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67 lines
2.2 KiB
67 lines
2.2 KiB
# copyright (c) 2019 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
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import unittest
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import paddle.fluid as fluid
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from mobilenet import MobileNet
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from paddle.fluid.contrib.slim.core import Compressor
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from paddle.fluid.contrib.slim.graph import GraphWrapper
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import sys
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sys.path.append("./light_nas")
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from light_nas_space import LightNASSpace
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class TestLightNAS(unittest.TestCase):
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def test_compression(self):
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if not fluid.core.is_compiled_with_cuda():
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return
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class_dim = 10
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image_shape = [1, 28, 28]
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space = LightNASSpace()
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startup_prog, train_prog, test_prog, train_metrics, test_metrics, train_reader, test_reader = space.create_net(
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)
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train_cost, train_acc1, train_acc5, global_lr = train_metrics
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test_cost, test_acc1, test_acc5 = test_metrics
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place = fluid.CUDAPlace(0)
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exe = fluid.Executor(place)
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exe.run(startup_prog)
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val_fetch_list = [('acc_top1', test_acc1.name), ('acc_top5',
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test_acc5.name)]
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train_fetch_list = [('loss', train_cost.name)]
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com_pass = Compressor(
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place,
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fluid.global_scope(),
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train_prog,
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train_reader=train_reader,
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train_feed_list=None,
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train_fetch_list=train_fetch_list,
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eval_program=test_prog,
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eval_reader=test_reader,
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eval_feed_list=None,
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eval_fetch_list=val_fetch_list,
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train_optimizer=None,
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search_space=space)
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com_pass.config('./light_nas/compress.yaml')
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eval_graph = com_pass.run()
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if __name__ == '__main__':
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unittest.main()
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