Building MindSpore Lite

Windows macOS Linux iOS Android Environment Preparation Intermediate Expert

This chapter introduces how to quickly compile MindSpore Lite, which includes the following modules:

Modules in MindSpore Lite:

Module	Support Platform	Description
converter	Linux, Windows	Model Conversion Tool
runtime(cpp, java)	Linux, Windows, Android, iOS	Model Inference Framework(Windows platform does not support java version runtime)
benchmark	Linux, Windows, Android	Benchmarking Tool
benchmark_train	Linux, Android	Performance and Accuracy Validation
cropper	Linux	Static library crop tool for libmindspore-lite.a
minddata	Linux, Android	Image Processing Library
codegen	Linux	Model inference code generation tool
obfuscator	Linux	Model Obfuscation Tool

Linux Environment Compilation

Environment Requirements

The compilation environment supports Linux x86_64 only. Ubuntu 18.04.02 LTS is recommended.
Compilation dependencies of cpp:
- GCC >= 7.3.0
- CMake >= 3.18.3
- Git >= 2.28.0
- Android_NDK >= r20
  - Configure environment variables: export ANDROID_NDK=NDK path.
Additional compilation dependencies of Java:
- Gradle >= 6.6.1
  - Configure environment variables: export GRADLE_HOME=GRADLE path.
  - Add the bin directory to the PATH: export PATH=${GRADLE_HOME}/bin:$PATH.
- OpenJDK >= 1.8
  - Configure environment variables: export JAVA_HOME=JDK path.
  - Add the bin directory to the PATH: export PATH=${JAVA_HOME}/bin:$PATH.
- Android SDK
  - Create a new directory, configure environment variablesexport ANDROID_SDK_ROOT=new directory.
  - Download SDK Tools, create SDK through sdkmanager: ./sdkmanager --sdk_root=${ANDROID_SDK_ROOT} "cmdline-tools;latest".
  - Accept the license through sdkmanager under the ${ANDROID_SDK_ROOT} directory: yes | ./sdkmanager --licenses.

You can also directly use the Docker compilation image that has been configured with the above dependencies.

Download the docker image: docker pull swr.cn-south-1.myhuaweicloud.com/mindspore-build/mindspore-lite:ubuntu18.04.2-20210530

Create a container: docker run -tid --net=host --name=docker01 swr.cn-south-1.myhuaweicloud.com/mindspore-build/mindspore-lite:ubuntu18.04.2-20210530

Enter the container: docker exec -ti -u 0 docker01 bash

Compilation Options

The script build.sh in the root directory of MindSpore can be used to compile MindSpore Lite.

The compilation parameter of `build.sh`

Parameter	Parameter Description	Value Range	Defaults
-I	Selects an applicable architecture.	arm64, arm32, or x86_64	None
-A	Compile AAR package (including arm32 and arm64).	on, off	off
-d	If this parameter is set, the debug version is compiled. Otherwise, the release version is compiled.	None	None
-i	If this parameter is set, incremental compilation is performed. Otherwise, full compilation is performed.	None	None
-j[n]	Sets the number of threads used during compilation. Otherwise, the number of threads is set to 8 by default.	Integer	8
-a	Whether to enable AddressSanitizer	on, off	off

When compiling the x86_64 version, if the JAVA_HOME environment variable is configured and Gradle is installed, the JAR package will be compiled at the same time.

When the -I parameter changes, such as -I x86_64 is converted to -I arm64, adding -i for parameter compilation does not take effect.

When compiling the AAR package, the -A on parameter must be added, and there is no need to add the -I parameter.

The options of `mindspore/lite/CMakeLists.txt`

Option	Parameter Description	Value Range	Defaults
MSLITE_GPU_BACKEND	Set the GPU backend, only opencl is valid when `-I arm64`, and only tensorrt is valid when `-I x86_64`	opencl, tensorrt, off	opencl when `-I arm64`, off when `-I x86_64`
MSLITE_ENABLE_NPU	Whether to compile NPU operator, only valid when `-I arm64` or `-I arm32`	on, off	off
MSLITE_ENABLE_TRAIN	Whether to compile the training version	on, off	on
MSLITE_ENABLE_SSE	Whether to enable SSE instruction set, only valid when `-I x86_64`	on, off	off
MSLITE_ENABLE_AVX	Whether to enable AVX instruction set, only valid when `-I x86_64`	on, off	off
MSLITE_ENABLE_CONVERTER	Whether to compile the model conversion tool, only valid when `-I x86_64`	on, off	on
MSLITE_ENABLE_TOOLS	Whether to compile supporting tools	on, off	on
MSLITE_ENABLE_TESTCASES	Whether to compile test cases	on, off	off

The above options can be modified by setting the environment variable with the same name or the file mindspore/lite/CMakeLists.txt.

