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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 typing import TYPE_CHECKING
from ..import_utils import OptionalDependencyNotAvailable, _LazyModule, is_diffusers_available
_import_structure = {
"alignprop_config": ["AlignPropConfig"],
"alignprop_trainer": ["AlignPropTrainer"],
"bco_config": ["BCOConfig"],
"bco_trainer": ["BCOTrainer"],
"callbacks": [
"LogCompletionsCallback",
"MergeModelCallback",
"RichProgressCallback",
"SyncRefModelCallback",
"WinRateCallback",
],
"cpo_config": ["CPOConfig"],
"cpo_trainer": ["CPOTrainer"],
"ddpo_config": ["DDPOConfig"],
"dpo_config": ["DPOConfig", "FDivergenceConstants", "FDivergenceType"],
"dpo_trainer": ["DPOTrainer"],
"gkd_config": ["GKDConfig"],
"gkd_trainer": ["GKDTrainer"],
"grpo_config": ["GRPOConfig"],
"grpo_trainer": ["GRPOTrainer"],
"iterative_sft_config": ["IterativeSFTConfig"],
"iterative_sft_trainer": ["IterativeSFTTrainer"],
"judges": [
"AllTrueJudge",
"BaseBinaryJudge",
"BaseJudge",
"BasePairwiseJudge",
"BaseRankJudge",
"HfPairwiseJudge",
"OpenAIPairwiseJudge",
"PairRMJudge",
],
"kto_config": ["KTOConfig"],
"kto_trainer": ["KTOTrainer"],
"model_config": ["ModelConfig"],
"nash_md_config": ["NashMDConfig"],
"nash_md_trainer": ["NashMDTrainer"],
"online_dpo_config": ["OnlineDPOConfig"],
"online_dpo_trainer": ["OnlineDPOTrainer"],
"orpo_config": ["ORPOConfig"],
"orpo_trainer": ["ORPOTrainer"],
"ppo_config": ["PPOConfig"],
"ppo_trainer": ["PPOTrainer"],
"prm_config": ["PRMConfig"],
"prm_trainer": ["PRMTrainer"],
"reward_config": ["RewardConfig"],
"reward_trainer": ["RewardTrainer"],
"rloo_config": ["RLOOConfig"],
"rloo_trainer": ["RLOOTrainer"],
"sft_config": ["SFTConfig"],
"sft_trainer": ["SFTTrainer"],
"utils": [
"ConstantLengthDataset",
"DataCollatorForCompletionOnlyLM",
"RunningMoments",
"compute_accuracy",
"disable_dropout_in_model",
"empty_cache",
"peft_module_casting_to_bf16",
],
"xpo_config": ["XPOConfig"],
"xpo_trainer": ["XPOTrainer"],
}
try:
if not is_diffusers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
_import_structure["ddpo_trainer"] = ["DDPOTrainer"]
if TYPE_CHECKING:
from .alignprop_config import AlignPropConfig
from .alignprop_trainer import AlignPropTrainer
from .bco_config import BCOConfig
from .bco_trainer import BCOTrainer
from .callbacks import (
LogCompletionsCallback,
MergeModelCallback,
RichProgressCallback,
SyncRefModelCallback,
WinRateCallback,
)
from .cpo_config import CPOConfig
from .cpo_trainer import CPOTrainer
from .ddpo_config import DDPOConfig
from .dpo_config import DPOConfig, FDivergenceConstants, FDivergenceType
from .dpo_trainer import DPOTrainer
from .gkd_config import GKDConfig
from .gkd_trainer import GKDTrainer
from .grpo_config import GRPOConfig
from .grpo_trainer import GRPOTrainer
from .iterative_sft_trainer import IterativeSFTConfig, IterativeSFTTrainer
from .judges import (
AllTrueJudge,
BaseBinaryJudge,
BaseJudge,
BasePairwiseJudge,
BaseRankJudge,
HfPairwiseJudge,
OpenAIPairwiseJudge,
PairRMJudge,
)
from .kto_config import KTOConfig
from .kto_trainer import KTOTrainer
from .model_config import ModelConfig
from .nash_md_config import NashMDConfig
from .nash_md_trainer import NashMDTrainer
from .online_dpo_config import OnlineDPOConfig
from .online_dpo_trainer import OnlineDPOTrainer
from .orpo_config import ORPOConfig
from .orpo_trainer import ORPOTrainer
from .ppo_config import PPOConfig
from .ppo_trainer import PPOTrainer
from .prm_config import PRMConfig
from .prm_trainer import PRMTrainer
from .reward_config import RewardConfig
from .reward_trainer import RewardTrainer
from .rloo_config import RLOOConfig
from .rloo_trainer import RLOOTrainer
from .sft_config import SFTConfig
from .sft_trainer import SFTTrainer
from .utils import (
ConstantLengthDataset,
DataCollatorForCompletionOnlyLM,
RunningMoments,
compute_accuracy,
disable_dropout_in_model,
empty_cache,
peft_module_casting_to_bf16,
)
from .xpo_config import XPOConfig
from .xpo_trainer import XPOTrainer
try:
if not is_diffusers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
from .ddpo_trainer import DDPOTrainer
else:
import sys
sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
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