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.
This is the second part of https://docs.google.com/document/d/12qP3x5uaqZSKS-A_kK0ylPOp0E02_l-deAbmm8YtdFw/edit#. After this PR, dashboard agents will fully work with minimal ray installation.
Note that this PR requires to introduce "aioredis", "frozenlist", and "aiosignal" to the minimal installation. These dependencies are very small (or will be removed soon), and including them to minimal makes thing very easy. Please see the below for the reasoning.
This PR moves the sdk to its own folder, then includes everything in `import ray.autoscaler.sdk` in ray's import path.
Note: that there were circular dependencies in naively doing this because the ray core now uses constants that were defined in the autoscaler for internal kv operations (and the autoscaler similarly calls into the ray core). The solution was to move those internal kv keys into ray core constants so the imports flow (more) one way.
Co-authored-by: Alex Wu <alex@anyscale.com>
This patch fixed two issues.
1. log_monitor.py can crash when gcs is not temporarily available. Added retry logic in gcs_pubsub.py.
2. it is possible that the signal handler can raise another exception during exception handling.
This PR adds a `CometLoggerCallback` to the Tune Integrations, allowing users to log runs from Ray to [Comet](https://www.comet.ml/site/).
Co-authored-by: Michael Cullan <mjcullan@gmail.com>
Co-authored-by: Antoni Baum <antoni.baum@protonmail.com>
Resubmitting #21705 which was merged then reverted. It seems somehow sphinx building broke in the meantime, not clear how it is connected to this PR.
Here is the original description:
>Part of the effort to enable tests on windows, this enables test_metrics and test_metric_agents, which pass locally.
There was a user request to disable runtime env logs. This is the first PR that allows users to disable runtime env logs through an env var. Basically if users specify `RAY_RUNTIME_ENV_LOG_TO_DRIVER_ENABLED =0`, this will disable runtime env logs.
Note that in the log monitor RAY_RUNTIME_ENV_LOG_TO_DRIVER_ENABLED=1 by default. This is temporary, and I'd like to make this 0 by default after improving runtime error failure messages.
Once we disable log msgs by default, we can unify `RAY_RUNTIME_ENV_LOG_TO_DRIVER_ENABLED` and `RAY_RUNTIME_ENV_LOCAL_DEV_MODE`
Now if an actor throws an exception containing non-ASCII characters, the actor won't die and will be alive.
This is because the following exception occurred during handling the user's exception:
```
File "python/ray/_raylet.pyx", line 587, in ray._raylet.task_execution_handler
File "python/ray/_raylet.pyx", line 434, in ray._raylet.execute_task
File "python/ray/_raylet.pyx", line 551, in ray._raylet.execute_task
File "/home/admin/.local/lib/python3.6/site-packages/ray/utils.py", line 96, in push_error_to_driver
worker.core_worker.push_error(job_id, error_type, message, time.time())
File "python/ray/_raylet.pyx", line 1636, in ray._raylet.CoreWorker.push_error
UnicodeEncodeError: 'ascii' codec can't encode characters in position 2597-2600: ordinal not in range(128)
An unexpected internal error occurred while the worker was executing a task.
```
This PR fixes this issue.
Currently, when we destroy the created placement group, we will kill all workers that are related to this placement group, however, we only killed the running worker at this time, if there is a worker which startup very slow and the related placement group was already destroyed before the worker startup successfully, then there will be a worker leak.
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).
RayDP needs to be updated to work with redisless ray.
To be more specific this [line](c08a786770/python/raydp/spark/ray_cluster_master.py (L146)
) needs to be updated to using `node.address`
We should update this after the release with the feature being turned on by default.
Currently, the docs have an [end-to-end tutorial](https://web.archive.org/web/20211122152843/https://docs.ray.io/en/latest/serve/tutorial.html) walking users through deploying a `Counter` function on Serve. This PR adds an end-to-end tutorial walking users through deploying an entire Hugging Face model using Serve, providing a better understanding of how to deploy an actual model via Serve.
Co-authored-by: Edward Oakes <ed.nmi.oakes@gmail.com>
Co-authored-by: Simon Mo <simon.mo@hey.com>
Currently `wait_until_succeeded_without_exception` is used in the dashboard, and it returns True/False. Unfortunately, there are lots of code that doesn't assert on this method (which means things are not actually tested).
This PR fixes issues with loading ExperimentAnalysis from path or pickle if the trainable used in the trials is not registered. Chiefly, it ensures that the stub attribute set in load_trials_from_experiment_checkpoint doesn't get overridden by the state of the loaded trial, and that when pickling, all trials in ExperimentAnalysis are turned into stubs if they aren't already. A test has also been added.
Full context see https://github.com/ray-project/ray/issues/21791
pytest work for "some" environments for this test and on CI master, but this decorator is still unnecessary and was introduced by mistake. So just remove it and see what happens with the original issue.
Support the ability to specify a default lifetime for actors which are not specified lifetime when creating. This is a job level configuration item.
#### API Change
The Python API looks like:
```python
ray.init(job_config=JobConfig(default_actor_lifetime="detached"))
```
Java API looks like:
```java
System.setProperty("ray.job.default-actor-lifetime", defaultActorLifetime.name());
Ray.init();
```
One example usage is:
```python
ray.init(job_config=JobConfig(default_actor_lifetime="detached"))
a1 = A.options(lifetime="non_detached").remote() # a1 is a non-detached actor.
a2 = A.remote() # a2 is a non-detached actor.
```
Co-authored-by: Kai Yang <kfstorm@outlook.com>
Co-authored-by: Qing Wang <jovany.wq@antgroup.com>
By default, ~/ray_results/exp_name/trial_name/checkpoint_name.
Instead of the whole trial checkpoint (~/ray_results/exp_name/trial_name/) directory.
Stuff like progress.csv, result.json, params.pkl, params.json, events.out etc are coming from driver process.
This could also enable us to de-couple sync up and delete - they don't have to wait for each other to finish.
Currently, GCS KV client only has blocking API. Calling them from dashboard event loop can block other operations for many seconds, leading to failures such as taking too long (> 2min) to submit a job and making nightly tests fail (#21699). This PR offloads the blocking work to a separate thread. Implementing async GCS KV API will be done in the future.
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).
