def test_center_crop(self):
img_tensor = torch.randint(0, 255, (1, 32, 32), dtype=torch.uint8)
cropped_tensor = F_t.center_crop(img_tensor, [10, 10])
cropped_pil_image = F.center_crop(transforms.ToPILImage()(img_tensor),
[10, 10])
cropped_pil_tensor = (transforms.ToTensor()(cropped_pil_image) *
255).to(torch.uint8)
self.assertTrue(torch.equal(cropped_tensor, cropped_pil_tensor))
def test_center_crop(self):
script_center_crop = torch.jit.script(F_t.center_crop)
img_tensor = torch.randint(0, 255, (1, 32, 32), dtype=torch.uint8)
img_tensor_clone = img_tensor.clone()
cropped_tensor = F_t.center_crop(img_tensor, [10, 10])
cropped_pil_image = F.center_crop(transforms.ToPILImage()(img_tensor), [10, 10])
cropped_pil_tensor = (transforms.ToTensor()(cropped_pil_image) * 255).to(torch.uint8)
self.assertTrue(torch.equal(cropped_tensor, cropped_pil_tensor))
self.assertTrue(torch.equal(img_tensor, img_tensor_clone))
# scriptable function test
cropped_script = script_center_crop(img_tensor, [10, 10])
self.assertTrue(torch.equal(cropped_script, cropped_tensor))