After modifying the Option, adding the -i parameter for incremental compilation will not take effect.

Compilation Example

First, download source code from the MindSpore code repository.

git clone https://gitee.com/mindspore/mindspore.git -b r1.3

Then, run the following commands in the root directory of the source code to compile MindSpore Lite of different versions:

Compile the x86_64 architecture version and set the number of threads at the same time.
```
bash build.sh -I x86_64 -j32
```
Compile the ARM64 architecture version without compiling training-related code.
```
export MSLITE_ENABLE_TRAIN=off
bash build.sh -I arm64 -j32
```
Or modify mindspore/lite/CMakeLists.txt to set MSLITE_ENABLE_TRAIN to off and execute the command:
```
bash build.sh -I arm64 -j32
```
Compile the AAR package containing aarch64 and aarch32.
```
bash build.sh -A on -j32
```

Finally, the following files will be generated in the output/ directory:

mindspore-lite-{version}-{os}-{arch}.tar.gz: Contains runtime, and related tools.
mindspore-lite-maven-{version}.zip: The AAR package which contains runtime (java).

version: Version of the output, consistent with that of the MindSpore.

os: Operating system on which the output will be deployed.

arch: System architecture on which the output will be deployed.

Directory Structure

When the compilation option is -I x86_64:

mindspore-lite-{version}-linux-x64
├── runtime
│   ├── include
│   ├── lib
│   │   ├── libminddata-lite.a         # Static library of image processing
│   │   ├── libminddata-lite.so        # Dynamic library of image processing
│   │   ├── libmindspore-lite.a        # Static library of inference framework in MindSpore Lite
│   │   ├── libmindspore-lite-jni.so   # Dynamic library of inference framework jni in MindSpore Lite
│   │   ├── libmindspore-lite.so       # Dynamic library of inference framework in MindSpore Lite
│   │   ├── libmindspore-lite-train.a  # Static library of training framework in MindSpore Lite
│   │   ├── libmindspore-lite-train.so # Dynamic library of training framework in MindSpore Lite
│   │   ├── libmsdeobfuscator-lite.so  # The files of obfuscated model loading dynamic library, need to open the `ENABLE_MODEL_OBF` option.
│   │   └── mindspore-lite-java.jar    # Jar of inference framework in MindSpore Lite
│   └── third_party
│       └── libjpeg-turbo
└── tools
    ├── benchmark       # Benchmarking tool
    ├── benchmark_train # Training model benchmark tool
    ├── codegen         # Code generation tool
    ├── converter       # Model conversion tool
    ├── obfuscator      # Model obfuscation tool
    └── cropper         # Static library crop tool

When the compilation option is -I arm64 or -I arm32:

mindspore-lite-{version}-android-{arch}
├── runtime
│   ├── include
│   ├── lib
│   │   ├── libminddata-lite.a         # Static library of image processing
│   │   ├── libminddata-lite.so        # Dynamic library of image processing
│   │   ├── libmindspore-lite.a        # Static library of inference framework in MindSpore Lite
│   │   ├── libmindspore-lite.so       # Dynamic library of inference framework in MindSpore Lite
│   │   ├── libmindspore-lite-train.a  # Static library of training framework in MindSpore Lite
│   │   └── libmindspore-lite-train.so # Dynamic library of training framework in MindSpore Lite
│   │   └── libmsdeobfuscator-lite.so  # The files of obfuscated model loading dynamic library, need to open the `ENABLE_MODEL_OBF` option.
│   └── third_party
│       ├── hiai_ddk
│       └── libjpeg-turbo
└── tools
    ├── benchmark       # Benchmarking tool
    ├── benchmark_train # Training model benchmark tool
    └── codegen         # Code generation tool

When the compilation option is -A on:

mindspore-lite-maven-{version}
└── mindspore
    └── mindspore-lite
        └── {version}
            └── mindspore-lite-{version}.aar # MindSpore Lite runtime aar

Windows Environment Compilation

Environment Requirements

System environment: Windows 7, Windows 10; 64-bit.
Compilation dependencies are:
- CMake >= 3.18.3
- MinGW GCC = 7.3.0

The compilation script will execute git clone to obtain the code of the third-party dependent libraries.

If you want to compile 32-bit Mindspore Lite, please use 32-bit MinGW to compile.

Compilation Options

The script build.bat in the root directory of MindSpore can be used to compile MindSpore Lite.

