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reduce unittest time of test_datasets (#30275)

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revert-31562-mean
LielinJiang 4 years ago committed by GitHub
parent a0ee09148e
commit 86d81af5ef
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1 changed files with 28 additions and 28 deletions
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python/paddle/tests/test_datasets.py
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@ -94,13 +94,13 @@ class TestMNISTTest(unittest.TestCase):
mnist = MNIST(mode='test', transform=transform)
self.assertTrue(len(mnist) == 10000)
for i in range(len(mnist)):
image, label = mnist[i]
self.assertTrue(image.shape[0] == 1)
self.assertTrue(image.shape[1] == 28)
self.assertTrue(image.shape[2] == 28)
self.assertTrue(label.shape[0] == 1)
self.assertTrue(0 <= int(label) <= 9)
i = np.random.randint(0, len(mnist) - 1)
image, label = mnist[i]
self.assertTrue(image.shape[0] == 1)
self.assertTrue(image.shape[1] == 28)
self.assertTrue(image.shape[2] == 28)
self.assertTrue(label.shape[0] == 1)
self.assertTrue(0 <= int(label) <= 9)
class TestMNISTTrain(unittest.TestCase):
@ -109,13 +109,13 @@ class TestMNISTTrain(unittest.TestCase):
mnist = MNIST(mode='train', transform=transform)
self.assertTrue(len(mnist) == 60000)
for i in range(len(mnist)):
image, label = mnist[i]
self.assertTrue(image.shape[0] == 1)
self.assertTrue(image.shape[1] == 28)
self.assertTrue(image.shape[2] == 28)
self.assertTrue(label.shape[0] == 1)
self.assertTrue(0 <= int(label) <= 9)
i = np.random.randint(0, len(mnist) - 1)
image, label = mnist[i]
self.assertTrue(image.shape[0] == 1)
self.assertTrue(image.shape[1] == 28)
self.assertTrue(image.shape[2] == 28)
self.assertTrue(label.shape[0] == 1)
self.assertTrue(0 <= int(label) <= 9)
# test cv2 backend
mnist = MNIST(mode='train', transform=transform, backend='cv2')
@ -140,13 +140,13 @@ class TestFASHIONMNISTTest(unittest.TestCase):
mnist = FashionMNIST(mode='test', transform=transform)
self.assertTrue(len(mnist) == 10000)
for i in range(len(mnist)):
image, label = mnist[i]
self.assertTrue(image.shape[0] == 1)
self.assertTrue(image.shape[1] == 28)
self.assertTrue(image.shape[2] == 28)
self.assertTrue(label.shape[0] == 1)
self.assertTrue(0 <= int(label) <= 9)
i = np.random.randint(0, len(mnist) - 1)
image, label = mnist[i]
self.assertTrue(image.shape[0] == 1)
self.assertTrue(image.shape[1] == 28)
self.assertTrue(image.shape[2] == 28)
self.assertTrue(label.shape[0] == 1)
self.assertTrue(0 <= int(label) <= 9)
class TestFASHIONMNISTTrain(unittest.TestCase):
@ -155,13 +155,13 @@ class TestFASHIONMNISTTrain(unittest.TestCase):
mnist = FashionMNIST(mode='train', transform=transform)
self.assertTrue(len(mnist) == 60000)
for i in range(len(mnist)):
image, label = mnist[i]
self.assertTrue(image.shape[0] == 1)
self.assertTrue(image.shape[1] == 28)
self.assertTrue(image.shape[2] == 28)
self.assertTrue(label.shape[0] == 1)
self.assertTrue(0 <= int(label) <= 9)
i = np.random.randint(0, len(mnist) - 1)
image, label = mnist[i]
self.assertTrue(image.shape[0] == 1)
self.assertTrue(image.shape[1] == 28)
self.assertTrue(image.shape[2] == 28)
self.assertTrue(label.shape[0] == 1)
self.assertTrue(0 <= int(label) <= 9)
# test cv2 backend
mnist = FashionMNIST(mode='train', transform=transform, backend='cv2')

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