def floating_point_ops(
        self, input_dict: Dict[str, Union[torch.Tensor, Any]], exclude_embeddings: bool = True
    ) -> int:
        """
        Get number of (optionally, non-embeddings) floating-point operations for the forward and backward passes of a
        batch with this transformer model. Default approximation neglects the quadratic dependency on the number of
        tokens (valid if `12 * d_model << sequence_length`) as laid out in [this
        paper](https://arxiv.org/pdf/2001.08361.pdf) section 2.1. Should be overridden for transformers with parameter
        re-use e.g. Albert or Universal Transformers, or if doing long-range modeling with very high sequence lengths.

        Args:
            batch_size (`int`):
                The batch size for the forward pass.

            sequence_length (`int`):
                The number of tokens in each line of the batch.

            exclude_embeddings (`bool`, *optional*, defaults to `True`):
                Whether or not to count embedding and softmax operations.

        Returns:
            `int`: The number of floating-point operations.
        """

        return 6 * self.estimate_tokens(input_dict) * self.num_parameters(exclude_embeddings=exclude_embeddings)

        Get number of (optionally, non-embeddings) floating-point operations for the forward and backward passes of a
        batch with this transformer model. Default approximation neglects the quadratic dependency on the number of
        tokens (valid if `12 * d_model << sequence_length`) as laid out in [this
        paper](https://arxiv.org/pdf/2001.08361.pdf) section 2.1. Should be overridden for transformers with parameter
        re-use e.g. Albert or Universal Transformers, or if doing long-range modeling with very high sequence lengths.

        Args:
            batch_size (`int`):
                The batch size for the forward pass.

            sequence_length (`int`):
                The number of tokens in each line of the batch.

            exclude_embeddings (`bool`, *optional*, defaults to `True`):
                Whether or not to count embedding and softmax operations.

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