File size: 2,315 Bytes
1faccd4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 | # Copyright 2025 Bytedance Ltd. and/or its affiliates
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import ray
from verl.single_controller.base.decorator import Dispatch, register
from verl.single_controller.base.worker import Worker
from verl.single_controller.ray.base import RayClassWithInitArgs, RayResourcePool, RayWorkerGroup
from verl.utils.device import get_device_name
class TestActor(Worker):
# TODO: pass *args and **kwargs is bug prone and not very convincing
def __init__(self, x) -> None:
super().__init__()
self.a = x
@register(dispatch_mode=Dispatch.ONE_TO_ALL)
def get(self):
return self.a + self.rank
class TestHighLevelActor(Worker):
def __init__(self, x=None) -> None:
super().__init__()
self.test_actor = TestActor(x=x)
@register(dispatch_mode=Dispatch.ONE_TO_ALL)
def get(self):
return self.test_actor.get()
def test_nested_worker():
ray.init(num_cpus=100)
# create 4 workers, each hold a GPU
resource_pool = RayResourcePool([4], use_gpu=True)
class_with_args = RayClassWithInitArgs(cls=ray.remote(TestActor), x=2)
worker_group = RayWorkerGroup(
resource_pool=resource_pool,
ray_cls_with_init=class_with_args,
name_prefix="worker_group_basic",
device_name=get_device_name(),
)
output = worker_group.get()
assert output == [2, 3, 4, 5]
class_with_args = RayClassWithInitArgs(cls=ray.remote(TestHighLevelActor), x=2)
high_level_worker_group = RayWorkerGroup(
resource_pool=resource_pool,
ray_cls_with_init=class_with_args,
name_prefix="worker_group_basic_2",
device_name=get_device_name(),
)
output_1 = high_level_worker_group.get()
assert output_1 == [2, 3, 4, 5]
ray.shutdown()
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