Adds a new page and table to document current scalability thresholds in Ray Tune to the documentation.
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
* [tune] make `tune.with_parameters()` work with the class API
* Update python/ray/tune/utils/trainable.py
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
* Refactor placement group factory object to accept placement_group arguments instead of callables
* Convert resources to pgf
* Enable placement groups per default
* Fix tests WIP
* Fix stop/resume with placement groups
* Fix progress reporter test
* Fix trial executor tests
* Check resource for trial, not resource object
* Move ENV vars into class
* Fix tests
* Sphinx
* Wait for trial start in PBT
* Revert merge errors
* Support trial reuse with placement groups
* Better check for just staged trials
* Fix trial queuing
* Wait for pg after trial termination
* Clean up PGs before tune run
* No PG settings in pbt scheduler
* Fix buffering tests
* Skip test if ray reports erroneous available resources
* Disable PG for cluster resource counting test
* Debug output for tests
* Output in-use resources for placement groups
* Don't start new trial on trial start failure
* Add docs
* Cleanup PGs once futures returned
* Fix placement group shutdown
* Use updated_queue flag
* Apply suggestions from code review
* Apply suggestions from code review
* Update docs
* Reuse placement groups independently from actors
* Do not remove placement groups for paused trials
* Only continue enqueueing trials if it didn't fail the first time
* Rename parameter
* Fix pause trial
* Code review + try_recover
* Update python/ray/tune/utils/placement_groups.py
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
* Move placement group lifecycle management
* Move total used resources to pg manager
* Update FAQ example
* Requeue trial if start was unsuccessful
* Do not cleanup pgs at start of run
* Revert "Do not cleanup pgs at start of run"
This reverts commit 933d9c4c
* Delayed PG removal
* Fix trial requeue test
* Trigger pg cleanup on status update
* Fix tests
* Fix docs
* fix-test
Signed-off-by: Richard Liaw <rliaw@berkeley.edu>
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>
* Support `yield` and `return` statements in Tune trainable functions
* Support anonymous metric with ``tune.report(value)``
* Raise on invalid return/yield value
* Fix end to end reporter test
* Added basic functionality and tests
* Feature parity with old tune search space config
* Convert Optuna search spaces
* Introduced quantized values
* Updated Optuna resolving
* Added HyperOpt search space conversion
* Convert search spaces to AxSearch
* Convert search spaces to BayesOpt
* Added basic functionality and tests
* Feature parity with old tune search space config
* Convert Optuna search spaces
* Introduced quantized values
* Updated Optuna resolving
* Added HyperOpt search space conversion
* Convert search spaces to AxSearch
* Convert search spaces to BayesOpt
* Re-factored samplers into domain classes
* Re-added base classes
* Re-factored into list comprehensions
* Added `from_config` classmethod for config conversion
* Applied suggestions from code review
* Removed truncated normal distribution
* Set search properties in tune.run
* Added test for tune.run search properties
* Move sampler initializers to base classes
* Add tune API sampling test, fixed includes, fixed resampling bug
* Add to API docs
* Fix docs
* Update metric and mode only when set. Set default metric and mode to experiment analysis object.
* Fix experiment analysis tests
* Raise error when delimiter is used in the config keys
* Added randint/qrandint to API docs, added additional check in tune.run
* Fix tests
* Fix linting error
* Applied suggestions from code review. Re-aded tune.function for the time being
* Fix sampling tests
* Fix experiment analysis tests
* Fix tests and linting error
* Removed unnecessary default_config attribute from OptunaSearch
* Revert to set AxSearch default metric
* fix-min-max
* fix
* nits
* Added function check, enhanced loguniform error message
* fix-print
* fix
* fix
* Raise if unresolved values are in config and search space is already set
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
