Spaces:
Runtime error
Runtime error
# modified from https://github.com/yangdongchao/SoundStorm/blob/master/soundstorm/s1/AR/data/data_module.py | |
# reference: https://github.com/lifeiteng/vall-e | |
from pytorch_lightning import LightningDataModule | |
from AR.data.bucket_sampler import DistributedBucketSampler | |
from AR.data.dataset import Text2SemanticDataset | |
from torch.utils.data import DataLoader | |
class Text2SemanticDataModule(LightningDataModule): | |
def __init__( | |
self, | |
config, | |
train_semantic_path, | |
train_phoneme_path, | |
dev_semantic_path=None, | |
dev_phoneme_path=None, | |
): | |
super().__init__() | |
self.config = config | |
self.train_semantic_path = train_semantic_path | |
self.train_phoneme_path = train_phoneme_path | |
self.dev_semantic_path = dev_semantic_path | |
self.dev_phoneme_path = dev_phoneme_path | |
self.num_workers = self.config["data"]["num_workers"] | |
def prepare_data(self): | |
pass | |
def setup(self, stage=None, output_logs=False): | |
self._train_dataset = Text2SemanticDataset( | |
phoneme_path=self.train_phoneme_path, | |
semantic_path=self.train_semantic_path, | |
max_sec=self.config["data"]["max_sec"], | |
pad_val=self.config["data"]["pad_val"], | |
) | |
self._dev_dataset = self._train_dataset | |
# self._dev_dataset = Text2SemanticDataset( | |
# phoneme_path=self.dev_phoneme_path, | |
# semantic_path=self.dev_semantic_path, | |
# max_sample=self.config['data']['max_eval_sample'], | |
# max_sec=self.config['data']['max_sec'], | |
# pad_val=self.config['data']['pad_val']) | |
def train_dataloader(self): | |
batch_size=self.config["train"]["batch_size"]//2 if self.config["train"].get("if_dpo",False)==True else self.config["train"]["batch_size"] | |
batch_size = max(min(batch_size,len(self._train_dataset)//4),1)#防止不保存 | |
sampler = DistributedBucketSampler(self._train_dataset, batch_size=batch_size) | |
return DataLoader( | |
self._train_dataset, | |
batch_size=batch_size, | |
sampler=sampler, | |
collate_fn=self._train_dataset.collate, | |
num_workers=self.num_workers, | |
persistent_workers=True, | |
prefetch_factor=16, | |
) | |
def val_dataloader(self): | |
return DataLoader( | |
self._dev_dataset, | |
batch_size=1, | |
shuffle=False, | |
collate_fn=self._train_dataset.collate, | |
num_workers=max(self.num_workers, 12), | |
persistent_workers=True, | |
prefetch_factor=16, | |
) | |
# 这个会使用到嘛? | |
def test_dataloader(self): | |
return DataLoader( | |
self._dev_dataset, | |
batch_size=1, | |
shuffle=False, | |
collate_fn=self._train_dataset.collate, | |
) | |