meta_optimizer_factory.py 1.5 KB
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#   Copyright (c) 2020 PaddlePaddle Authors. 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.

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from ..meta_optimizers import AMPOptimizer
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from ..meta_optimizers import RecomputeOptimizer
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from ..meta_optimizers import GradientMergeOptimizer
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from ..meta_optimizers import GraphExecutionOptimizer
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from ..meta_optimizers import PipelineOptimizer
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from ..meta_optimizers import LocalSGDOptimizer
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from ..meta_optimizers import LarsOptimizer
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__all__ = ["MetaOptimizerFactory"]
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meta_optimizer_names = [
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    "AMPOptimizer",
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    "RecomputeOptimizer",
    "GradientMergeOptimizer",
    "GraphExecutionOptimizer",
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    "PipelineOptimizer",
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    "LocalSGDOptimizer",
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    "LarsOptimizer",
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]
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class MetaOptimizerFactory(object):
    def __init__(self):
        pass

    def _get_valid_meta_optimizers(self, user_defined_optimizer):
        opt_list = []
        for opt_name in meta_optimizer_names:
            opt_list.append(globals()[opt_name](user_defined_optimizer))
        return opt_list