Adds a unit-tested and restructured ray_release package for running release tests.
Relevant changes in behavior:
Per default, Buildkite will wait for the wheels of the current commit to be available. Alternatively, users can a) specify a different commit hash, b) a wheels URL (which we will also wait for to be available) or c) specify a branch (or user/branch combination), in which case the latest available wheels will be used (e.g. if master is passed, behavior matches old default behavior).
The main subpackages are:
Cluster manager: Creates cluster envs/computes, starts cluster, terminates cluster
Command runner: Runs commands, e.g. as client command or sdk command
File manager: Uploads/downloads files to/from session
Reporter: Reports results (e.g. to database)
Much of the code base is unit tested, but there are probably some pieces missing.
Example build (waited for wheels to be built): https://buildkite.com/ray-project/kf-dev/builds/51#_
Wheel build: https://buildkite.com/ray-project/ray-builders-branch/builds/6023
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
Please review **e2e.py and test_suite belonging to your team**!
This is the first part of https://docs.google.com/document/d/16IrwerYi2oJugnRf5hvzukgpJ6FAVEpB6stH_CiNMjY/edit#
This PR adds a team name to each test suite.
If the name is not specified, it will be reported as unspecified.
If you are running a local test, and if the new test suite doesn't have a team name specified, it will raise an exception (in this way, we can avoid missing team names in the future).
Note that we will aggregate all of test config into a single file, nightly_test.yaml.
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.
* 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
