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from dataclasses import dataclass
@dataclass
class MelConfig:
sample_rate: int = 44100
n_fft: int = 2048
win_length: int = 2048
hop_length: int = 512
f_min: float = 0.0
f_max: float = None
pad: int = 0
n_mels: int = 128
power: float = 1.0
normalized: bool = False
center: bool = False
pad_mode: str = "reflect"
mel_scale: str = "htk"
def __post_init__(self):
if self.pad == 0:
self.pad = (self.n_fft - self.hop_length) // 2
@dataclass
class VocosConfig:
input_channels: int = 128
dim: int = 512
intermediate_dim: int = 1536
num_layers: int = 8
@dataclass
class TrainConfig:
train_dataset_path: str = './filelists/filelist.txt'
test_dataset_path: str = './filelists/filelist.txt'
batch_size: int = 22
learning_rate: float = 1e-4
num_epochs: int = 10000
model_save_path: str = './checkpoints'
log_dir: str = './runs'
log_interval: int = 128
warmup_steps: int = 200
segment_size = 20480 |