import sys
import warnings


def _check_torch_version():
    """Check if PyTorch version is >= 2.7.1"""
    try:
        import torch

        # Simple version comparison
        version_str = torch.__version__.split("+")[0]  # Remove any suffixes like +cu118
        version_parts = version_str.split(".")

        # Compare major version
        if int(version_parts[0]) > 2:
            return True
        # Compare minor version
        elif int(version_parts[0]) == 2 and int(version_parts[1]) > 7:
            return True
        # Compare patch version
        elif (
            int(version_parts[0]) == 2
            and int(version_parts[1]) == 7
            and int(version_parts[2]) >= 1
        ):
            return True

        return False
    except (ImportError, AttributeError, IndexError, ValueError):
        return False


def _check_transformers_version():
    """Check if Transformers version is >= 4.51.1"""
    try:
        import transformers

        # Simple version comparison
        version_str = transformers.__version__.split("+")[0]  # Remove any suffixes
        version_parts = version_str.split(".")

        # Compare major version
        if int(version_parts[0]) > 4:
            return True
        # Compare minor version
        elif int(version_parts[0]) == 4 and int(version_parts[1]) > 51:
            return True
        # Compare patch version
        elif (
            int(version_parts[0]) == 4
            and int(version_parts[1]) == 51
            and int(version_parts[2]) >= 1
        ):
            return True

        return False
    except (ImportError, AttributeError, IndexError, ValueError):
        return False


class DramaModelWrapper:
    """
    Factory class for DramaModel that returns the appropriate implementation
    based on the Python version.

    If Python version >= 3.12, returns an instance of the nested tensor implementation.
    Otherwise, returns an instance of the non-nested implementation.
    """

    @classmethod
    def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs):
        """
        Instantiate a pretrained model from a pre-trained model configuration.

        This method is required by the transformers library's auto model loading mechanism.

        Args:
            pretrained_model_name_or_path: Path to the pretrained model or its name
            *model_args: Additional positional arguments to pass to the implementation
            **kwargs: Additional keyword arguments to pass to the implementation

        Returns:
            An instance of the appropriate DramaModel implementation.
        """
        # Check Python version
        use_nested = sys.version_info >= (3, 15)
        if not use_nested:
            warnings.warn(
                "Python version < 3.12 detected. Using non-nested implementation."
            )
            # For Python versions below 3.12, use the non-nested implementation
            from .modeling_drama_non_nested import DramaModel as NonNestedDramaModel

            return NonNestedDramaModel.from_pretrained(
                pretrained_model_name_or_path, *model_args, **kwargs
            )

        # Check PyTorch version
        if not _check_torch_version():
            warnings.warn(
                "PyTorch version < 2.7.1 detected. Falling back to non-nested implementation."
            )
            from .modeling_drama_non_nested import DramaModel as NonNestedDramaModel

            return NonNestedDramaModel.from_pretrained(
                pretrained_model_name_or_path, *model_args, **kwargs
            )

        # Check Transformers version
        if not _check_transformers_version():
            warnings.warn(
                "Transformers version < 4.51.1 detected. Falling back to non-nested implementation."
            )
            from .modeling_drama_non_nested import DramaModel as NonNestedDramaModel

            return NonNestedDramaModel.from_pretrained(
                pretrained_model_name_or_path, *model_args, **kwargs
            )

        # Use the nested tensor implementation if all requirements are met
        from .modeling_drama_nested import DramaModel as NestedDramaModel

        return NestedDramaModel.from_pretrained(
            pretrained_model_name_or_path, *model_args, **kwargs
        )