Instead of wrapping the whole training run in a remote call, we only query the files on the node in a remote call. XGBoost-Ray is then started from the local node.
* [xgboost] Fix release test app configs
* Revert full app config
* Update base docker image
* Only change cpu base image
* default
* Pin xgboost to 1.5. in cpu tests
* Remove numpy hack
* Revert one line
Co-authored-by: Amog Kamsetty <amogkamsetty@yahoo.com>
* use nightly
* switch ml cpu to ray cpu
* fix
* add pytest
* add more pytest
* add constraint
* add tensorflow
* fix merge conflict
* add tblib
* fix
* add back uninstall