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Deprecate num_workers argument to ray.init and ray start. (#3114)

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* Remove num_workers argument.

* Fix

* Fix
This commit is contained in:
Robert Nishihara
2018-10-28 20:12:49 -07:00
committed by Philipp Moritz
parent 9868af4c7c
commit 32f0d6b77e
17 changed files with 31 additions and 72 deletions
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python/benchmarks/benchmark_actor.py
+1 -1
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@@ -9,7 +9,7 @@ NUM_WORKERS = 4
def setup():
if not hasattr(setup, "is_initialized"):
ray.init(num_workers=NUM_WORKERS, num_cpus=4)
ray.init(num_cpus=4)
setup.is_initialized = True
python/benchmarks/benchmark_get.py
+1 -1
View File
@@ -9,7 +9,7 @@ import ray
def setup():
if not hasattr(setup, "is_initialized"):
ray.init(num_workers=4, num_cpus=4)
ray.init(num_cpus=4)
setup.is_initialized = True
python/benchmarks/benchmark_put.py
+1 -1
View File
@@ -9,7 +9,7 @@ import ray
def setup():
if not hasattr(setup, "is_initialized"):
ray.init(num_workers=4, num_cpus=4)
ray.init(num_cpus=0)
setup.is_initialized = True
python/benchmarks/benchmark_queue.py
+1 -1
View File
@@ -8,7 +8,7 @@ from ray.experimental.queue import Queue
def setup():
if not hasattr(setup, "is_initialized"):
ray.init(num_workers=4, num_cpus=4)
ray.init(num_cpus=4)
setup.is_initialized = True
python/benchmarks/benchmark_task.py
+1 -1
View File
@@ -7,7 +7,7 @@ import ray
def setup():
if not hasattr(setup, "is_initialized"):
ray.init(num_workers=10, num_cpus=10, resources={"foo": 1})
ray.init(num_cpus=10, resources={"foo": 1})
setup.is_initialized = True
python/benchmarks/benchmark_wait.py
+1 -1
View File
@@ -9,7 +9,7 @@ import ray
def setup(*args):
if not hasattr(setup, "is_initialized"):
ray.init(num_workers=4, num_cpus=4)
ray.init(num_cpus=4)
setup.is_initialized = True
python/benchmarks/benchmarks.py
+1 -1
View File
@@ -7,7 +7,7 @@ import ray
def setup():
if not hasattr(setup, "is_initialized"):
ray.init(num_workers=4, num_cpus=4)
ray.init(num_cpus=4)
setup.is_initialized = True
python/ray/services.py
+4 -3
View File
@@ -1328,7 +1328,8 @@ def start_ray_processes(address_info=None,
resources = num_local_schedulers * [resources]
if num_workers is not None:
workers_per_local_scheduler = num_local_schedulers * [num_workers]
raise Exception("The 'num_workers' argument is deprecated. Please use "
"'num_cpus' instead.")
else:
workers_per_local_scheduler = []
for resource_dict in resources:
@@ -1479,7 +1480,7 @@ def start_ray_node(node_ip_address,
redis_address,
object_manager_ports=None,
node_manager_ports=None,
num_workers=0,
num_workers=None,
num_local_schedulers=1,
object_store_memory=None,
redis_password=None,
@@ -1572,7 +1573,7 @@ def start_ray_head(address_info=None,
node_ip_address="127.0.0.1",
redis_port=None,
redis_shard_ports=None,
num_workers=0,
num_workers=None,
num_local_schedulers=1,
object_store_memory=None,
worker_path=None,
python/ray/worker.py
-4
View File
@@ -1303,8 +1303,6 @@ def _init(address_info=None,
object IDs. The same value can be used across multiple runs of the
same job in order to generate the object IDs in a consistent
manner. However, the same ID should not be used for different jobs.
num_workers (int): The number of workers to start. This is only
provided if start_ray_local is True.
num_local_schedulers (int): The number of local schedulers to start.
