Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Update nvflare demo for release 2.1.2 (#8038)

Browse Source
This commit is contained in:
Rong Ou 2022-06-29 02:58:06 -07:00 committed by GitHub
parent f470ad3af9
commit 6eb23353d7
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 5 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
demo/nvflare/README.md
View File

@ -8,9 +8,10 @@ This directory contains a demo of Federated Learning using
To run the demo, first build XGBoost with the federated learning plugin enabled (see the To run the demo, first build XGBoost with the federated learning plugin enabled (see the
[README](../../plugin/federated/README.md)). [README](../../plugin/federated/README.md)).
Install NVFlare (note that currently NVFlare only supports Python 3.8): Install NVFlare (note that currently NVFlare only supports Python 3.8; for NVFlare 2.1.2 we also
need to pin the protobuf package to 3.20.x to avoid protoc errors):
```shell ```shell
pip install nvflare pip install nvflare protobuf==3.20.1
``` ```
Prepare the data: Prepare the data:
@ -38,12 +39,9 @@ Then start the admin CLI, using `admin/admin` as username/password:
./poc/admin/startup/fl_admin.sh ./poc/admin/startup/fl_admin.sh
``` ```
In the admin CLI, run the following commands: In the admin CLI, run the following command:
```shell ```shell
upload_app hello-xgboost submit_job hello-xgboost
set_run_number 1
deploy_app hello-xgboost all
start_app all
``` ```
Once the training finishes, the model file should be written into Once the training finishes, the model file should be written into