Update nvflare demo for release 2.1.2 (#8038)

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Rong Ou 2022-06-29 02:58:06 -07:00 committed by GitHub
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@ -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
[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
pip install nvflare
pip install nvflare protobuf==3.20.1
```
Prepare the data:
@ -38,12 +39,9 @@ Then start the admin CLI, using `admin/admin` as username/password:
./poc/admin/startup/fl_admin.sh
```
In the admin CLI, run the following commands:
In the admin CLI, run the following command:
```shell
upload_app hello-xgboost
set_run_number 1
deploy_app hello-xgboost all
start_app all
submit_job hello-xgboost
```
Once the training finishes, the model file should be written into