## Why are these changes needed?
This is part of redis removal project. In this PR all direct usage of redis got removed except function table.
Function table will be migrated in the next PR
## Related issue number
#19443
* 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
* [Core]Make convertion between ray/grpc status more specific
* per comments
* lint
* per comments
* use ABORT instead of UNKNOWN, add some tests
* lint
* lint
## Why are these changes needed?
## Related issue number
Final part of #13984
## Checks
- [x] I've run `scripts/format.sh` to lint the changes in this PR.
- [x] I've included any doc changes needed for https://docs.ray.io/en/master/.
- [x] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/
- Testing Strategy
- [x] Unit tests
- [ ] Release tests
- [ ] This PR is not tested :(
To avoid exporting thrirdparty library symbol globally, these absl/grpc libs have been applied in _streaming.so.
Side-effect:
Static variables might be uninitialized if core worker lib and streaming lib both use them.
* Create a core set of algorithms tests to run nightly.
* Run release tests under tf, tf2, and torch frameworks.
* Fix
* Add eager_tracing option for tf2 framework.
* make sure core tests can run in parallel.
* cql
* Report progress while running nightly/weekly tests.
* Innclude SAC in nightly lineup.
* Revert changes to learning_tests
* rebrand to performance test.
* update build_pipeline.py with new performance_tests name.
* Record stats.
* bug fix, need to populate experiments dict.
* Alphabetize yaml files.
* Allow specifying frameworks. And do not run tf2 by default.
* remove some debugging code.
* fix
* Undo testing changes.
* Do not run CQL regression for now.
* LINT.
Co-authored-by: sven1977 <svenmika1977@gmail.com>
## Why are these changes needed?
Currently, when `WorkerContext::GetCurrentTaskID()` returns a random task ID in user-created threads, and the returned task ID doesn't include the job ID. In this case, subsequent non-actor tasks and return values, and objects created by `ray.put()` don't include the job ID neither. This makes us hard to find the correct job ID from a task or object ID.
This PR updates the task ID generation code to always encode the job ID.
A side-effect of this PR is the change of possibility of task ID collision in user-created threads due to the fixed job ID part. w/o this PR: `sqrt(pi * 256 ^ 12 / 2)` ~= 352 trillion tasks. w/ this PR: `sqrt(pi * 256 ^ 8 / 2)` ~= 5 billion tasks. But this should be OK because the job ID part of task IDs in non-user-created threads are always fixed, so it won't be worse than non-user-created threads.
## Related issue number
## Checks
- [ ] I've run `scripts/format.sh` to lint the changes in this PR.
- [ ] I've included any doc changes needed for https://docs.ray.io/en/master/.
- [ ] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/
- Testing Strategy
- [ ] Unit tests
- [ ] Release tests
- [ ] This PR is not tested :(
