Treat actor creation like a regular task. (#1668)

* Treat actor creation like a regular task.

* Small cleanups.

* Change semantics of actor resource handling.

* Bug fix.

* Minor linting

* Bug fix

* Fix jenkins test.

* Fix actor tests

* Some cleanups

* Bug fix

* Fix bug.

* Remove cached actor tasks when a driver is removed.

* Add more info to taskspec in global state API.

* Fix cyclic import bug in tune.

* Fix

* Fix linting.

* Fix linting.

* Don't schedule any tasks (especially actor creaiton tasks) on local schedulers with 0 CPUs.

* Bug fix.

* Add test for 0 CPU case

* Fix linting

* Address comments.

* Fix typos and add comment.

* Add assertion and fix test.

python/ray/experimental/state.py

@@ -16,6 +16,8 @@ from ray.utils import (decode, binary_to_object_id, binary_to_hex,
 # Import flatbuffer bindings.
 from ray.core.generated.TaskReply import TaskReply
 from ray.core.generated.ResultTableReply import ResultTableReply
+from ray.core.generated.TaskExecutionDependencies import \
+    TaskExecutionDependencies
 
 # These prefixes must be kept up-to-date with the definitions in
 # ray_redis_module.cc.
@@ -262,17 +264,35 @@ class GlobalState(object):
             "ParentTaskID": binary_to_hex(task_spec.parent_task_id().id()),
             "ParentCounter": task_spec.parent_counter(),
             "ActorID": binary_to_hex(task_spec.actor_id().id()),
+            "ActorCreationID":
+                binary_to_hex(task_spec.actor_creation_id().id()),
+            "ActorCreationDummyObjectID":
+                binary_to_hex(task_spec.actor_creation_dummy_object_id().id()),
             "ActorCounter": task_spec.actor_counter(),
             "FunctionID": binary_to_hex(task_spec.function_id().id()),
             "Args": task_spec.arguments(),
             "ReturnObjectIDs": task_spec.returns(),
             "RequiredResources": task_spec.required_resources()}
 
+        execution_dependencies_message = (
+            TaskExecutionDependencies.GetRootAsTaskExecutionDependencies(
+                task_table_message.ExecutionDependencies(), 0))
+        execution_dependencies = [
+            ray.local_scheduler.ObjectID(
+                execution_dependencies_message.ExecutionDependencies(i))
+            for i in range(
+                execution_dependencies_message.ExecutionDependenciesLength())]
+
+        # TODO(rkn): The return fields ExecutionDependenciesString and
+        # ExecutionDependencies are redundant, so we should remove
+        # ExecutionDependencies. However, it is currently used in monitor.py.
+
         return {"State": task_table_message.State(),
                 "LocalSchedulerID": binary_to_hex(
                     task_table_message.LocalSchedulerId()),
                 "ExecutionDependenciesString":
                     task_table_message.ExecutionDependencies(),
+                "ExecutionDependencies": execution_dependencies,
                 "SpillbackCount":
                     task_table_message.SpillbackCount(),
                 "TaskSpec": task_spec_info}