File size: 3,287 Bytes
857c2e9 | 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 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 | # Copyright 2024 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.ray.base import RayWorkerGroup, RayResourcePool, RayClassWithInitArgs
@ray.remote
class RefBasicRayActor:
...
class DPEngineRayWorkerGroup(RayWorkerGroup):
class DummyModule:
def __init__(self, core, methods_names) -> None:
self.core = core
def func_generator(method_name):
def func(*args, **kwargs):
return self.core.execute_all_async("execute_engine", method_name, *args, **kwargs)
return func
for method_name in methods_names:
setattr(self, method_name, func_generator(method_name))
def __init__(self, name_prefix, process_dispatch_scheme, use_gpu, engine_type, *args, **kwargs) -> None:
from torch import nn
# print(f"in DataParallelEngineWrapper, name_prefix = {name_prefix}")
if isinstance(process_dispatch_scheme, RayResourcePool):
rpdc = process_dispatch_scheme
else:
rpdc = RayResourcePool(process_on_nodes=process_dispatch_scheme,
use_gpu=use_gpu,
name_prefix=name_prefix,
max_colocate_count=1)
rcia = RayClassWithInitArgs(cls=engine_type, *args, **kwargs)
self._engine_type = engine_type
super().__init__(rpdc, rcia)
nn_module_methods = [
method_name for method_name in dir(nn.Module)
if callable(getattr(nn.Module, method_name)) and not method_name.startswith("__")
]
nn_module_methods += ["__call__"]
def func_generator(method_name):
def func(*args, **kwargs):
return self.execute_all_async(method_name, *args, **kwargs)
return func
print(f"{engine_type} has methods: {dir(engine_type)}")
for method_name in dir(engine_type):
try:
is_callable = callable(getattr(engine_type, method_name))
except Exception as _:
pass
else:
if is_callable and method_name not in dir(RefBasicRayActor):
print(f"register method: {method_name}")
setattr(self, method_name, func_generator(method_name))
self.module = DPEngineRayWorkerGroup.DummyModule(self, nn_module_methods)
@property
def engine(self):
return self.module
def get_model_size_on_rank_zero(self):
results = ray.get([worker.get_model_size_on_rank_zero.remote() for worker in self._workers])
for result in results:
if result is not None:
return result
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