training_steps: ${trainer.max_steps} | |
| final_lr_ratio: 0 | |
| callbacks: | |
| model_summary: | |
| _target_: lightning.pytorch.callbacks.ModelSummary | |
| max_depth: 1 | |
| model_checkpoint: | |
| every_n_train_steps: ${trainer.val_check_interval} | |
| grad_norm_monitor: | |
| sub_module: | |
| - encoder | |
| - decoder | |
| - quantizer | |
| - discriminator | |