def floating_point_ops(self, inputs: Dict[str, Union[torch.Tensor, Any]]):
        """
        For models that inherit from [`PreTrainedModel`], uses that method to compute the number of floating point
        operations for every backward + forward pass. If using another model, either implement such a method in the
        model or subclass and override this method.

        Args:
            inputs (`Dict[str, Union[torch.Tensor, Any]]`):
                The inputs and targets of the model.

        Returns:
            `int`: The number of floating-point operations.
        """
        if hasattr(self.model, "floating_point_ops"):
            return self.model.floating_point_ops(inputs)
        else:
            return 0

        For models that inherit from [`PreTrainedModel`], uses that method to compute the number of floating point
        operations for every backward + forward pass. If using another model, either implement such a method in the
        model or subclass and override this method.

        Args:
            inputs (`Dict[str, Union[torch.Tensor, Any]]`):
                The inputs and targets of the model.

        Returns:
            `int`: The number of floating-point operations.
        
dpkd/transformers/src/transformers/trainer.py