48 lines
1.5 KiB
YAML
48 lines
1.5 KiB
YAML
data:
|
|
sampling_rate: 44100
|
|
block_size: 512 # Equal to hop_length
|
|
duration: 2 # Audio duration during training, must be less than the duration of the shortest audio clip
|
|
encoder: 'vec768l12' # 'hubertsoft', 'vec256l9', 'vec768l12'
|
|
cnhubertsoft_gate: 10
|
|
encoder_sample_rate: 16000
|
|
encoder_hop_size: 320
|
|
encoder_out_channels: 768 # 256 if using 'hubertsoft'
|
|
training_files: "filelists/train.txt"
|
|
validation_files: "filelists/val.txt"
|
|
extensions: # List of extension included in the data collection
|
|
- wav
|
|
model:
|
|
type: 'Diffusion'
|
|
n_layers: 20
|
|
n_chans: 512
|
|
n_hidden: 256
|
|
use_pitch_aug: true
|
|
n_spk: 1 # max number of different speakers
|
|
device: cuda
|
|
vocoder:
|
|
type: 'nsf-hifigan'
|
|
ckpt: 'pretrain/nsf_hifigan/model'
|
|
infer:
|
|
speedup: 10
|
|
method: 'dpm-solver' # 'pndm' or 'dpm-solver'
|
|
env:
|
|
expdir: logs/44k/diffusion
|
|
gpu_id: 0
|
|
train:
|
|
num_workers: 2 # If your cpu and gpu are both very strong, set to 0 may be faster!
|
|
amp_dtype: fp32 # fp32, fp16 or bf16 (fp16 or bf16 may be faster if it is supported by your gpu)
|
|
batch_size: 48
|
|
cache_all_data: true # Save Internal-Memory or Graphics-Memory if it is false, but may be slow
|
|
cache_device: 'cpu' # Set to 'cuda' to cache the data into the Graphics-Memory, fastest speed for strong gpu
|
|
cache_fp16: true
|
|
epochs: 100000
|
|
interval_log: 10
|
|
interval_val: 2000
|
|
interval_force_save: 10000
|
|
lr: 0.0002
|
|
decay_step: 100000
|
|
gamma: 0.5
|
|
weight_decay: 0
|
|
save_opt: false
|
|
spk:
|
|
'nyaru': 0 |