* add marvil policy graph
* fix typo
* add offline optimizer and enable running marwil
* fix loss function
* add maintaining the moving average of advantage norm
* use sync replay optimizer for unifying
* remove offline optimizer and use sync replay optimizer
* format by yapf
* add imitation learning objective
* fix according to eric's review
* format by yapf
* revise
* add test data
* marwil
Rename `xray_test.py` to `mini_test.py` and use that in the documentation. Right now we suggest that people run `runtest.py`, but that often doesn't succeed and takes too long.
* Limit Redis max memory to 10GB/shard by default.
* Update stress tests.
* Reorganize
* Update
* Add minimum cap size for object store and redis.
* Small test update.
This PR introduces cluster-level fault tolerance for Tune by checkpointing global state. This occurs with relatively high frequency and allows users to easily resume experiments when the cluster crashes.
Note that this PR may affect automated workflows due to auto-prompting, but this is resolvable.
* Modify: add interface for model
* Modify: remove single quota and build; add metrics
* Modify: flatten into list of dict
* Update distributed_sgd.rst
* Modify: update format with scripts/format.sh
* Update sgd_worker.py
- Surfaces local cluster usage
- Increases visability of these instructions
- Removes some docker docs (that are really out of scope for Ray
documentation IMO)
Closes#3517.
* Init commit for async plasma client
* Create an eventloop model for ray/plasma
* Implement a poll-like selector base on `ray.wait`. Huge improvements.
* Allow choosing workers & selectors
* remove original design
* initial implementation of epoll-like selector for plasma
* Add a param for `worker` used in `PlasmaSelectorEventLoop`
* Allow accepting a `Future` which returns object_id
* Do not need `io.py` anymore
* Create a basic testing model
* fix: `ray.wait` returns tuple of lists
* fix a few bugs
* improving performance & bug fixing
* add test
* several improvements & fixing
* fix relative import
* [async] change code format, remove old files
* [async] Create context wrapper for the eventloop
* [async] fix: context should return a value
* [async] Implement futures grouping
* [async] Fix bugs & replace old functions
* [async] Fix bugs found in tests
* [async] Implement `PlasmaEpoll`
* [async] Make test faster, add tests for epoll
* [async] Fix code format
* [async] Add comments for main code.
* [async] Fix import path.
* [async] Fix test.
* [async] Compatibility.
* [async] less verbose to not annoy the CI.
* [async] Add test for new API
* [async] Allow showing debug info in some of the test.
* [async] Fix test.
* [async] Proper shutdown.
* [async] Lint~
* [async] Move files to experimental and create API
* [async] Use async/await syntax
* [async] Fix names & styles
* [async] comments
* [async] bug fixing & use pytest
* [async] bug fixing & change tests
* [async] use logger
* [async] add tests
* [async] lint
* [async] type checking
* [async] add more tests
* [async] fix bugs on waiting a future while timeout. Add more docs.
* [async] Formal docs.
* [async] Add typing info since these codes are compatible with py3.5+.
* [async] Documents.
* [async] Lint.
* [async] Fix deprecated call.
* [async] Fix deprecated call.
* [async] Implement a more reasonable way for dealing with pending inputs.
* [async] Fix docs
* [async] Lint
* [async] Fix bug: Type for time
* [async] Set our eventloop as the default eventloop so that we can get it through `asyncio.get_event_loop()`.
* [async] Update test & docs.
* [async] Lint.
* [async] Temporarily print more debug info.
* [async] Use `Poll` as a default option.
* [async] Limit resources.
* new async implementation for Ray
* implement linked list
* bug fix
* update
* support seamless async operations
* update
* update API
* fix tests
* lint
* bug fix
* refactor names
* improve doc
* properly shutdown async_api
* doc
* Change the table on the index page.
* Adjust table size.
* Only keeps `as_future`.
* change how we init connection
* init connection in `ray.worker.connect`
* doc
* fix
* Move initialization code into the module.
* Fix docs & code
* Update pyarrow version.
* lint
* Restore index.rst
* Add known issues.
* Apply suggestions from code review
Co-Authored-By: suquark <suquark@gmail.com>
* rename
* Update async_api.rst
* Update async_api.py
* Update async_api.rst
* Update async_api.py
* Update worker.py
* Update async_api.rst
* fix tests
* lint
* lint
* replace the magic number
auto wrap multi-agent dict and tuple spaces by keeping a policy -> preprocessor in the sampler
add some Q-learning debug stats
report min, max of custom metrics
better errors
IMPALA support for multiagent was broken since IMPALA has a requirement that batch sizes be of a certain length. However multi-agent envs can create variable-length batches.
Fix this by adding zero-padding as needed (similar to the RNN case).
