Horizontal Federated Device-side Deployment
This document describes how to compile and deploy Federated-Client.
Linux Compilation Guidance
System Environment and Third-party Dependencies
This section describes how to complete the device-side compilation of MindSpore federated learning. Currently, the federated learning device-side only provides compilation guidance on Linux, and other systems are not supported. The following table lists the system environment and third-party dependencies required for compilation.
Software Name |
Version |
Functions |
---|---|---|
Ubuntu |
18.04.02LTS |
Compiling and running MindSpore operating system |
Between 7.3.0 to 9.4.0 |
C++ compiler for compiling MindSpore |
|
- |
Source code management tools used by MindSpore |
|
3.18.3 and above |
Compiling and building MindSpore tools |
|
6.6.1 |
JVM-based building tools |
|
3.3.1 and above |
Tools for managing and building Java projects |
|
Between 1.8 to 1.15 |
Tools for managing and building Java projects |
Installing GCC
Install GCC with the following command.
sudo apt-get install gcc-7 git -y
To install a higher version of GCC, use the following command to install GCC 8.
sudo apt-get install gcc-8 -y
Or install GCC 9.
sudo apt-get install software-properties-common -y
sudo add-apt-repository ppa:ubuntu-toolchain-r/test
sudo apt-get update
sudo apt-get install gcc-9 -y
Installing git
Install git with the following command.
sudo apt-get install git -y
Installing Cmake
Install CMake with the following command.
wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc 2>/dev/null | sudo apt-key add -
sudo apt-add-repository "deb https://apt.kitware.com/ubuntu/ $(lsb_release -cs) main"
sudo apt-get install cmake -y
Installing Gradle
Install Gradle with the following command.
# Download the corresponding zip package and unzip it.
# Configure environment variables:
export GRADLE_HOME=GRADLE path
export GRADLE_USER_HOME=GRADLE path
# Add the bin directory to the PATH:
export PATH=${GRADLE_HOME}/bin:$PATH
Installing Maven
Install Maven with the following command.
# Download the corresponding zip package and unzip it.
# Configure environment variables:
export MAVEN_HOME=MAVEN path
# Add the bin directory to the PATH:
export PATH=${MAVEN_HOME}/bin:$PATH
Installing OpenJDK
Install OpenJDK with the following command.
# Download the corresponding zip package and unzip it.
# Configure environment variables:
export JAVA_HOME=JDK path
# Add the bin directory to the PATH:
export PATH=${JAVA_HOME}/bin:$PATH
Verifying Installation
Verify that the installation in System environment and third-party dependencies is successful.
Open a command window and enter: gcc --version
The following output identifies a successful installation:
gcc version version number
Open a command window and enter:git --version
The following output identifies a successful installation:
git version version number
Open a command window and enter:cmake --version
The following output identifies a successful installation:
cmake version version number
Open a command window and enter:gradle --version
The following output identifies a successful installation:
Gradle version number
Open a command window and enter:mvn --version
The following output identifies a successful installation:
Apache Maven version number
Open a command window and enter:java --version
The following output identifies a successful installation:
openjdk version version number
Compilation Options
The cli_build.sh
script in the federated learning device_client directory is used for compilation on the federated learning device-side.
Instructions for Using cli_build.sh Parameters
Parameters |
Parameter Description |
Value Range |
Default Values |
---|---|---|---|
-p |
the download path of dependency external packages |
string |
third |
-c |
whether to reuse dependency packages previously downloaded |
on and off |
on |
Compilation Examples
First, you need to download the source code from the gitee code repository before you can compile it.
git clone https://gitee.com/mindspore/federated.git -b r0.1 ./
Go to the mindspore_federated/device_client directory and execute the following command:
bash cli_build.sh
Since the end-side framework and the model are decoupled, the x86 architecture package we provide, mindspore-lite-{version}-linux-x64.tar.gz, does not contain model-related scripts, so the user needs to generate the jar package corresponding to the model scripts. The jar package corresponding to the model scripts we provide can be obtained in the following way:
cd federated/example/quick_start_flclient bash build.sh -r mindspore-lite-java-flclient.jar # After -r, you need to give the absolute path to the latest x86 architecture package (generated in Step 2, federated/mindspore_federated/device_client/build/libs/jarX86/mindspore-lite-java-flclient.jar)
After running the above command, the path of generated jar package is federated/example/quick_start_flclient/target/quick_start_flclient.jar.
Building Dependency Environment
After extracting the file
federated/mindspore_federated/device_client/third/mindspore-lite-{version}-linux-x64.tar.gz
, the obtained directory structure is as follows(files that are not used in federated learning are not displayed here):mindspore-lite-{version}-linux-x64 ├── tools └── runtime ├── include # Header files of training framework ├── lib # Training framework library │ ├── libminddata-lite.a # Static library files for image processing │ ├── libminddata-lite.so # Dynamic library files for image processing │ ├── libmindspore-lite-jni.so # jni dynamic library relied by MindSpore Lite inference framework │ ├── libmindspore-lite-train.a # Static library relied by MindSpore Lite training framework │ ├── libmindspore-lite-train.so # Dynamic library relied by MindSpore Lite training framework │ ├── libmindspore-lite-train-jni.so # jni dynamic library relied by MindSpore Lite training framework │ ├── libmindspore-lite.a # Static library relied by MindSpore Lite inference framework │ ├── libmindspore-lite.so # Dynamic library relied by MindSpore Lite inference framework │ ├── mindspore-lite-java.jar # MindSpore Lite training framework jar package └── third_party ├── glog │└── libmindspore_glog.so.0 # Dynamic library files of glog └── libjpeg-turbo └── lib ├── libjpeg.so.62 # Dynamic library files for image processing └── libturbojpeg.so.0 # Dynamic library files for image processing
Put the so files relied by federated learning in paths
mindspore-lite-{version}-linux-x64/runtime/lib/
,mindspore-lite-{version}-linux-x64/runtime/third_party/glog/
andmindspore-lite-{version}-linux-x64/runtime/third_party/libjpeg-turbo/lib/
in a folder, e.g./resource/x86libs/
. Then set the environment variables in x86 (absolute paths need to be provided below):export LD_LIBRARY_PATH=/resource/x86libs/:$LD_LIBRARY_PATH
After setting up the dependency environment, you can simulate starting multiple clients in the x86 environment for federated learning by referring to the application practice tutorial Implementing an end-cloud federation for image classification application (x86).