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

        Returns:
            str: Formatted string.
        """
        head = 'Dataset ' + self.__class__.__name__
        body = []
        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)}')

        body.extend(self.extra_repr())

        if len(self.pipeline.transforms) > 0:
            body.append('With transforms:')
            for t in self.pipeline.transforms:
                body.append(f'    {t}')

        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/base_dataset.py