FATE-Board as a suite of visualization tool for federated learning modeling designed to deep explore models and understand models easily and effectively.
To make it easier to understand, track, debug, and explore federated learning modeling, as well as examine, evaluate, and compare various federation learning models. FATEBoard provides a visual way to probe models, from which you can reshape and improve models efficiently.
The FATE stand-alone version has been integrated with FATE-Board, and users just follow the steps indicated on the home page to launch the relevant components instead of configuring additional information.
In a distributed environment, FATEBoard needs to be deployed through cluster automated deployment script rather than individually, which you need to configure some information about the cluster, such as URL of FATEFlow, directory of log files, SSH information of each machine, etc. All the configuration information could be generated automatically using automated script deployment. If the information is not filled in correctly, it will not work properly.
you can launch a fateboard service by following steps.
Modify FATE/fateboard/src/main/resources/application.properties.
Item | explainsexplains | default |
---|---|---|
server.port | port of fateboard | 8080 |
fateflow.url | the url of fate_flow node | none |
spring.datasource.driver-Class-Name | driver for database | com.mysql.cj.jdbc.Driver |
management.endpoints.web.exposure.include | endpoints for exposure | * |
spring.http.encoding.charset | code set for http | UTF-8 |
spring.http.encoding.enabled | toggle for encoding | true |
server.tomcat.uri-encoding | code set for tomcat | UTF-8 |
spring.datasource.url | url of database | jdbc:mysql://localhost:3306/fate_flow?characterEncoding=utf8&characterSetResults=utf8&autoReconnect=true&failOverReadOnly=false&serverTimezone=GMT%2B8 |
spring.datasource.username | username of database | none |
spring.datasource.password | password of database | none |
server.tomcat.max-threads | max threads of tomcat | 1000 |
server.tomcat.max-connections | max connections of tomcat | 2000 |
example1 (database: mysql)
server.port=8080
fateflow.url=http://localhost:9380
spring.datasource.driver-Class-Name=com.mysql.cj.jdbc.Driver
management.endpoints.web.exposure.include=*
spring.http.encoding.charset=UTF-8
spring.http.encoding.enabled=true
server.tomcat.uri-encoding=UTF-8
spring.datasource.url=jdbc:mysql://localhost:3306/fate_flow?characterEncoding=utf8&characterSetResults=utf8&autoReconnect=true&failOverReadOnly=false&serverTimezone=GMT%2B8
spring.datasource.username=fate_dev
spring.datasource.password=fate_dev
server.tomcat.max-threads=1000
server.tomcat.max-connections=20000
example2(database:sqlite)
server.port=8080
fateflow.url=http://localhost:9380
spring.datasource.driver-class-name=org.sqlite.JDBC
spring.datasource.url=jdbc:sqlite:/fate/fate_flow/fate_flow_sqlite.db
management.endpoints.web.exposure.include=*
spring.http.encoding.charset=UTF-8
spring.http.encoding.enabled=true
server.tomcat.uri-encoding=UTF-8
spring.datasource.username=
spring.datasource.password=
server.tomcat.max-threads=1000
server.tomcat.max-connections=20000
Modify FATE/fateboard/src/main/resources/ssh.properties.
Format : ip=username|password|port
Item | explains |
---|---|
ip | ip of other nodes in FATE |
username | username of operating system |
password | passwordof operating system |
port | port which can access |
example:
192.168.xxx.xxx=app|app|22
Package
cd FATE/fateboard
mvn clean package -DskipTests
Launch the service
command explains:
Item | explains |
---|---|
-Dspring.config.location | path of application.properties of fateboard |
-Dssh_config_file | path of directory which ssh.properties lies in |
-DFATE_DEPLOY_PREFIX | path of logs directory which produced by fate_flow |
command example:
NOTES: Please replace ${version} in command below with the real fateboard version you use.
