Compilation and Running Sample

Prerequisites

To compile and execute operator APIs, ensure that the basic environment has been set up, including the driver, firmware, CANN software package, and ops package.
For details about the operator API call process and compilation and running operations, see "Single-Operator Calling > Single-Operator API Execution > Sample Code for Calling aclnn APIs" in Application Development Guide (C&C++).

Preparations

Assume that the development environment and operating environment are deployed on the same server (equipped with the AI processor). In this scenario, code development and code running are performed on the same machine. The following uses the GridSample operator as an example. The calling logic, process, and compilation script of other operators are similar to those of the GridSample operator. You should modify the API calling script (*.cpp) and compilation script (CMakeLists) as required.

Sample code

The GridSample operator is used to provide an input tensor and a grid, and fill the pixel value of a location in the input to the location specified by the grid based on the coordinates of the location provided in the grid to obtain the final output. You can obtain the sample code from "Example" in aclnnGridSampler2D and name the code file test_grid_sampler2_d.cpp.

CMakeLists file

The following is an example of the CMake file, which should be modified as required.

# Copyright (c) Huawei Technologies Co., Ltd. 2019. All rights reserved.

# CMake lowest version requirement
cmake_minimum_required(VERSION 3.14)

# Set the project name.
project(ACLNN_EXAMPLE)

# Compile options
add_compile_options(-std=c++11)

# Set compilation options.
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY  "./bin")    
set(CMAKE_CXX_FLAGS_DEBUG "-fPIC -O0 -g -Wall")
set(CMAKE_CXX_FLAGS_RELEASE "-fPIC -O2 -Wall")

# Set the executable file name (for example, opapi_test) and specify the directory where the operator file (*.cpp) is stored.
add_executable(opapi_test
               test_grid_sampler2_d.cpp)

# Set ASCEND_PATH (CANN package path, which should be replaced with the actual path) and INCLUDE_BASE_DIR (header file directory).
if(NOT "$ENV{ASCEND_CUSTOM_PATH}" STREQUAL "")      
    set(ASCEND_PATH $ENV{ASCEND_CUSTOM_PATH})
else()
    set(ASCEND_PATH "/usr/local/Ascend/cann")
endif()
set(INCLUDE_BASE_DIR "${ASCEND_PATH}/include")
include_directories(
    ${INCLUDE_BASE_DIR}
    ${INCLUDE_BASE_DIR}/aclnn
)

# Set the link library file paths.
target_link_libraries(opapi_test PRIVATE
                      ${ASCEND_PATH}/lib64/libacl_rt.so
                      ${ASCEND_PATH}/lib64/libnnopbase.so
                      ${ASCEND_PATH}/lib64/libopapi_math.so
                      ${ASCEND_PATH}/lib64/libopapi_cv.so)

# The executable file is in the bin folder of the directory where the CMakeLists file is located.
install(TARGETS opapi_test DESTINATION ${CMAKE_RUNTIME_OUTPUT_DIRECTORY})

Operators with integrated and parallel collective communication and MatMul computation are collectively referred to as merged compute and communication operators (abbreviated as MC2 operators), including AllGatherMatmul, AlltoAllAllGatherBatchMatMul, BatchMatMulReduceScatterAlltoAll, MatmulAllReduce, MatmulAllReduceAddRmsNorm, and MatmulReduceScatter. When these operator APIs are called, multi-threading and Huawei Collective Communication Library (HCCL) are generally involved. Therefore, the following content needs to be imported to the CMake file to ensure successful compilation:

# Set the link library file paths.
find_package(Threads REQUIRED)
target_link_libraries(opapi_test PRIVATE
                      ${ASCEND_PATH}/lib64/libacl_rt.so
                      ${ASCEND_PATH}/lib64/libnnopbase.so
                      ${ASCEND_PATH}/lib64/libopapi_math.so
                      ${ASCEND_PATH}/lib64/libopapi_cv.so
                      ${ASCEND_PATH}/lib64/libhccl.so      # Collective communication library file
                      ${CMAKE_THREAD_LIBS_INIT})           # Library file on which multi-threading depends

You can use the find_package(Threads REQUIRED) of CMake to search for the thread library. The command can automatically link the header files on which the thread library depends or the library files on which the thread library indirectly depends.

Compilation and Running

Prepare the calling code (*.cpp) and compilation script (CMakeLists.txt) of the operator.
Set environment variables.

After installing the CANN software, log in to the environment as the CANN running user and run the following command to make the environment variables take effect:
```
source ${INSTALL_DIR}/set_env.sh
```
${INSTALL_DIR} indicates the CANN component directory, which should be replaced with the actual directory.
Compile and run the script.
- Go to the directory where CMakeLists.txt is stored and run the following command to create the build folder to store the generated compilation file.
```
mkdir -p build 
```
- Go to the build directory, run the cmake command to compile the code, and then run the make command to generate an executable file.
```
cd build
cmake ../ -DCMAKE_CXX_COMPILER=g++ -DCMAKE_SKIP_RPATH=TRUE
make
```
  After the compilation is successful, the opapi_test executable file is generated in the bin folder in the build directory.
- Go to the bin folder and run the executable file opapi_test.
```
cd bin
./opapi_test
```
  The following uses the running result of the GridSample operator as an example:
```
resultData[0] is: 0.250000
resultData[1] is: 2.250000
resultData[2] is: 2.000000
resultData[3] is: 8.500000
resultData[4] is: 20.500000
resultData[5] is: 12.000000
resultData[6] is: 8.250000
resultData[7] is: 18.250000
resultData[8] is: 10.000000
```