def process(self, data_batch, data_samples):
        """Process one batch of data samples.

        The processed results should be stored in ``self.results``, which will
        be used to computed the metrics when all batches have been processed.

        Args:
            data_batch: A batch of data from the dataloader.
            data_samples (Sequence[dict]): A batch of outputs from the model.
        """

        for data_sample in data_samples:
            result = dict()

            result['caption'] = data_sample.get('pred_caption')
            result['image_id'] = int(data_sample.get('image_id'))

            # Save the result to `self.results`.
            self.results.append(result)
Process one batch of data samples.

        The processed results should be stored in ``self.results``, which will
        be used to computed the metrics when all batches have been processed.

        Args:
            data_batch: A batch of data from the dataloader.
            data_samples (Sequence[dict]): A batch of outputs from the model.
        
mmpretrain/evaluation/metrics/caption.py