wehub-resource-sync
135 lines
4.2 KiB
Python
135 lines
4.2 KiB
Python
# Copyright (c) 2026 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.
|
|
|
|
"""
|
|
图像模型组件测试 / Image Model Component Tests
|
|
|
|
测试目标 / Test Target:
|
|
paddle.vision.models 预训练模型组件
|
|
|
|
覆盖的模块 / Covered Modules:
|
|
- paddle.vision.models.resnet: ResNet架构
|
|
- paddle.vision.models.mobilenetv1/v2: MobileNet
|
|
- paddle.vision.models.vgg: VGG架构
|
|
- paddle.vision.models.alexnet: AlexNet
|
|
|
|
作用 / Purpose:
|
|
补充视觉模型API的测试，提升覆盖率。
|
|
"""
|
|
|
|
import unittest
|
|
|
|
import paddle
|
|
from paddle.vision import models
|
|
|
|
paddle.disable_static()
|
|
|
|
|
|
class TestResNet(unittest.TestCase):
|
|
"""测试ResNet模型 / Test ResNet models"""
|
|
|
|
def test_resnet18_inference(self):
|
|
"""测试ResNet18推理 / Test ResNet18 inference"""
|
|
model = models.resnet18(pretrained=False)
|
|
model.eval()
|
|
x = paddle.randn([2, 3, 224, 224])
|
|
with paddle.no_grad():
|
|
output = model(x)
|
|
self.assertEqual(output.shape, [2, 1000])
|
|
|
|
def test_resnet50_structure(self):
|
|
"""测试ResNet50结构 / Test ResNet50 structure"""
|
|
model = models.resnet50(pretrained=False)
|
|
self.assertIsNotNone(model.fc)
|
|
# Test with small batch
|
|
model.eval()
|
|
x = paddle.randn([1, 3, 224, 224])
|
|
with paddle.no_grad():
|
|
output = model(x)
|
|
self.assertEqual(output.shape[1], 1000)
|
|
|
|
def test_resnet_custom_classes(self):
|
|
"""测试自定义分类数ResNet / Test ResNet with custom num_classes"""
|
|
model = models.resnet18(pretrained=False, num_classes=10)
|
|
model.eval()
|
|
x = paddle.randn([2, 3, 224, 224])
|
|
with paddle.no_grad():
|
|
output = model(x)
|
|
self.assertEqual(output.shape, [2, 10])
|
|
|
|
|
|
class TestMobileNet(unittest.TestCase):
|
|
"""测试MobileNet / Test MobileNet"""
|
|
|
|
def test_mobilenetv1(self):
|
|
"""测试MobileNetV1推理 / Test MobileNetV1 inference"""
|
|
model = models.mobilenet_v1(pretrained=False)
|
|
model.eval()
|
|
x = paddle.randn([2, 3, 224, 224])
|
|
with paddle.no_grad():
|
|
output = model(x)
|
|
self.assertEqual(output.shape, [2, 1000])
|
|
|
|
def test_mobilenetv2(self):
|
|
"""测试MobileNetV2推理 / Test MobileNetV2 inference"""
|
|
model = models.mobilenet_v2(pretrained=False)
|
|
model.eval()
|
|
x = paddle.randn([2, 3, 224, 224])
|
|
with paddle.no_grad():
|
|
output = model(x)
|
|
self.assertEqual(output.shape, [2, 1000])
|
|
|
|
|
|
class TestVGG(unittest.TestCase):
|
|
"""测试VGG / Test VGG"""
|
|
|
|
def test_vgg16(self):
|
|
"""测试VGG16推理 / Test VGG16 inference"""
|
|
model = models.vgg16(pretrained=False)
|
|
model.eval()
|
|
x = paddle.randn([1, 3, 224, 224])
|
|
with paddle.no_grad():
|
|
output = model(x)
|
|
self.assertEqual(output.shape, [1, 1000])
|
|
|
|
|
|
class TestAlexNet(unittest.TestCase):
|
|
"""测试AlexNet / Test AlexNet"""
|
|
|
|
def test_alexnet(self):
|
|
"""测试AlexNet推理 / Test AlexNet inference"""
|
|
model = models.alexnet(pretrained=False)
|
|
model.eval()
|
|
x = paddle.randn([1, 3, 224, 224])
|
|
with paddle.no_grad():
|
|
output = model(x)
|
|
self.assertEqual(output.shape, [1, 1000])
|
|
|
|
|
|
class TestSqueezeNet(unittest.TestCase):
|
|
"""测试SqueezeNet / Test SqueezeNet"""
|
|
|
|
def test_squeezenet1_0(self):
|
|
"""测试SqueezeNet1.0 / Test SqueezeNet1.0"""
|
|
model = models.squeezenet1_0(pretrained=False)
|
|
model.eval()
|
|
x = paddle.randn([1, 3, 224, 224])
|
|
with paddle.no_grad():
|
|
output = model(x)
|
|
self.assertEqual(output.shape, [1, 1000])
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|