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def test_smoke(self):
height, width, channels = 4, 5, 3
img = np.ones((height, width, channels))
transforms = nn.Sequential(
taug.ToTensor(),
taug.Grayscale(),
)
assert transforms(img).shape == (1, height, width)
def test_rgb_to_tensor(self):
height, width, channels = 4, 5, 3
img = np.ones((height, width, channels))
assert taug.ToTensor()(img).shape == (channels, height, width)
def test_rgb_to_grayscale_batch(self):
batch_size, channels, height, width = 2, 3, 4, 5
img = torch.ones(batch_size, channels, height, width)
assert taug.Grayscale()(img).shape == (batch_size, 1, height, width)
def test_smoke(self):
height, width, channels = 4, 5, 3
img = np.ones((height, width, channels))
transforms = nn.Sequential(
taug.ToTensor(),
taug.Grayscale(),
)
assert transforms(img).shape == (1, height, width)