def __call__(self, batch_input: torch.Tensor, batch_score: torch.Tensor):
        """Randomly apply batch augmentations to the batch inputs and batch
        data samples."""
        aug_index = np.random.choice(len(self.augments), p=self.probs)
        aug = self.augments[aug_index]

        if aug is not None:
            return aug(batch_input, batch_score)
        else:
            return batch_input, batch_score.float()
Randomly apply batch augmentations to the batch inputs and batch
        data samples.
mmpretrain/models/utils/batch_augments/wrapper.py