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# 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 importlib
from typing import List, Optional, Type
import torch.nn as nn
# Supported models in Megatron-LM
# Architecture -> (module, class).
_MODELS = {
"LlamaForCausalLM": (
"llama",
("ParallelLlamaForCausalLMRmPadPP", "ParallelLlamaForValueRmPadPP", "ParallelLlamaForCausalLMRmPad"),
),
"Qwen2ForCausalLM": (
"qwen2",
("ParallelQwen2ForCausalLMRmPadPP", "ParallelQwen2ForValueRmPadPP", "ParallelQwen2ForCausalLMRmPad"),
),
"MistralForCausalLM": (
"mistral",
("ParallelMistralForCausalLMRmPadPP", "ParallelMistralForValueRmPadPP", "ParallelMistralForCausalLMRmPad"),
),
}
# return model class
class ModelRegistry:
@staticmethod
def load_model_cls(model_arch: str, value=False) -> Optional[Type[nn.Module]]:
if model_arch not in _MODELS:
return None
megatron = "megatron"
module_name, model_cls_name = _MODELS[model_arch]
if not value: # actor/ref
model_cls_name = model_cls_name[0]
elif value: # critic/rm
model_cls_name = model_cls_name[1]
module = importlib.import_module(f"verl.models.{module_name}.{megatron}.modeling_{module_name}_megatron")
return getattr(module, model_cls_name, None)
@staticmethod
def get_supported_archs() -> List[str]:
return list(_MODELS.keys())
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