This is only provided if start_ray_local is True.
object_store_memory: The maximum amount of memory (in bytes) to
@@ -1554,8 +1552,6 @@ def init(redis_address=None,
object IDs. The same value can be used across multiple runs of the
same job in order to generate the object IDs in a consistent
manner. However, the same ID should not be used for different jobs.
num_workers (int): The number of workers to start. This is only
provided if redis_address is not provided.
local_mode (bool): True if the code should be executed serially
without Ray. This is useful for debugging.
redirect_worker_output: True if the stdout and stderr of worker
test/actor_test.py
+6 -15
View File
@@ -718,7 +718,7 @@ def test_actor_load_balancing(shutdown_only):
num_local_schedulers = 3
ray.worker._init(
start_ray_local=True,
num_workers=0,
num_cpus=1,
num_local_schedulers=num_local_schedulers)
@ray.remote
@@ -764,7 +764,6 @@ def test_actor_gpus(shutdown_only):
num_gpus_per_scheduler = 4
ray.worker._init(
start_ray_local=True,
num_workers=0,
num_local_schedulers=num_local_schedulers,
num_cpus=(num_local_schedulers * [10 * num_gpus_per_scheduler]),
num_gpus=(num_local_schedulers * [num_gpus_per_scheduler]))
@@ -807,7 +806,6 @@ def test_actor_multiple_gpus(shutdown_only):
num_gpus_per_scheduler = 5
ray.worker._init(
start_ray_local=True,
num_workers=0,
num_local_schedulers=num_local_schedulers,
num_cpus=(num_local_schedulers * [10 * num_gpus_per_scheduler]),
num_gpus=(num_local_schedulers * [num_gpus_per_scheduler]))
@@ -878,7 +876,6 @@ def test_actor_different_numbers_of_gpus(shutdown_only):
# numbers of GPUs.
ray.worker._init(
start_ray_local=True,
num_workers=0,
num_local_schedulers=3,
num_cpus=[10, 10, 10],
num_gpus=[0, 5, 10])
@@ -919,7 +916,6 @@ def test_actor_multiple_gpus_from_multiple_tasks(shutdown_only):
num_gpus_per_scheduler = 10
ray.worker._init(
start_ray_local=True,
num_workers=0,
num_local_schedulers=num_local_schedulers,
redirect_output=True,
num_cpus=(num_local_schedulers * [10 * num_gpus_per_scheduler]),
@@ -968,7 +964,6 @@ def test_actors_and_tasks_with_gpus(shutdown_only):
num_gpus_per_scheduler = 6
ray.worker._init(
start_ray_local=True,
num_workers=0,
num_local_schedulers=num_local_schedulers,
num_cpus=num_gpus_per_scheduler,
num_gpus=(num_local_schedulers * [num_gpus_per_scheduler]))
@@ -1283,7 +1278,7 @@ def test_local_scheduler_dying(shutdown_only):
ray.worker._init(
start_ray_local=True,
num_local_schedulers=2,
num_workers=0,
num_cpus=1,
redirect_output=True)
@ray.remote
@@ -1399,7 +1394,7 @@ def setup_counter_actor(test_checkpoint=False,
ray.worker._init(
start_ray_local=True,
num_local_schedulers=2,
num_workers=0,
num_cpus=1,
redirect_output=True)
# Only set the checkpoint interval if we're testing with checkpointing.
@@ -1733,7 +1728,7 @@ def _test_nondeterministic_reconstruction(num_forks, num_items_per_fork,
ray.worker._init(
start_ray_local=True,
num_local_schedulers=2,
num_workers=0,
num_cpus=1,
redirect_output=True)
