wehub-resource-sync
90 lines
2.9 KiB
Python
90 lines
2.9 KiB
Python
# Copyright (c) 2018 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 random
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import unittest
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import paddle
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from paddle.vision.models._utils import IntermediateLayerGetter
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class TestBase:
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def setUp(self):
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self.init_model()
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self.model.eval()
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self.layer_names = [
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(order, name)
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for order, (name, _) in enumerate(self.model.named_children())
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]
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# choose two layer children of model randomly
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self.start, self.end = sorted(
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random.sample(self.layer_names, 2), key=lambda x: x[0]
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)
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self.return_layers_dic = {self.start[1]: "feat1", self.end[1]: "feat2"}
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self.new_model = IntermediateLayerGetter(
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self.model, self.return_layers_dic
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)
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def init_model(self):
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self.model = None
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@paddle.no_grad()
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def test_inter_result(self):
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inp = paddle.randn([1, 3, 80, 80])
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inter_oup = self.new_model(inp)
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for layer_name, layer in self.model.named_children():
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if (isinstance(layer, paddle.nn.Linear) and inp.ndim == 4) or (
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len(layer.sublayers()) > 0
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and isinstance(layer.sublayers()[0], paddle.nn.Linear)
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and inp.ndim == 4
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):
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inp = paddle.flatten(inp, 1)
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inp = layer(inp)
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if layer_name in self.return_layers_dic:
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feat_name = self.return_layers_dic[layer_name]
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self.assertTrue((inter_oup[feat_name] == inp).all())
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class TestIntermediateLayerGetterResNet18(TestBase, unittest.TestCase):
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def init_model(self):
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self.model = paddle.vision.models.resnet18(pretrained=False)
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class TestIntermediateLayerGetterDenseNet121(TestBase, unittest.TestCase):
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def init_model(self):
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self.model = paddle.vision.models.densenet121(pretrained=False)
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class TestIntermediateLayerGetterVGG11(TestBase, unittest.TestCase):
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def init_model(self):
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self.model = paddle.vision.models.vgg11(pretrained=False)
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class TestIntermediateLayerGetterMobileNetV3Small(TestBase, unittest.TestCase):
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def init_model(self):
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self.model = paddle.vision.models.MobileNetV3Small()
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class TestIntermediateLayerGetterShuffleNetV2(TestBase, unittest.TestCase):
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def init_model(self):
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self.model = paddle.vision.models.shufflenet_v2_x0_25()
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if __name__ == "__main__":
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unittest.main()
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