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# Copyright 2020-2025 The HuggingFace Team. All rights reserved.
#
# 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.
from dataclasses import dataclass, field
from trl.trainer.online_dpo_config import OnlineDPOConfig
@dataclass
class NashMDConfig(OnlineDPOConfig):
r"""
Configuration class for the [`NashMDTrainer`].
Subclass of [`OnlineDPOConfig`] we can use all its arguments and add the following:
Parameters:
mixture_coef (`float` or `list[float]`, *optional*, defaults to `0.5`):
Logit mixture coefficient for the model and reference model. If a list of floats is provided then the
mixture coefficient is selected for each new epoch and the last coefficient is used for the rest of the
epochs.
"""
mixture_coef: list[float] = field(
default_factory=lambda: [0.5],
metadata={
"help": "Logit mixture coefficient for the model and reference model. If a list of floats is provided "
"then the mixture coefficient is selected for each new epoch and the last coefficient is used for the "
"rest of the epochs."
},
)
def __post_init__(self):
super().__post_init__()
if hasattr(self.mixture_coef, "__len__") and len(self.mixture_coef) == 1:
self.mixture_coef = self.mixture_coef[0]
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