# Make a shared queue.
@@ -2033,7 +2028,7 @@ def test_custom_label_placement(shutdown_only):
ray.worker._init(
start_ray_local=True,
num_local_schedulers=2,
num_workers=0,
num_cpus=2,
resources=[{
"CustomResource1": 2
}, {
@@ -2064,11 +2059,7 @@ def test_custom_label_placement(shutdown_only):
def test_creating_more_actors_than_resources(shutdown_only):
ray.init(
num_workers=0,
num_cpus=10,
num_gpus=2,
resources={"CustomResource1": 1})
ray.init(num_cpus=10, num_gpus=2, resources={"CustomResource1": 1})
@ray.remote(num_gpus=1)
class ResourceActor1(object):
test/component_failures_test.py
-2
View File
@@ -216,7 +216,6 @@ def ray_start_workers_separate_multinode(request):
num_initial_workers = request.param[1]
# Start the Ray processes.
ray.worker._init(
num_workers=(num_initial_workers * num_local_schedulers),
num_local_schedulers=num_local_schedulers,
start_workers_from_local_scheduler=False,
start_ray_local=True,
@@ -260,7 +259,6 @@ def _test_component_failed(component_type):
num_local_schedulers = 4
num_workers_per_scheduler = 8
ray.worker._init(
num_workers=num_workers_per_scheduler,
num_local_schedulers=num_local_schedulers,
start_ray_local=True,
num_cpus=[num_workers_per_scheduler] * num_local_schedulers,
test/credis_test.py
+1 -1
View File
@@ -17,7 +17,7 @@ def parse_client(addr_port_str):
"Tests functionality of the new GCS.")
class CredisTest(unittest.TestCase):
def setUp(self):
self.config = ray.init(num_workers=0)
self.config = ray.init(num_cpus=0)
def tearDown(self):
ray.shutdown()
test/jenkins_tests/multi_node_tests/large_memory_test.py
+1 -1
View File
@@ -7,7 +7,7 @@ import numpy as np
import ray
if __name__ == "__main__":
ray.init(num_workers=0)
ray.init(num_cpus=0)
A = np.ones(2**31 + 1, dtype="int8")
a = ray.put(A)
test/multi_node_test.py
+4 -8
View File
@@ -272,10 +272,6 @@ def test_calling_start_ray_head():
run_and_get_output(["ray", "start", "--head"])
subprocess.Popen(["ray", "stop"]).wait()
# Test starting Ray with a number of workers specified.
run_and_get_output(["ray", "start", "--head", "--num-workers", "20"])
subprocess.Popen(["ray", "stop"]).wait()
# Test starting Ray with a redis port specified.
run_and_get_output(["ray", "start", "--head", "--redis-port", "6379"])
subprocess.Popen(["ray", "stop"]).wait()
@@ -315,10 +311,10 @@ def test_calling_start_ray_head():
# Test starting Ray with all arguments specified.
run_and_get_output([
"ray", "start", "--head", "--num-workers", "2", "--redis-port",
"6379", "--redis-shard-ports", "6380,6381,6382",
"--object-manager-port", "12345", "--num-cpus", "2", "--num-gpus",
"0", "--redis-max-clients", "100", "--resources", "{\"Custom\": 1}"
"ray", "start", "--head", "--redis-port", "6379",
"--redis-shard-ports", "6380,6381,6382", "--object-manager-port",
"12345", "--num-cpus", "2", "--num-gpus", "0",
"--redis-max-clients", "100", "--resources", "{\"Custom\": 1}"
])
subprocess.Popen(["ray", "stop"]).wait()
test/runtest.py
+6 -27
View File
@@ -302,7 +302,7 @@ def test_python_workers(shutdown_only):
