Paddle/doc/design/kernel_hint_design.md

## 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 use a CPU kernel, `use_cudnn` to choose a CUDNN kernel, we need to provide a way for a user 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 come from the input tensor of the operator, `GetActualKernelType(inputs)` use inputs to infer the proper kernel key that fit the incoming data, user can not config it.

The design also provides a virtual method `GetExpectedKernelType` that user can overload and 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 right. 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` for CPU kernel, and `use_cudnn`, `force_cudnn`, `cudnn_kernel` for use of 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 predefine some options, such as `force_cpu`, `use_cudnn`, `use_mkldnn` for a user to choose.

```cpp
const std::string kNonHint = "";
const std::string kForceCPU = "force_cpu";
const std::string kUseCUDNN = "use_cudnn";
const std::string kUseMKLDNN = "use_mkldnn";

KernelType GetExpectedKernelTyp() {
    // "kernel_hint" is a user defined attribute name
	if (Attr<std::string>("kernel_hint") == kForceCPU) {
		return KernelType(CPUPlace, ...)
	} else {
		...
	}
}
```

In Python code

```python
def xx_layer(..., kernel_hint=None):
	layer_helper = ...
	layer_helper .append_op(
		type="xx",
		# "kernel_hint" should be the same with the attr name in CPP
		attr={"kernel_hint": kernel_hint or ""})
```