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140a180ebb
Xgboosts train_small timed out because of a CPU borrowing feature related to placement groups. The root bug will be fixed in the coming weeks, but this PR makes the release test consistently pass by requesting 0 CPUs for the remote wrapper script. |
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| .. | ||
| workloads | ||
| app_config.yaml | ||
| app_config_gpu.yaml | ||
| create_test_data.py | ||
| README.rst | ||
| tpl_cpu_moderate.yaml | ||
| tpl_cpu_small.yaml | ||
| tpl_gpu_small.yaml | ||
| wait_cluster.py | ||
| xgboost_tests.yaml | ||
XGBoost on Ray tests ==================== This directory contains various XGBoost on Ray release tests. You should run these tests with the `releaser <https://github.com/ray-project/releaser>`_ tool. Overview -------- There are four kinds of tests: 1. ``distributed_api_test`` - checks general API functionality and should finish very quickly (< 1 minute) 2. ``train_*`` - checks single trial training on different setups. 3. ``tune_*`` - checks multi trial training via Ray Tune. 4. ``ft_*`` - checks fault tolerance. Generally the releaser tool will run all tests in parallel, but if you do it sequentially, be sure to do it in the order above. If ``train_*`` fails, ``tune_*`` will fail, too. Acceptance criteria ------------------- These tests are considered passing when they throw no error at the end of the output log.