chore: import upstream snapshot with attribution
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# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import sys as _sys
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from paddle.optimizer import (
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ASGD as ASGD,
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LBFGS as LBFGS,
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SGD as SGD,
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Adadelta as Adadelta,
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Adagrad as Adagrad,
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Adam as Adam,
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Adamax as Adamax,
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AdamW as AdamW,
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Muon as Muon,
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NAdam as NAdam,
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Optimizer as Optimizer,
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RAdam as RAdam,
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RMSProp as RMSProp,
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Rprop as Rprop,
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adadelta,
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adagrad,
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adam,
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adamax,
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adamw,
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asgd,
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lbfgs,
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muon,
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nadam,
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optimizer,
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radam,
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rmsprop,
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rprop,
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sgd,
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)
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from . import lr_scheduler # noqa: F401
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_sys.modules['paddle.optim.adadelta'] = adadelta
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_sys.modules['paddle.optim.adagrad'] = adagrad
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_sys.modules['paddle.optim.adam'] = adam
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_sys.modules['paddle.optim.adamax'] = adamax
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_sys.modules['paddle.optim.adamw'] = adamw
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_sys.modules['paddle.optim.asgd'] = asgd
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_sys.modules['paddle.optim.lbfgs'] = lbfgs
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_sys.modules['paddle.optim.muon'] = muon
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_sys.modules['paddle.optim.nadam'] = nadam
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_sys.modules['paddle.optim.optimizer'] = optimizer
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_sys.modules['paddle.optim.radam'] = radam
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_sys.modules['paddle.optim.rmsprop'] = rmsprop
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_sys.modules['paddle.optim.rprop'] = rprop
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_sys.modules['paddle.optim.sgd'] = sgd
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__all__ = [
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"Adadelta",
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"Adagrad",
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"Adam",
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"Adamax",
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"AdamW",
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"ASGD",
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"LBFGS",
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"Muon",
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"NAdam",
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"Optimizer",
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"RAdam",
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"RMSProp",
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"Rprop",
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"SGD",
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]
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@@ -0,0 +1,45 @@
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# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import paddle.optimizer.lr
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LambdaLR = paddle.optimizer.lr.LambdaDecay
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MultiplicativeLR = paddle.optimizer.lr.MultiplicativeDecay
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StepLR = paddle.optimizer.lr.StepDecay
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MultiStepLR = paddle.optimizer.lr.MultiStepDecay
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ConstantLR = paddle.optimizer.lr.PiecewiseDecay
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LinearLR = paddle.optimizer.lr.LinearLR
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ExponentialLR = paddle.optimizer.lr.ExponentialDecay
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CosineAnnealingLR = paddle.optimizer.lr.CosineAnnealingDecay
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ReduceLROnPlateau = paddle.optimizer.lr.ReduceOnPlateau
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CyclicLR = paddle.optimizer.lr.CyclicLR
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CosineAnnealingWarmRestarts = paddle.optimizer.lr.CosineAnnealingWarmRestarts
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OneCycleLR = paddle.optimizer.lr.OneCycleLR
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LRScheduler = paddle.optimizer.lr.LRScheduler
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__all__ = [
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"LambdaLR",
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"MultiplicativeLR",
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"StepLR",
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"MultiStepLR",
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"ConstantLR",
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"LinearLR",
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"ExponentialLR",
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"CosineAnnealingLR",
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"ReduceLROnPlateau",
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"CyclicLR",
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"CosineAnnealingWarmRestarts",
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"OneCycleLR",
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"LRScheduler",
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]
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