def __repr__(self):
        """Print the basic information of the dataset.

        Returns:
            str: Formatted string.
        """
        head = 'Dataset ' + self.__class__.__name__
        body = []
        type_ = 'test' if self.test_mode else 'training'
        body.append(f'Type: \t{type_}')
        body.append(f'Seed: \t{self.seed}')

        def ordinal(n):
            # Copy from https://codegolf.stackexchange.com/a/74047
            suffix = 'tsnrhtdd'[(n // 10 % 10 != 1) * (n % 10 < 4) * n % 10::4]
            return f'{n}{suffix}'

        body.append(
            f'Fold: \t{ordinal(self.fold+1)} of {self.num_splits}-fold')
        if self._fully_initialized:
            body.append(f'Number of samples: \t{self.__len__()}')
        else:
            body.append("Haven't been initialized")

        if self.CLASSES is not None:
            body.append(f'Number of categories: \t{len(self.CLASSES)}')
        else:
            body.append('The `CLASSES` meta info is not set.')

        body.append(
            f'Original dataset type:\t{self.dataset.__class__.__name__}')

        lines = [head] + [' ' * 4 + line for line in body]
        return '\n'.join(lines)
Print the basic information of the dataset.

        Returns:
            str: Formatted string.
        
mmpretrain/datasets/dataset_wrappers.py