AR/data/data_module.py

# modified from https://github.com/feng-yufei/shared_debugging_code/blob/main/data_module.py
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']
        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)