The compilation parameter of `build.bat`

Parameter	Parameter Description	Mandatory or Not
lite	Set this parameter to compile the MindSpore Lite project.	Yes
[n]	Set the number of threads used during compilation, otherwise the default is set to 6 threads.	No

The options of `mindspore/lite/CMakeLists.txt`

Option	Parameter Description	Value Range	Defaults
MSLITE_ENABLE_SSE	Whether to enable SSE instruction set	on, off	off
MSLITE_ENABLE_AVX	Whether to enable AVX instruction set	on, off	off
MSLITE_ENABLE_CONVERTER	Whether to compile the model conversion tool	on, off	on
MSLITE_ENABLE_TOOLS	Whether to compile supporting tools	on, off	on
MSLITE_ENABLE_TESTCASES	Whether to compile test cases	on, off	off

The above options can be modified by setting the environment variable with the same name or the file mindspore/lite/CMakeLists.txt.

Compilation Example

First, use the git tool to download the source code from the MindSpore code repository.

git clone https://gitee.com/mindspore/mindspore.git -b r1.3

Then, use the cmd tool to compile MindSpore Lite in the root directory of the source code and execute the following commands.

Compile the Windows version with the default number of threads (6 threads).

call build.bat lite

Compile the Windows version with the specified number of 8 threads.

call build.bat lite 8

Finally, the following files will be generated in the output/ directory:

mindspore-lite-{version}-win-x64.zip: Contains model inference framework and related tool.

version: Version of the output, consistent with that of the MindSpore.

Directory Structure

mindspore-lite-{version}-win-x64
├── runtime
│   ├── include
│   └── lib
│       ├── libgcc_s_seh-1.dll      # Dynamic library of MinGW
│       ├── libmindspore-lite.a     # Static library of inference framework in MindSpore Lite
│       ├── libmindspore-lite.dll   # Dynamic library of inference framework in MindSpore Lite
│       ├── libmindspore-lite.dll.a # Link file of dynamic library of inference framework in MindSpore Lite
│       ├── libssp-0.dll            # Dynamic library of MinGW
│       ├── libstdc++-6.dll         # Dynamic library of MinGW
│       └── libwinpthread-1.dll     # Dynamic library of MinGW
└── tools
    ├── benchmark # Benchmarking tool
    └── converter # Model conversion tool

Currently, MindSpore Lite is not supported on Windows.

macOS Environment Compilation

Environment Requirements

System environment: macOS 10.15.4 and above ; 64-bit.
Compilation dependencies are:
- CMake >= 3.18.3
- Xcode == 11.4.1
- Git >= 2.28.0

The compilation script will execute git clone to obtain the code of the third-party dependent libraries.

Compilation Options

The script build.sh in the root directory of MindSpore can be used to compile MindSpore Lite.

The compilation parameter of `build.sh`

Parameter	Parameter Description	Value Range	Defaults
-I	Selects an applicable architecture.	arm64, arm32	None
-j[n]	Sets the number of threads used during compilation. Otherwise, the number of threads is set to 8 by default.	Integer	8

Compilation Example

First, use the git tool to download the source code from the MindSpore code repository.

git clone https://gitee.com/mindspore/mindspore.git -b r1.3

Then, use the cmd tool to compile MindSpore Lite in the root directory of the source code and execute the following commands.

Compile the ARM64 architecture version
```
bash build.sh -I arm64 -j8
```
Compile the ARM32 architecture version
```
bash build.sh -I arm32 -j8
```

Finally, the following files will be generated in the output/ directory:

mindspore-lite-{version}-{os}-{arch}.tar.gz: Contains model inference framework.

version: Version of the output, consistent with that of the MindSpore.

os: Operating system on which the output will be deployed.

arch: System architecture on which the output will be deployed.

Directory Structure

mindspore-lite.framework
└── runtime
    ├── Headers        # 推理框架头文件
    ├── Info.plist     # 配置文件
    └── mindspore-lite # 静态库

Currently, MindSpore Lite Train and converter are not supported on macOS.

Building MindSpore Lite

Linux Environment Compilation

Environment Requirements

Compilation Options

The compilation parameter of build.sh

The options of mindspore/lite/CMakeLists.txt

Compilation Example

Directory Structure

Windows Environment Compilation

Environment Requirements

Compilation Options

The compilation parameter of build.bat

The options of mindspore/lite/CMakeLists.txt

Compilation Example

Directory Structure

macOS Environment Compilation

Environment Requirements

Compilation Options

The compilation parameter of build.sh

Compilation Example

Directory Structure

The compilation parameter of `build.sh`

The options of `mindspore/lite/CMakeLists.txt`

The compilation parameter of `build.bat`

The options of `mindspore/lite/CMakeLists.txt`

The compilation parameter of `build.sh`