def get_weight_args_quant_dequant_info(
    seen_q_op_info: SeenQOpInfo,
    weight_tensor_id_to_scale_zp: Dict[str, Tuple[torch.Tensor, torch.Tensor]],
) -> Tuple[List[Optional[Tuple[float, int, torch.dtype]]], List[bool], bool]:
    """
    Returns a list of information about the tensor inputs to the current op.
    """
    quant_infos: List[Optional[Tuple[float, int, torch.dtype]]] = []
    any_arg_quant_or_dequant_needed = []
    for _, input_arg in enumerate(seen_q_op_info.weight_tensor_infos):
        if input_arg is not None:
            tensor_id = str(seen_q_op_info.idx) + "_" + str(input_arg.id)
            if tensor_id in weight_tensor_id_to_scale_zp:
                scale, zp = weight_tensor_id_to_scale_zp[tensor_id]
                output_dtype = input_arg.inf_dtype
                quant_infos.append((scale, zp, output_dtype))  # type: ignore[arg-type]
                if input_arg.orig_dtype == torch.float32 and input_arg.inf_dtype in [
                    torch.quint8,
                    torch.qint8,
                ]:
                    any_arg_quant_or_dequant_needed.append(True)
                else:
                    any_arg_quant_or_dequant_needed.append(False)
            else:
                quant_infos.append(None)
                any_arg_quant_or_dequant_needed.append(False)
        else:
            quant_infos.append(None)
            any_arg_quant_or_dequant_needed.append(None)
    return quant_infos, any_arg_quant_or_dequant_needed

    Returns a list of information about the tensor inputs to the current op.
    
intel_extension_for_pytorch/quantization/_quantization_state_utils.py