java -Dspring.config.location=FATE/fateboard/src/main/resources/application.properties -DFATE_DEPLOY_PREFIX=FATE/logs/ -Dssh_config_file=FATE/fateboard/src/main/resources/ -Xmx2048m -Xms2048m -XX:+PrintGCDetails -XX:+PrintGCDateStamps -Xloggc:gc.log -XX:+HeapDumpOnOutOfMemoryError -jar FATE/fateboard/target/fateboard-${version}.jar >/dev/null 2>&1 &
Stop the service
Get the pid of fateboard:
NOTES: Please replace ${version} in command below with the real fateboard version you use.
ps -ef|grep java|grep fateboard-${version}.jar|grep -v grep|awk '{print $2}'
kill the fateboard:
NOTES: Please replace ${pid} in command below with the real pid you get.
kill -9 ${pid}
Database Configuration
The default database for FATEBoard for cluster version is mysql. If you want to use standalone version, you should use sqlite databse. Just update the file : fateboard/src/main/resources/application.properties with right parameters of sqlite. The parameters you should update are below: spring.datasource.driver-Class-Name=org.sqlite.JDBC spring.datasource.url=xxx spring.datasource.username= spring.datasource.password=
Starting FATEBoard
The FATEBoard source code uses the spring-boot framework and the embedded tomcat container. The default web port provided is 8080. Before starting, it is necessary to check whether port 8080 of the machine is already occupied. If the port is occupied, FATEBoard will fail to start.
FATEBoard gets job list through accessing MySQL database or SQLite database. If the database is not installed properly, the job list query will fail. FATEBoard access FATEFlow through HTTP protocol. If FATEFlow is not started properly, FATEBoard will not display charts.
You can access FATEBoard by visiting http://{fateboard-ip}:8080.
Starting a new job
FATEBoard can be used in Google Chrome, IE (10.0 and above) and other mainstream browsers. Some browsers might work, but there may be bugs or performance issues.
Job Dashboard
FATEBoard’s dashboard visualizes basic statistics that vary over time, which include running time of job, real-time Log of job, running status for each component. Once you submit your job, you may have to wait for it to run. You can check the RUNNING page to see the progress of all running jobs and all waiting jobs.
Job Visualization
Job visualization provides overviews of the overall execution of the job, visualizes all the results as much as possible. There are some simple interactions as following:
Visualizing the job workflow
The job workflow of federated learning modeling is easy to understand, which can help you track the running progress intuitively. For each role, you may see your own graph in the federated learning modeling.
Visualizing the model graph
FATEBoard provides different visualizations for federated learning models, including statistical table, histograms, curves, confusion matrices, and so on. You can compare the performance of multiple training models on the same dataset, or inspect a single model’s performance for continued tuning and training, which all probe your models better.
Take evaluation as an example:
For Binary Classification job, FATEBoard shows an evaluation score chart, a ROC curve, a K-S curve, a Lift curve, a Gains curve, a Precision-Recall curve, and an accuracy curve.For Multiclass classification job, FATEBoard shows an evaluation score chart, and a Precision-Recall curve.For Regression job, FATEBoard shows an evaluation score chart. If a validate set was provided for the job, then evaluation curves are presented separately according to train set and validate set. Evaluation curves of different model training are presented together for model performance comparison, as well as model validation.
Visualizing the data
Preview the data of each component and you can view 100 lines of output data, from which you can also see the prediction data, including prediction result, prediction score and prediction detail.
My FATEBoard isn’t showing any data of components!
FATEBoard sends a request to access FATEFlow via HTTP to obtain all the data needed by a model. Log of httpclient is defined separately in the logback.xml in the source code, through which you can check communication between FATEBoard and FATEFlow, and you can easily locate the problem if there is an exception.
My FATEBoard isn’t showing any log!
FATEBoard gets the list of jobs and details by querying MySQL. In a stand-alone environment, Fateboard reads the local log file and returns it to the user through WebSocekt. If the log file cannot be displayed, you can first check whether the local log file has been generated. In a clustered environment, FATEBoard could access log files on different machines with SSH, and push them to the browser through WebSocket. The default log lookup path is /data/projects/fate/python/logs/. If you cannot view the logs, it may be an error in SSH information in the cluster. you can set the correct SSH information by clicking the button in the upper right corner of the page.
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