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[2.5] Updated XGBoost User Guide #3109

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Dec 13, 2024
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21 changes: 11 additions & 10 deletions docs/user_guide/federated_xgboost/secure_xgboost_user_guide.rst
Original file line number Diff line number Diff line change
Expand Up @@ -76,6 +76,15 @@ The following docker image is recommended for GPU training:

nvcr.io/nvidia/pytorch:24.03-py3

Building Encryption Plugins
---------------------------

The secure training requires encryption plugins, which need to be built from the source code
for your specific environment.

To build the plugins, check out the NVFlare source code from https://github.com/NVIDIA/NVFlare and following the
instructions in :github_nvflare_link:`this document. <integration/xgboost/encryption_plugins/README.md>`

.. _xgb_provisioning:

NVFlare Provisioning
Expand Down Expand Up @@ -181,7 +190,7 @@ The plugin can be configured in the ``local/resources.json`` file on clients:
{
"federated_plugin": {
"name": "nvflare",
"path": "/tmp/libnvflare.so"
"path": "/opt/libs/libnvflare.so"
}
}

Expand All @@ -193,7 +202,7 @@ The following environment variables can be used to override the values in the JS
.. code-block:: bash

export NVFLARE_XGB_PLUGIN_NAME=nvflare
export NVFLARE_XGB_PLUGIN_PATH=/tmp/libnvflare.so
export NVFLARE_XGB_PLUGIN_PATH=/opt/libs/libnvflare.so

.. note::

Expand Down Expand Up @@ -222,14 +231,6 @@ For example,

The server_context.tenseal file is not needed.

Building Encryption Plugins
===========================

The plugins need to be built from the source code for your specific environment.

To build the plugins, check out the NVFlare source code from https://github.com/NVIDIA/NVFlare and following the
instructions in :github_nvflare_link:`this document. <integration/xgboost/encryption_plugins/README.md>`

Job Configuration
=================
.. _secure_xgboost_controller:
Expand Down
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