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67 lines
2.3 KiB
67 lines
2.3 KiB
3 years ago
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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3 years ago
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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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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from paddle.utils import try_import
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3 years ago
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from paddlers.models.ppdet.core.workspace import register, serializable
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from paddlers.models.ppdet.utils.logger import setup_logger
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3 years ago
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logger = setup_logger(__name__)
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@register
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@serializable
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class UnstructuredPruner(object):
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def __init__(self,
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stable_epochs,
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pruning_epochs,
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tunning_epochs,
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pruning_steps,
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ratio,
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initial_ratio,
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prune_params_type=None):
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self.stable_epochs = stable_epochs
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self.pruning_epochs = pruning_epochs
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self.tunning_epochs = tunning_epochs
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self.ratio = ratio
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self.prune_params_type = prune_params_type
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self.initial_ratio = initial_ratio
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self.pruning_steps = pruning_steps
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def __call__(self, model, steps_per_epoch, skip_params_func=None):
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paddleslim = try_import('paddleslim')
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from paddleslim import GMPUnstructuredPruner
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configs = {
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'pruning_strategy': 'gmp',
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'stable_iterations': self.stable_epochs * steps_per_epoch,
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'pruning_iterations': self.pruning_epochs * steps_per_epoch,
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'tunning_iterations': self.tunning_epochs * steps_per_epoch,
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'resume_iteration': 0,
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'pruning_steps': self.pruning_steps,
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'initial_ratio': self.initial_ratio,
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}
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pruner = GMPUnstructuredPruner(
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model,
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ratio=self.ratio,
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skip_params_func=skip_params_func,
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prune_params_type=self.prune_params_type,
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local_sparsity=True,
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configs=configs)
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return pruner
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