未验证 提交 ab8fd269 编写于 作者: Y Yuan Shuai 提交者: GitHub

add layout (#2590)

上级 b917cdd8
---
layout: post
title: 如何增加Layout
---
Paddle-Lite中Place包含了Target、Layout、Precision信息,用来注册和选择模型中的具体Kernel。下面以增加Place中的layout:`ImageDefault``ImageFolder``ImageNW`为例,讲解如何增加新Layout。
根据在`lite/core/``lite/api`目录下以`NHWC`为关键词检索代码,发现需要分别在以下的文件中加入Layout内容:
1. lite/api/paddle_place.h
2. lite/api/paddle_place.cc
3. lite/api/python/pybind/pybind.cc
4. lite/core/op_registry.h
5. lite/core/op_registry.cc
## 1. lite/api/paddle_place.h
`enum class DataLayoutType`中加入对应的Layout,注意已有的Layout不能改变值,增加新Layout递增即可:
```cpp
enum class DataLayoutType : int {
kUnk = 0,
kNCHW = 1,
kNHWC = 3,
kImageDefault = 4, // for opencl image2d
kImageFolder = 5, // for opencl image2d
kImageNW = 6, // for opencl image2d
kAny = 2, // any data layout
NUM = 7, // number of fields.
};
```
## 2. lite/api/paddle_place.cc
本文件有3处修改,注意在` DataLayoutToStr`函数中加入对应Layout的字符串名,顺序为`lite/api/paddle_place.h`中枚举值的顺序:
```cpp
// 该文件第1处
const std::string& DataLayoutToStr(DataLayoutType layout) {
static const std::string datalayout2string[] = {
"unk", "NCHW", "any", "NHWC", "ImageDefault", "ImageFolder", "ImageNW"};
auto x = static_cast<int>(layout);
CHECK_LT(x, static_cast<int>(DATALAYOUT(NUM)));
return datalayout2string[x];
}
// 该文件第2处
const std::string& DataLayoutRepr(DataLayoutType layout) {
static const std::string datalayout2string[] = {"kUnk",
"kNCHW",
"kAny",
"kNHWC",
"kImageDefault",
"kImageFolder",
"kImageNW"};
auto x = static_cast<int>(layout);
CHECK_LT(x, static_cast<int>(DATALAYOUT(NUM)));
return datalayout2string[x];
}
// 该文件第3处
std::set<DataLayoutType> ExpandValidLayouts(DataLayoutType layout) {
static const std::set<DataLayoutType> valid_set({DATALAYOUT(kNCHW),
DATALAYOUT(kAny),
DATALAYOUT(kNHWC),
DATALAYOUT(kImageDefault),
DATALAYOUT(kImageFolder),
DATALAYOUT(kImageNW)});
if (layout == DATALAYOUT(kAny)) {
return valid_set;
}
return std::set<DataLayoutType>({layout});
}
```
## 3. lite/api/python/pybind/pybind.cc
```cpp
// DataLayoutType
py::enum_<DataLayoutType>(*m, "DataLayoutType")
.value("NCHW", DataLayoutType::kNCHW)
.value("NHWC", DataLayoutType::kNHWC)
.value("ImageDefault", DataLayoutType::kImageDefault)
.value("ImageFolder", DataLayoutType::kImageFolder)
.value("ImageNW", DataLayoutType::kImageNW)
.value("Any", DataLayoutType::kAny);
```
## 4. lite/core/op_registry.h
找到KernelRegister final中的`using any_kernel_registor_t =`,加入下面修改信息:
```cpp
// 找到KernelRegister final中的`using any_kernel_registor_t =`
// 加入如下内容:
KernelRegistryForTarget<TARGET(kOpenCL),
PRECISION(kFP16),
DATALAYOUT(kNCHW)> *, //
KernelRegistryForTarget<TARGET(kOpenCL),
PRECISION(kFP16),
DATALAYOUT(kNHWC)> *, //
KernelRegistryForTarget<TARGET(kOpenCL),
PRECISION(kFP16),
DATALAYOUT(kImageDefault)> *, //
