* Implement actor field for tasks
* Implement actor management in local scheduler.
* initial python frontend for actors
* import actors on worker
* IPython code completion and tests
* prepare creating actors through local schedulers
* add actor id to PyTask
* submit actor calls to local scheduler
* starting to integrate
* simple fix
* Fixes from rebasing.
* more work on python actors
* Improve local scheduler actor handlers.
* Pass actor ID to local scheduler when connecting a client.
* first working version of actors
* fixing actors
* fix creating two copies of the same actor
* fix actors
* remove sleep
* get rid of export synchronization
* update
* insert actor methods into the queue in the right order
* remove print statements
* make it compile again after rebase
* Minor updates.
* fix python actor ids
* Pass actor_id to start_worker.
* add test
* Minor changes.
* Update actor tests.
* Temporary plan for import counter.
* Temporarily fix import counters.
* Fix some tests.
* Fixes.
* Make actor creation non-blocking.
* Fix test?
* Fix actors on Python 2.
* fix rare case.
* Fix python 2 test.
* More tests.
* Small fixes.
* Linting.
* Revert tensorflow version to 0.12.0 temporarily.
* Small fix.
* Enhance inheritance test.
* Start and clean up workers from the local scheduler
Ability to kill workers in photon scheduler
Test for old method of starting workers
Common codepath for killing workers
Common codepath for killing workers
Photon test case for starting and killing workers
fix build
Fix component failure test
Register a worker's pid as part of initial connection
Address comments and revert photon_connect
Set PATH during travis install
Fix
* Fix photon test case to accept clients on plasma manager fd
* attribute-based heterogeneity-awareness in global scheduler and photon
* minor post-rebase fix
* photon: enforce dynamic capacity constraint on task dispatch
* globalsched: cap the number of times we try to schedule a task in round robin
* propagating ability to specify resource capacity to ray.init
* adding resources to remote function export and fetch/register
* globalsched: remove unused functions; update cached photon resource capacity (until next photon heartbeat)
* Add some integration tests.
* globalsched: cleanup + factor out constraint checking
* lots of style
* task_spec_required_resource: global refactor
* clang format
* clang format + comment update in photon
* clang format photon comment
* valgrind
* reduce verbosity for Travis
* Add test for scheduler load balancing.
* addressing comments
* refactoring global scheduler algorithm
* Minor cleanups.
* Linting.
* Fix array_test.py and linting.
* valgrind fix for photon tests
* Attempt to fix stress tests.
* fix hashmap free
* fix hashmap free comment
* memset photon resource vectors to 0 in case they get used before the first heartbeat
* More whitespace changes.
* Undo whitespace error I introduced.
* Provide functionality for local scheduler to start new workers.
* Pass full command for starting new worker in to local scheduler.
* Separate out configuration state of local scheduler.
* Optimizations:
- Track mapping of missing object to dependent tasks to avoid iterating over task queue
- Perform all fetch requests for missing objects using the same timer
* Fix bug and add regression test
* Record task dependencies and active fetch requests in the same hash table
* fix typo
* Fix memory leak and add test cases for scheduling when dependencies are evicted
* Fix python3 test case
* Minor details.
