# Kernel Hint Design ## Problem In PaddlePaddle's [Design](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/switch_kernel.md), one Operator may have multiple kernels. Users may have some personal preference to choose a certain type of kernel for an operator, such as `force_cpu` to choose a CPU kernel, `use_cudnn` to choose a CUDNN kernel, we need to provide a way for users to do this. In the current design, we use KernelType to describe one kernel. ```cpp struct KernelType { Place place_; DataType data_type_; LayoutType layout_; }; ``` `place_` `data_type_` and `layout_` can be got from the input tensors of the operator, `GetActualKernelType(inputs)` use inputs to infer the proper kernel key that fit the incoming data, but users can not directly configure it. The [design](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/switch_kernel.md) also provides a virtual method `GetExpectedKernelType` that user can overload and use to choose the KernelType they want to use. So we should send the information user defined in proto to `GetExpectedKernelType` for choosing a kernel. The problem is, how should we define and send the information for `GetExpectedKernelType` to use? ## Solution ### Potential choice 1. Do nothing, let the user add the information they want to operator‘s attribute and get them inside `GetExpectedKernelType`, this can work properly. But there is a little problem that users may define many kinds of hints for the same purpose, such as `force_cpu`, `use_cpu`, `cpu_kernel` to choose CPU kernel, and `use_cudnn`, `force_cudnn`, `cudnn_kernel` to choose CUDNN kernel. 2. Pre-define all the needed option and use a single attr key such as `kernel_hint` for the user, this is not so flexible if the user wants to define some more kind of hint. ### Final choice To provide enough flexibility while avoiding confusion definition, we can define some global constants for these attribute names, such as `force_cpu`, `use_cudnn`, `use_mkldnn` for a user to choose. In C++ ```cpp const std::string kForceCPU = "force_cpu"; const std::string kUseCUDNN = "use_cudnn"; const std::string kUseMKLDNN = "use_mkldnn"; KernelType GetExpectedKernelType() { if (Attr(kForceCPU)) { return KernelType(CPUPlace, ...) } else { ... } } ``` In Python code ```python FORCE_CPU = core.kForceCPU() def xx_layer(..., force_cpu=false): layer_helper = LayerHelper(...) layer_helper.append_op( type="xx", attr={FORCE_CPU: force_cpu}) ```