85b2fb3eee
* Integrating a faster version of grow_gpu plugin 1. Removed the older files to reduce duplication 2. Moved all of the grow_gpu files under 'exact' folder 3. All of them are inside 'exact' namespace to avoid any conflicts 4. Fixed a bug in benchmark.py while running only 'grow_gpu' plugin 5. Added cub and googletest submodules to ease integration and unit-testing 6. Updates to CMakeLists.txt to directly build cuda objects into libxgboost * Added support for building gpu plugins through make flow 1. updated makefile and config.mk to add right targets 2. added unit-tests for gpu exact plugin code * 1. Added support for building gpu plugin using 'make' flow as well 2. Updated instructions for building and testing gpu plugin * Fix travis-ci errors for PR#2360 1. lint errors on unit-tests 2. removed googletest, instead depended upon dmlc-core provide gtest cache * Some more fixes to travis-ci lint failures PR#2360 * Added Rory's copyrights to the files containing code from both. * updated copyright statement as per Rory's request * moved the static datasets into a script to generate them at runtime * 1. memory usage print when silent=0 2. tests/ and test/ folder organization 3. removal of the dependency of googletest for just building xgboost 4. coding style updates for .cuh as well * Fixes for compilation warnings * add cuda object files as well when JVM_BINDINGS=ON
XGBoost Plugins Modules
This folder contains plugin modules to xgboost that can be optionally installed. The plugin system helps us to extend xgboost with additional features, and add experimental features that may not yet be ready to be included in the main project.
To include a certain plugin, say plugin_a, you only need to add the following line to the config.mk.
# Add plugin by including the plugin in config.mk
XGB_PLUGINS += plugin/plugin_a/plugin.mk
Then rebuild libxgboost by typing make, you can get a new library with the plugin enabled.
Link Static XGBoost Library with Plugins
This problem only happens when you link libxgboost.a.
If you only use libxgboost.so(this include python and other bindings),
you can ignore this section.
When you want to link libxgboost.a with additional plugins included,
you will need to enabled whole archive via The following option.
--whole-archive libxgboost.a --no-whole-archive
Write Your Own Plugin
You can plugin your own modules to xgboost by adding code to this folder, without modification to the main code repo. The example folder provides an example to write a plugin.
List of register functions
A plugin has to register a new functionality to xgboost to be able to use it. The register macros available to plugin writers are:
- XGBOOST_REGISTER_METRIC - Register an evaluation metric
- XGBOOST_REGISTER_GBM - Register a new gradient booster that learns through gradient statistics
- XGBOOST_REGISTER_OBJECTIVE - Register a new objective function used by xgboost
- XGBOOST_REGISTER_TREE_UPDATER - Register a new tree-updater which updates the tree given the gradient information
And from dmlc-core:
- DMLC_REGISTER_PARAMETER - Register a set of parameter for a specific usecase
- DMLC_REGISTER_DATA_PARSER - Register a data parser where the data can be represented by a URL. This is used by DMatrix.