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Adding basic support for a user-interpretable resource label (#761)

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* adding support for the user-interpretable label(UIR)

* more plumbing for num_uirs further upstream; set to infty when specified on cmd line

* pass default num_uirs for actors; update GlobalStateAPI

* support num_uirs in ray.init()

* local scheduler resource accounting: support num_uirs; prep for vectorized resource accounting

* global scheduler test updated

* Fix bug introduced by rebase.

* Rename UIR -> CustomResource and add test.

* Small changes and use constexpr instead of macros.

* Linting and some renaming.

* Reorder some code.

* Remove cpus_in_use and fix bug.

* Add another test and make a small change.

* Rephrase documentation about feature stability.
This commit is contained in:
Alexey Tumanov
2017-08-08 02:53:59 -07:00
committed by Philipp Moritz
parent 03f2325780
commit fc885bd918
14 changed files with 242 additions and 82 deletions
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python/ray/actor.py
+4 -1
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@@ -105,6 +105,7 @@ def fetch_and_register_actor(actor_class_key, worker):
FunctionProperties(num_return_vals=1,
num_cpus=1,
num_gpus=0,
num_custom_resource=0,
max_calls=0))
worker.num_task_executions[driver_id][function_id] = 0
@@ -174,6 +175,7 @@ def export_actor(actor_id, class_id, actor_method_names, num_cpus, num_gpus,
FunctionProperties(num_return_vals=1,
num_cpus=1,
num_gpus=0,
num_custom_resource=0,
max_calls=0))
# Select a local scheduler for the actor.
@@ -259,7 +261,8 @@ def reconstruct_actor_state(actor_id, worker):
hex_to_object_id(task_spec_info["ActorID"]),
task_spec_info["ActorCounter"],
[task_spec_info["RequiredResources"]["CPUs"],
task_spec_info["RequiredResources"]["GPUs"]])
task_spec_info["RequiredResources"]["GPUs"],
task_spec_info["RequiredResources"]["CustomResource"]])
# Verify that the return object IDs are the same as they were the
# first time.