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