Passing tests: https://buildkite.com/ray-project/periodic-ci/builds/2560#_
Add an echo timestamp to the post build commands of the ray lightning release tests to trigger a cluster env rebuild and get the latest versions of ray lightning. Without this, the cluster env gets cached so an outdated version is installed on the cluster that is different than the one on the driver, resulting in the below failures.
Closes#21871Closes#21863
Also reinstalls the dependencies in the post build commands so old versions are not cached in the Docker images
When the script terminates, it will also terminate its cluster including dashboard, which will prevent subsequent job submissions. Other long running e2e tests do not terminate in smoke test mode, so make `serve_failure` behave the same.
Try to clear the result dir before running the e2e.py script, to avoid failures where the directory already exists, or a file cannot be overwritten due to permission issue.
With the new job-based file copy, fetching results takes longer. We thus have to increase the long running update test check times in order not to run into bogus release test failures.
Also fixes artifact uploading issues.
Many release tests have error messages when copying results with `shutil.copytree()`. e.g.
https://buildkite.com/ray-project/periodic-ci/builds/2511#131c0d22-61a3-4dcf-b80a-de37b68ec591/139-450
This PR tries to make the copying process tolerate existing destination directory. There is logic to remove the destination directory, but I'm not sure why it failed.
This error should not be failing the tests though.
Long running tests are cheap and low overhead (small number of node usage). We should just promote this to run every day so we can catch regressions quickly.
Fix dash on ray large scale test on K8s. Basically, chmod requires a root access, which we don't have it by default in the k8s cluster. We don't need chmod I think (I verified the test passes without it).
This PR consolidates both #21667 and #21759 (look there for features), but improves on them in the following way:
- [x] we reverted renaming of existing projects `tune`, `rllib`, `train`, `cluster`, `serve`, `raysgd` and `data` so that links won't break. I think my consolidation efforts with the `ray-` prefix were a little overeager in that regard. It's better like this. Only the creation of `ray-core` was a necessity, and some files moved into the `rllib` folder, so that should be relatively benign.
- [x] Additionally, we added Algolia `docsearch`, screenshot below. This is _much_ better than our current search. Caveat: there's a sphinx dependency that needs to be replaced (`sphinx-tabs`) by another, newer one (`sphinx-panels`), as the former prevents loading of the `algolia.js` library. Will follow-up in the next PR (hoping this one doesn't get re-re-re-re-reverted).
This PR add four tests for many tasks:
many short tasks send from the single node
many short tasks send from multiple nodes
many long tasks send from multiple nodes
many long tasks send from the single node
TODO: migrate many nodes actor tests to this one.
scheduling envelop should contain:
(tasks): scheduling_test_many_xx_tasks_yy_nodes
(actors):many_nodes_actor_test (to be combined with this one)
(shuffle): pipelined_ingestion_1500_gb_15_windows
(shuffle): dask_on_ray_1tb_sort
The first migration of test into k8s. We are adopting a conservative approach (migrate slowly while we keep existing test suites). Once things are confirmed to be stable, we will migrate with more speed.
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
When a session startup times out due to resources not being available, the session may still come up after that timeout. At that time the control script (e2e.py) is already terminated, so the session runs until the autosuspend limit is hit, incurring unnecessary costs. Instead, we should always trigger session termination on session timeout.
Previous changes failed because a) permission errors b) unzip being unavailable at remote nodes. Instead we are using tar gzip archives now.
This reverts commit 42bcab27e8.
RAY_GCS_ACTOR_SCHEDULING_ENABLED is wrong should be RAY_gcs_actor_scheduling_enabled. Since gcs based actor scheduling is not enabled yet so I just removed this flag.
Expands the `to_torch` method for Datasets with:
* An ability to choose to output a list/dict of feature tensors instead of just one (through setting `feature_columns` to be a list of lists or a dict of lists)
* An ability to choose whether the label should be unsqueezed or not
* An ability to pass `None` as the label (for prediction).
Furthermore, this changes how the `feature_column_dtypes` argument works. Previously, it took a list of dtypes for each feature. However, as the tensor was concatenated in the end, only one dtype mattered (the biggest one). Now, this argument expects a single dtype which will be applied to the features tensor (or a list/dict if `feature_columns` is a list of list/dict of lists).
Unit tests for all cases are included.
Co-authored-by: matthewdeng <matthew.j.deng@gmail.com>
