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- """
- Copyright 2020 Tianshu AI Platform. 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 copy import deepcopy
- import os
- import torch
-
- class Pruner(object):
- def __init__(self, strategy):
- self.strategy = strategy
-
- def prune(self, model, rate=0.1, example_inputs=None):
- ori_num_params = sum( [ torch.numel(p) for p in model.parameters() ] )
- model = deepcopy(model).cpu()
- model = self._prune( model, rate=rate, example_inputs=example_inputs )
- new_num_params = sum( [ torch.numel(p) for p in model.parameters() ] )
- print( "%d=>%d, %.2f%% params were pruned"%( ori_num_params, new_num_params, 100*(ori_num_params-new_num_params)/ori_num_params ) )
- return model
-
- def _prune(self, model, **kargs):
- return self.strategy( model, **kargs)
-
-
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