mirror of
https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
b1308b1c8c
This fixes the previous problems from team column revert. This has 2 additional changes; alert handler receives the team argument, which was the root cause of breakage; https://github.com/ray-project/ray/pull/21289 Previously, tests without a team column were raising an exception, but I made the condition weaker (warning logs). I will eventually change it to raise an exception, but for smoother transition, we will log warning instead for a short time |
||
|---|---|---|
| .. | ||
| learning_tests | ||
| multi_gpu_learning_tests | ||
| multi_gpu_with_attention_learning_tests | ||
| multi_gpu_with_lstm_learning_tests | ||
| performance_tests | ||
| stress_tests | ||
| unit_gpu_tests | ||
| 1gpu_4cpus.yaml | ||
| 2gpus_32cpus.yaml | ||
| 4gpus_64cpus.yaml | ||
| 4gpus_544_cpus.yaml | ||
| 8gpus_64cpus.yaml | ||
| 8gpus_96cpus.yaml | ||
| 12gpus_192cpus.yaml | ||
| app_config.yaml | ||
| README.rst | ||
| rllib_tests.yaml | ||
| wait_cluster.py | ||
RLlib Tests =========== This directory contains various RLlib release tests. You should run these tests with the `releaser <https://github.com/ray-project/releaser>`_ tool. Overview -------- Currently, there are 3 RLlib tests: 1. ``learning_tests`` - Tests, whether major algos (tf+torch) can learn in Atari or PyBullet envs in ~30-60min. 1. ``stress_tests`` - Runs 4 IMPALA Atari jobs, each one using 1GPU and 128CPUs (needs autoscaling to succeed). 1. ``unit_gpu_tests`` - Tests, whether all of RLlib's example scripts can be run on a GPU. Generally the releaser tool will run all tests in parallel. Acceptance criteria ------------------- These tests are considered passing when they throw no error at the end of the output log.