def __call__(self, results):
        """Perform the Decord decoding.

        Args:
            results (dict): The resulting dict to be modified and passed
                to the next transform in pipeline.
        """
        container = results['video_reader']

        if results['frame_inds'].ndim != 1:
            results['frame_inds'] = np.squeeze(results['frame_inds'])

        frame_inds = results['frame_inds']
        # Generate frame index mapping in order
        frame_dict = {
            idx: container[idx].asnumpy()
            for idx in np.unique(frame_inds)
        }

        imgs = [frame_dict[idx] for idx in frame_inds]

        results['video_reader'] = None
        del container

        results['imgs'] = imgs
        results['original_shape'] = imgs[0].shape[:2]
        results['img_shape'] = imgs[0].shape[:2]

        return results
Perform the Decord decoding.

        Args:
            results (dict): The resulting dict to be modified and passed
                to the next transform in pipeline.
        
EVA-01/video/datasets/pipeline.py