# purposes only.
num_workers = 4
ray.worker._init(
num_workers=num_workers,
num_cpus=num_workers,
start_workers_from_local_scheduler=False,
start_ray_local=True)
@@ -315,7 +315,7 @@ def test_python_workers(shutdown_only):
def test_put_get(shutdown_only):
ray.init(num_workers=0)
ray.init(num_cpus=0)
for i in range(100):
value_before = i * 10**6
@@ -1150,7 +1150,6 @@ def test_free_objects_multi_node(shutdown_only):
ray.worker._init(
start_ray_local=True,
num_local_schedulers=3,
num_workers=1,
num_cpus=[1, 1, 1],
resources=[{
"Custom0": 1
@@ -1303,7 +1302,7 @@ def test_local_mode(shutdown_only):
def test_resource_constraints(shutdown_only):
num_workers = 20
ray.init(num_workers=num_workers, num_cpus=10, num_gpus=2)
ray.init(num_cpus=10, num_gpus=2)
@ray.remote(num_cpus=0)
def get_worker_id():
@@ -1379,7 +1378,7 @@ def test_resource_constraints(shutdown_only):
def test_multi_resource_constraints(shutdown_only):
num_workers = 20
ray.init(num_workers=num_workers, num_cpus=10, num_gpus=10)
ray.init(num_cpus=10, num_gpus=10)
@ray.remote(num_cpus=0)
def get_worker_id():
@@ -1668,8 +1667,7 @@ def test_multiple_local_schedulers(shutdown_only):
address_info = ray.worker._init(
start_ray_local=True,
num_local_schedulers=3,
num_workers=1,
num_cpus=[100, 5, 10],
num_cpus=[11, 5, 10],
num_gpus=[0, 5, 1])
# Define a bunch of remote functions that all return the socket name of
@@ -1944,20 +1942,6 @@ def test_specific_gpus(save_gpu_ids_shutdown_only):
ray.get([g.remote() for _ in range(100)])
def test_no_workers(shutdown_only):
ray.init(num_cpus=1, num_workers=0)
@ray.remote
def f():
return 1
# Make sure we can call a remote function. This will require starting a
# new worker.
ray.get(f.remote())
ray.get([f.remote() for _ in range(100)])
def test_blocking_tasks(shutdown_only):
ray.init(num_cpus=1)
@@ -2058,11 +2042,9 @@ def test_load_balancing_with_dependencies(shutdown_only):
# This test ensures that tasks are being assigned to all local
# schedulers in a roughly equal manner even when the tasks have
# dependencies.
num_workers = 3
num_local_schedulers = 3
ray.worker._init(
start_ray_local=True,
num_workers=num_workers,
num_local_schedulers=num_local_schedulers,
num_cpus=1)
@@ -2248,10 +2230,7 @@ def test_log_file_api(shutdown_only):
reason="New GCS API doesn't have a Python API yet.")
def test_workers(shutdown_only):
num_workers = 3
ray.init(
redirect_worker_output=True,
num_cpus=num_workers,
num_workers=num_workers)
ray.init(redirect_worker_output=True, num_cpus=num_workers)
@ray.remote
def f():
test/stress_tests.py
-2
View File
@@ -37,7 +37,6 @@ def ray_start_combination(request):
# Start the Ray processes.
ray.worker._init(
start_ray_local=True,
num_workers=num_workers_per_scheduler,
num_local_schedulers=num_local_schedulers,
num_cpus=10)
yield num_local_schedulers, num_workers_per_scheduler
@@ -191,7 +190,6 @@ def ray_start_reconstruction(request):
ray.worker._init(
address_info=address_info,
start_ray_local=True,
num_workers=1,
num_local_schedulers=num_local_schedulers,
num_cpus=[1] * num_local_schedulers,
redirect_output=True)
test/tempfile_test.py
+2 -2
View File
@@ -79,7 +79,7 @@ def test_raylet_tempfiles():
assert socket_files == {"plasma_store", "raylet"}
ray.shutdown()
ray.init(redirect_worker_output=True, num_workers=0)
ray.init(redirect_worker_output=True, num_cpus=0)
top_levels = set(os.listdir(tempfile_services.get_temp_root()))
assert top_levels == {"ray_ui.ipynb", "sockets", "logs"}
log_files = set(os.listdir(tempfile_services.get_logs_dir_path()))
@@ -93,7 +93,7 @@ def test_raylet_tempfiles():
assert socket_files == {"plasma_store", "raylet"}
ray.shutdown()
ray.init(redirect_worker_output=True, num_workers=2)
ray.init(redirect_worker_output=True, num_cpus=2)
top_levels = set(os.listdir(tempfile_services.get_temp_root()))
assert top_levels == {"ray_ui.ipynb", "sockets", "logs"}
time.sleep(3) # wait workers to start