def collater(self, samples):
        """Merge a list of samples to form a mini-batch.

        Args:
            samples (List[dict]): samples to collate

        Returns:
            dict: a mini-batch suitable for forwarding with a Model
        """
        if len(samples) == 0:
            return {}
        sample = OrderedDict()
        for k, ds in self.defn.items():
            try:
                sample[k] = ds.collater([s[k] for s in samples])
            except NotImplementedError:
                sample[k] = default_collate([s[k] for s in samples])
        return _unflatten(sample)
Merge a list of samples to form a mini-batch.

        Args:
            samples (List[dict]): samples to collate

        Returns:
            dict: a mini-batch suitable for forwarding with a Model
        
structured_prompting/fairseq-version/fairseq/fairseq/data/nested_dictionary_dataset.py