Implement a first pass at actors in the API. (#242)

* 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.

python/photon/test/test.py

@@ -18,6 +18,8 @@ import plasma
 USE_VALGRIND = False
 ID_SIZE = 20
 
+NIL_ACTOR_ID = 20 * b"\xff"
+
 def random_object_id():
   return photon.ObjectID(np.random.bytes(ID_SIZE))
 
@@ -39,7 +41,7 @@ class TestPhotonClient(unittest.TestCase):
     # Start a local scheduler.
     scheduler_name, self.p2 = photon.start_local_scheduler(plasma_store_name, use_valgrind=USE_VALGRIND)
     # Connect to the scheduler.
-    self.photon_client = photon.PhotonClient(scheduler_name)
+    self.photon_client = photon.PhotonClient(scheduler_name, NIL_ACTOR_ID)
 
   def tearDown(self):
     # Check that the processes are still alive.