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## Problem
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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.
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In the current design, we use KernelType to describe one kernel.
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```cpp
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struct KernelType {
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Place place_;
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DataType data_type_;
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LayoutType layout_;
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};
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```
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`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.
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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.
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So we should send the information user defined in proto to `GetExpectedKernelType` for choosing a kernel.
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The problem is, how should we define and send the information for `GetExpectedKernelType` to use?
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## Solution
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### Potential choice
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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.
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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.
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### Final choice
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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.
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In C++
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```cpp
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const std::string kForceCPU = "force_cpu";
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const std::string kUseCUDNN = "use_cudnn";
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const std::string kUseMKLDNN = "use_mkldnn";
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KernelType GetExpectedKernelType() {
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if (Attr<bool>(kForceCPU)) {
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return KernelType(CPUPlace, ...)
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} else {
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...
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}
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}
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```
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In Python code
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```python
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FORCE_CPU = core.kForceCPU()
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def xx_layer(..., force_cpu=false):
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layer_helper = LayerHelper(...)
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layer_helper.append_op(
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type="xx",
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attr={FORCE_CPU: force_cpu})
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```
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