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test: Updated asserts in test_transforms_video #1498

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Oct 18, 2019
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test: Updated asserts in test_transforms_video #1498

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16 changes: 8 additions & 8 deletions test/test_transforms_video.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,8 +25,8 @@ def test_random_crop_video(self):
transforms.ToTensorVideo(),
transforms.RandomCropVideo((oheight, owidth)),
])(clip)
assert result.size(2) == oheight
assert result.size(3) == owidth
self.assertEqual(result.size(2), oheight)
self.assertEqual(result.size(3), owidth)

transforms.RandomCropVideo((oheight, owidth)).__repr__()

Expand All @@ -41,8 +41,8 @@ def test_random_resized_crop_video(self):
transforms.ToTensorVideo(),
transforms.RandomResizedCropVideo((oheight, owidth)),
])(clip)
assert result.size(2) == oheight
assert result.size(3) == owidth
self.assertEqual(result.size(2), oheight)
self.assertEqual(result.size(3), owidth)

transforms.RandomResizedCropVideo((oheight, owidth)).__repr__()

Expand Down Expand Up @@ -110,13 +110,13 @@ def samples_from_standard_normal(tensor):
mean = [clip[c].mean().item() for c in range(channels)]
std = [clip[c].std().item() for c in range(channels)]
normalized = transforms.NormalizeVideo(mean, std)(clip)
assert samples_from_standard_normal(normalized)
self.assertTrue(samples_from_standard_normal(normalized))
random.setstate(random_state)

# Checking the optional in-place behaviour
tensor = torch.rand((3, 128, 16, 16))
tensor_inplace = transforms.NormalizeVideo((0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True)(tensor)
assert torch.equal(tensor, tensor_inplace)
self.assertTrue(torch.equal(tensor, tensor_inplace))

transforms.NormalizeVideo((0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True).__repr__()

Expand Down Expand Up @@ -152,7 +152,7 @@ def test_random_horizontal_flip_video(self):

p_value = stats.binom_test(num_horizontal, num_samples, p=0.5)
random.setstate(random_state)
assert p_value > 0.0001
self.assertGreater(p_value, 0.0001)

num_samples = 250
num_horizontal = 0
Expand All @@ -163,7 +163,7 @@ def test_random_horizontal_flip_video(self):

p_value = stats.binom_test(num_horizontal, num_samples, p=0.7)
random.setstate(random_state)
assert p_value > 0.0001
self.assertGreater(p_value, 0.0001)

transforms.RandomHorizontalFlipVideo().__repr__()

Expand Down