def validate_explanation(explanation: list[str] | None) -> list[str] | None:
        """Validate the explanations for a batch.

        This method validates batches of explanation strings.

        Args:
            explanation (``list[str]`` | ``None``): Input list of explanations.

        Returns:
            ``list[str]`` | ``None``: Validated list of explanations, or None.

        Raises:
            TypeError: If ``explanation`` is not a list of strings.

        Example:
            Validate explanations::

                >>> from anomalib.data.validators import ImageBatchValidator
                >>> explanations = ["Crack on wall", "Dent on car"]
                >>> validated = ImageBatchValidator.validate_explanation(explanations)
                >>> validated
                ['Crack on wall', 'Dent on car']
        """
        if explanation is None:
            return None
        if not isinstance(explanation, list):
            msg = f"Explanation must be a list of strings, got {type(explanation)}."
            raise TypeError(msg)
        return [str(exp) for exp in explanation]
Validate the explanations for a batch.

        This method validates batches of explanation strings.

        Args:
            explanation (``list[str]`` | ``None``): Input list of explanations.

        Returns:
            ``list[str]`` | ``None``: Validated list of explanations, or None.

        Raises:
            TypeError: If ``explanation`` is not a list of strings.

        Example:
            Validate explanations::

                >>> from anomalib.data.validators import ImageBatchValidator
                >>> explanations = ["Crack on wall", "Dent on car"]
                >>> validated = ImageBatchValidator.validate_explanation(explanations)
                >>> validated
                ['Crack on wall', 'Dent on car']
        
src/anomalib/data/validators/torch/image.py