def extract_feats(self, multi_inputs: Sequence[torch.Tensor],
                      **kwargs) -> list:
        """Extract features from a sequence of input tensor.

        Args:
            multi_inputs (Sequence[torch.Tensor]): A sequence of input
                tensor. It can be used in augmented inference.
            **kwargs: Other keyword arguments accepted by :meth:`extract_feat`.

        Returns:
            list: Features of every input tensor.
        """
        assert isinstance(multi_inputs, Sequence), \
            '`extract_feats` is used for a sequence of inputs tensor. If you '\
            'want to extract on single inputs tensor, use `extract_feat`.'
        return [self.extract_feat(inputs, **kwargs) for inputs in multi_inputs]
Extract features from a sequence of input tensor.

        Args:
            multi_inputs (Sequence[torch.Tensor]): A sequence of input
                tensor. It can be used in augmented inference.
            **kwargs: Other keyword arguments accepted by :meth:`extract_feat`.

        Returns:
            list: Features of every input tensor.
        
mmpretrain/models/classifiers/base.py