* Working prototype
* Pass buffer length, fix tests
* Don't buffer per default
* Dispatch and process save in one go, added tests
* Fix tests
* Pass adaptive seconds to train_buffered, stop result processing after STOP decision
* Fix tests, add release test
* Update tests
* Added detailed logs for slow operations
* Update python/ray/tune/trial_runner.py
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
* Apply suggestions from code review
* Revert tests and go back to old tuning loop
* nit
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
* Add DockerSyncer
* Add docs
* Update python/ray/tune/integration/docker.py
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
* Updated docs
* fix dir
* Added docker integration test
* added docker integration test to bazel build
* Use sdk.rsync API
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
* wip
* Update local mode docs in all locations
* Update doc/source/actors.rst
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
* Update doc/source/actors.rst
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
* Change duplicated text to links to a subtitle for local_mode
* change a reference to be explicit
* Apply suggestions from code review
Co-authored-by: Max Fitton <max@semprehealth.com>
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
* Add `log_to_file` parameter, pass to Trainable config, redirect stdout/stderr.
* Add logging handler to root ray logger
* Added test for `log_to_file` parameter
* Added logs, reuse test
* Revert debug change
* Update logdir on reset, flush streams after each train() step
* Remove magic keys from visible config
Co-authored-by: Kai Fricke <kai@anyscale.com>
