Method split

lada/models/basicvsrpp/mmagic/data_sample.py:323–365

Split a sequence of data sample in the first dimension. Args: allow_nonseq_value (bool): Whether allow non-sequential data in split operation. If True, non-sequential data will be copied for all split data samples. Otherwise, an error will be

(self,
              allow_nonseq_value: bool = False)

        return stacked_data_sample

    def split(self,
              allow_nonseq_value: bool = False) -> Sequence['DataSample']:
        """Split a sequence of data sample in the first dimension.

        Args:
            allow_nonseq_value (bool): Whether allow non-sequential data in
                split operation. If True, non-sequential data will be copied
                for all split data samples. Otherwise, an error will be
                raised. Defaults to False.

        Returns:
            Sequence[DataSample]: The list of data samples after splitting.
        """
        # 1. split
        data_sample_list = [DataSample() for _ in range(len(self))]
        for k in self.all_keys():
            stacked_value = self.get(k)
            if isinstance(stacked_value, torch.Tensor):
                # split tensor shape like (N, *shape) to N (*shape) tensors
                values = [v for v in stacked_value]
            elif isinstance(stacked_value, LabelData):
                # split tensor shape like (N, *shape) to N (*shape) tensors
                labels = [l_ for l_ in stacked_value.label]
                values = [LabelData(label=l_) for l_ in labels]
            elif isinstance(stacked_value, DataSample):
                values = stacked_value.split()
            else:
                if is_splitable_var(stacked_value):
                    values = stacked_value
                elif allow_nonseq_value:
                    values = [deepcopy(stacked_value)] * len(self)
                else:
                    raise TypeError(
                        f'\'{k}\' is non-sequential data and '
                        '\'allow_nonseq_value\' is False. Please check your '
                        'data sample or set \'allow_nonseq_value\' as True '
                        f'to copy field \'{k}\' for all split data sample.')

            field = 'metainfo' if k in self.metainfo_keys() else 'data'
            for data, v in zip(data_sample_list, values):
                data.set_field(v, k, field_type=field)

        return data_sample_list

    def __len__(self):
        """Get the length of the data sample."""