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246 lines
7.9 KiB
246 lines
7.9 KiB
# Copyright (c) 2020 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 unittest
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import os
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import numpy as np
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import tempfile
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import shutil
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import cv2
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import paddle.vision.transforms as T
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from paddle.vision.datasets import *
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from paddle.dataset.common import _check_exists_and_download
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class TestFolderDatasets(unittest.TestCase):
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def setUp(self):
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self.data_dir = tempfile.mkdtemp()
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self.empty_dir = tempfile.mkdtemp()
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for i in range(2):
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sub_dir = os.path.join(self.data_dir, 'class_' + str(i))
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if not os.path.exists(sub_dir):
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os.makedirs(sub_dir)
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for j in range(2):
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fake_img = (np.random.random((32, 32, 3)) * 255).astype('uint8')
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cv2.imwrite(os.path.join(sub_dir, str(j) + '.jpg'), fake_img)
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def tearDown(self):
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shutil.rmtree(self.data_dir)
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def test_dataset(self):
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dataset_folder = DatasetFolder(self.data_dir)
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for _ in dataset_folder:
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pass
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assert len(dataset_folder) == 4
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assert len(dataset_folder.classes) == 2
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dataset_folder = DatasetFolder(self.data_dir)
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for _ in dataset_folder:
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pass
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def test_folder(self):
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loader = ImageFolder(self.data_dir)
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for _ in loader:
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pass
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loader = ImageFolder(self.data_dir)
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for _ in loader:
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pass
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assert len(loader) == 4
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def test_transform(self):
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def fake_transform(img):
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return img
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transfrom = fake_transform
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dataset_folder = DatasetFolder(self.data_dir, transform=transfrom)
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for _ in dataset_folder:
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pass
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loader = ImageFolder(self.data_dir, transform=transfrom)
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for _ in loader:
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pass
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def test_errors(self):
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with self.assertRaises(RuntimeError):
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ImageFolder(self.empty_dir)
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with self.assertRaises(RuntimeError):
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DatasetFolder(self.empty_dir)
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with self.assertRaises(ValueError):
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_check_exists_and_download('temp_paddle', None, None, None, False)
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class TestMNISTTest(unittest.TestCase):
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def test_main(self):
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transform = T.Transpose()
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mnist = MNIST(mode='test', transform=transform)
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self.assertTrue(len(mnist) == 10000)
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for i in range(len(mnist)):
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image, label = mnist[i]
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self.assertTrue(image.shape[0] == 1)
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self.assertTrue(image.shape[1] == 28)
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self.assertTrue(image.shape[2] == 28)
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self.assertTrue(label.shape[0] == 1)
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self.assertTrue(0 <= int(label) <= 9)
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class TestMNISTTrain(unittest.TestCase):
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def test_main(self):
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transform = T.Transpose()
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mnist = MNIST(mode='train', transform=transform)
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self.assertTrue(len(mnist) == 60000)
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for i in range(len(mnist)):
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image, label = mnist[i]
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self.assertTrue(image.shape[0] == 1)
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self.assertTrue(image.shape[1] == 28)
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self.assertTrue(image.shape[2] == 28)
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self.assertTrue(label.shape[0] == 1)
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self.assertTrue(0 <= int(label) <= 9)
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# test cv2 backend
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mnist = MNIST(mode='train', transform=transform, backend='cv2')
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self.assertTrue(len(mnist) == 60000)
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for i in range(len(mnist)):
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image, label = mnist[i]
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self.assertTrue(image.shape[0] == 1)
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self.assertTrue(image.shape[1] == 28)
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self.assertTrue(image.shape[2] == 28)
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self.assertTrue(label.shape[0] == 1)
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self.assertTrue(0 <= int(label) <= 9)
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break
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with self.assertRaises(ValueError):
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mnist = MNIST(mode='train', transform=transform, backend=1)
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class TestFASHIONMNISTTest(unittest.TestCase):
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def test_main(self):
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transform = T.Transpose()
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mnist = FashionMNIST(mode='test', transform=transform)
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self.assertTrue(len(mnist) == 10000)
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for i in range(len(mnist)):
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image, label = mnist[i]
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self.assertTrue(image.shape[0] == 1)
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self.assertTrue(image.shape[1] == 28)
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self.assertTrue(image.shape[2] == 28)
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self.assertTrue(label.shape[0] == 1)
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self.assertTrue(0 <= int(label) <= 9)
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class TestFASHIONMNISTTrain(unittest.TestCase):
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def test_main(self):
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transform = T.Transpose()
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mnist = FashionMNIST(mode='train', transform=transform)
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self.assertTrue(len(mnist) == 60000)
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for i in range(len(mnist)):
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image, label = mnist[i]
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self.assertTrue(image.shape[0] == 1)
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self.assertTrue(image.shape[1] == 28)
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self.assertTrue(image.shape[2] == 28)
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self.assertTrue(label.shape[0] == 1)
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self.assertTrue(0 <= int(label) <= 9)
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# test cv2 backend
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mnist = FashionMNIST(mode='train', transform=transform, backend='cv2')
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self.assertTrue(len(mnist) == 60000)
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for i in range(len(mnist)):
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image, label = mnist[i]
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self.assertTrue(image.shape[0] == 1)
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self.assertTrue(image.shape[1] == 28)
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self.assertTrue(image.shape[2] == 28)
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self.assertTrue(label.shape[0] == 1)
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self.assertTrue(0 <= int(label) <= 9)
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break
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with self.assertRaises(ValueError):
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mnist = FashionMNIST(mode='train', transform=transform, backend=1)
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class TestFlowersTrain(unittest.TestCase):
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def test_main(self):
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flowers = Flowers(mode='train')
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self.assertTrue(len(flowers) == 6149)
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# traversal whole dataset may cost a
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# long time, randomly check 1 sample
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idx = np.random.randint(0, 6149)
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image, label = flowers[idx]
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image = np.array(image)
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self.assertTrue(len(image.shape) == 3)
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self.assertTrue(image.shape[2] == 3)
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self.assertTrue(label.shape[0] == 1)
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class TestFlowersValid(unittest.TestCase):
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def test_main(self):
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flowers = Flowers(mode='valid')
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self.assertTrue(len(flowers) == 1020)
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# traversal whole dataset may cost a
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# long time, randomly check 1 sample
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idx = np.random.randint(0, 1020)
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image, label = flowers[idx]
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image = np.array(image)
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self.assertTrue(len(image.shape) == 3)
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self.assertTrue(image.shape[2] == 3)
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self.assertTrue(label.shape[0] == 1)
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class TestFlowersTest(unittest.TestCase):
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def test_main(self):
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flowers = Flowers(mode='test')
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self.assertTrue(len(flowers) == 1020)
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# traversal whole dataset may cost a
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# long time, randomly check 1 sample
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idx = np.random.randint(0, 1020)
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image, label = flowers[idx]
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image = np.array(image)
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self.assertTrue(len(image.shape) == 3)
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self.assertTrue(image.shape[2] == 3)
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self.assertTrue(label.shape[0] == 1)
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# test cv2 backend
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flowers = Flowers(mode='test', backend='cv2')
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self.assertTrue(len(flowers) == 1020)
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# traversal whole dataset may cost a
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# long time, randomly check 1 sample
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idx = np.random.randint(0, 1020)
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image, label = flowers[idx]
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self.assertTrue(len(image.shape) == 3)
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self.assertTrue(image.shape[2] == 3)
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self.assertTrue(label.shape[0] == 1)
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with self.assertRaises(ValueError):
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flowers = Flowers(mode='test', backend=1)
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if __name__ == '__main__':
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unittest.main()
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