KernelRegistryForTarget<TARGET(kOpenCL),
PRECISION(kFP16),
DATALAYOUT(kImageFolder)> *, //
KernelRegistryForTarget<TARGET(kOpenCL),
PRECISION(kFP16),
DATALAYOUT(kImageNW)> *, //
KernelRegistryForTarget<TARGET(kOpenCL),
PRECISION(kFloat),
DATALAYOUT(kImageDefault)> *, //
KernelRegistryForTarget<TARGET(kOpenCL),
PRECISION(kFloat),
DATALAYOUT(kImageFolder)> *, //
KernelRegistryForTarget<TARGET(kOpenCL),
PRECISION(kFloat),
DATALAYOUT(kImageNW)> *, //
KernelRegistryForTarget<TARGET(kOpenCL),
PRECISION(kAny),
DATALAYOUT(kImageDefault)> *, //
KernelRegistryForTarget<TARGET(kOpenCL),
PRECISION(kAny),
DATALAYOUT(kImageFolder)> *, //
KernelRegistryForTarget<TARGET(kOpenCL),
PRECISION(kAny),
DATALAYOUT(kImageNW)> *, //
```
## 5. lite/core/op_registry.cc
该文件有2处修改:
```cpp
// 该文件第1处
#define CREATE_KERNEL1(target__, precision__) \
switch (layout) { \
case DATALAYOUT(kNCHW): \
return Create<TARGET(target__), \
PRECISION(precision__), \
DATALAYOUT(kNCHW)>(op_type); \
case DATALAYOUT(kAny): \
return Create<TARGET(target__), \
PRECISION(precision__), \
DATALAYOUT(kAny)>(op_type); \
case DATALAYOUT(kNHWC): \
return Create<TARGET(target__), \
PRECISION(precision__), \
DATALAYOUT(kNHWC)>(op_type); \
case DATALAYOUT(kImageDefault): \
return Create<TARGET(target__), \
PRECISION(precision__), \
DATALAYOUT(kImageDefault)>(op_type); \
case DATALAYOUT(kImageFolder): \
return Create<TARGET(target__), \
PRECISION(precision__), \
DATALAYOUT(kImageFolder)>(op_type); \
case DATALAYOUT(kImageNW): \
return Create<TARGET(target__), \
PRECISION(precision__), \
DATALAYOUT(kImageNW)>(op_type); \
default: \
LOG(FATAL) << "unsupported kernel layout " << DataLayoutToStr(layout); \
}
// 该文件第2处
// 找到文件中的下面的函数
KernelRegistry::KernelRegistry()
: registries_(static_cast<int>(TARGET(NUM)) *
static_cast<int>(PRECISION(NUM)) *
static_cast<int>(DATALAYOUT(NUM)))
// 在该函数中加入新增Layout的下面内容
INIT_FOR(kOpenCL, kFP16, kNCHW);
INIT_FOR(kOpenCL, kFP16, kNHWC);
INIT_FOR(kOpenCL, kFP16, kImageDefault);
INIT_FOR(kOpenCL, kFP16, kImageFolder);
INIT_FOR(kOpenCL, kFP16, kImageNW);
INIT_FOR(kOpenCL, kFloat, kImageDefault);
INIT_FOR(kOpenCL, kFloat, kImageFolder);
INIT_FOR(kOpenCL, kFloat, kImageNW);
INIT_FOR(kOpenCL, kAny, kImageDefault);
INIT_FOR(kOpenCL, kAny, kImageFolder);
INIT_FOR(kOpenCL, kAny, kImageNW);
```
......@@ -40,6 +40,7 @@ Paddle-Lite 框架是 PaddleMobile 新一代架构,重点支持移动端推理
- [支持Op列表]({{site.baseurl}}/develop/support_operation_list)
- [新增Op方法]({{site.baseurl}}/develop/add_new_operation)
- [新增Pass方法]({{site.baseurl}}/develop/add_new_pass)
- [新增Layout方法]({{site.baseurl}}/develop/add_new_layout)
- [测试工具]({{site.baseurl}}/develop/test_tools)
- [调试方法]({{site.baseurl}}/develop/debug_tools)
- [使用华为NPU]({{site.baseurl}}/develop/npu)
......
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