企业官网建设流程全解析

Directory Structure

【免费下载链接】geGE（Graph Engine）是面向昇腾的图编译器和执行器，提供了计算图优化、多流并行、内存复用和模型下沉等技术手段，加速模型执行效率，减少模型内存占用。 GE 提供对 PyTorch、TensorFlow 前端的友好接入能力，并同时支持 onnx、pb 等主流模型格式的解析与编译。项目地址: https://gitcode.com/cann/ge

├── 01_udf_add │ ├── CMakeLists.txt │ └── add_flow_func.cpp Single func interface definition of add function ├── 02_udf_call_add_nn │ ├── CMakeLists.txt │ └── call_nn_flow_func.cpp UDF calls tensorflow model ├── 03_udf_add_multi_func │ ├── CMakeLists.txt │ └── add_flow_func.cpp Multi-Func interface definition of add function ├── 04_control_func │ ├── CMakeLists.txt │ └── control_func.cpp Activates one of the multi funcs defined in 03 according to input └── README.md

Development Guide

01_udf_add and 02_udf_call_add_nn are single func call samples.

1. Include external header file meta_flow_func.h

2. Define processing class, public inheritance from MetaFlowFunc base class, overload Init and Proc functions

   • Init function performs initialization actions, such as variable initialization, attribute acquisition, etc. UDF framework will call this function during initialization phase
   • Proc contains user-defined computation processing logic. UDF framework will call this function after receiving input data

3. UDF registration, implemented through REGISTER_FLOW_FUNC macro to map class declaration to user-defined UDF function name, and register to UDF framework. For example:
   EGISTER_FLOW_FUNC("call_nn", CallNnFlowFunc);

   call_nn: User-defined UDF function name

   CallNnFlowFunc: Actual executing class name, needs to be consistent with class name in cpp file

03_udf_add_multi_func and 04_control_func are multi-func call samples

1. Include external header file meta_multi_func.h

2. Define processing class, public inheritance from MetaMultiFunc base class, overload Init and Proc functions

   • Init function performs initialization actions, such as variable initialization, attribute acquisition, etc. UDF framework will call this function during initialization phase

   • Proc contains user-defined computation processing logic. UDF framework will call this function after receiving input data. Multiple proc functions can be defined

3. UDF registration, implemented through FLOW_FUNC_REGISTRAR macro to map class declaration to user-defined UDF function name, and register to UDF framework. For example:
   FLOW_FUNC_REGISTRAR(AddFlowFunc)
   .RegProcFunc("Proc1", &AddFlowFunc::Proc1)
   .RegProcFunc("Proc2", &AddFlowFunc::Proc2);

Compilation Guide

After UDF function development is completed, you can use the following compilation instructions to check whether CMakeLists file and cpp source code have any issues.

source {HOME}/Ascend/cann/set_env.sh #{HOME} is the CANN software package installation directory, please replace according to the actual installation path # T ake 01_udf_add as an example cd 01_udf_add mkdir build cd build # If host is x86, compile x86 type so cmake -S .. -DTOOLCHAIN=g++ -DRELEASE=../release -DRESOURCE_TYPE=x86 -DUDF_TARGET_LIB=udf # If host is arm, compile arm type so cmake -S .. -DTOOLCHAIN=g++ -DRELEASE=../release -DRESOURCE_TYPE=Aarch -DUDF_TARGET_LIB=udf # If compiling Ascend type so, need to specify g++ in the environment where cann package is installed cmake -S .. -DTOOLCHAIN=$ASCEND_HOME_PATH/toolkit/toolchain/hcc/bin/aarch64-target-linux-gnu-g++ -DRELEASE_DIR=../release -DRESOURCE_TYPE=Ascend -DUDF_TARGET_LIB=udf make -j 64

【免费下载链接】geGE（Graph Engine）是面向昇腾的图编译器和执行器，提供了计算图优化、多流并行、内存复用和模型下沉等技术手段，加速模型执行效率，减少模型内存占用。 GE 提供对 PyTorch、TensorFlow 前端的友好接入能力，并同时支持 onnx、pb 等主流模型格式的解析与编译。项目地址: https://gitcode.com/cann/ge