test: Updated asserts in test_utils (#1499)

* test: Updated asserts in test_utils

Updated all raw asserts to corresponding unittest.TestCase.assert. See #1483

* style: Fixed lint check

Author: frgfm

test/test_utils.py

@@ -16,13 +16,13 @@ def test_make_grid_not_inplace(self):
         t_clone = t.clone()
 
         utils.make_grid(t, normalize=False)
-        assert torch.equal(t, t_clone), 'make_grid modified tensor in-place'
+        self.assertTrue(torch.equal(t, t_clone), 'make_grid modified tensor in-place')
 
         utils.make_grid(t, normalize=True, scale_each=False)
-        assert torch.equal(t, t_clone), 'make_grid modified tensor in-place'
+        self.assertTrue(torch.equal(t, t_clone), 'make_grid modified tensor in-place')
 
         utils.make_grid(t, normalize=True, scale_each=True)
-        assert torch.equal(t, t_clone), 'make_grid modified tensor in-place'
+        self.assertTrue(torch.equal(t, t_clone), 'make_grid modified tensor in-place')
 
     def test_normalize_in_make_grid(self):
         t = torch.rand(5, 3, 10, 10) * 255
@@ -38,22 +38,22 @@ def test_normalize_in_make_grid(self):
         rounded_grid_max = torch.round(grid_max * 10 ** n_digits) / (10 ** n_digits)
         rounded_grid_min = torch.round(grid_min * 10 ** n_digits) / (10 ** n_digits)
 
-        assert torch.equal(norm_max, rounded_grid_max), 'Normalized max is not equal to 1'
-        assert torch.equal(norm_min, rounded_grid_min), 'Normalized min is not equal to 0'
+        self.assertTrue(torch.equal(norm_max, rounded_grid_max), 'Normalized max is not equal to 1')
+        self.assertTrue(torch.equal(norm_min, rounded_grid_min), 'Normalized min is not equal to 0')
 
     @unittest.skipIf('win' in sys.platform, 'temporarily disabled on Windows')
     def test_save_image(self):
         with tempfile.NamedTemporaryFile(suffix='.png') as f:
             t = torch.rand(2, 3, 64, 64)
             utils.save_image(t, f.name)
-            assert os.path.exists(f.name), 'The image is not present after save'
+            self.assertTrue(os.path.exists(f.name), 'The image is not present after save')
 
     @unittest.skipIf('win' in sys.platform, 'temporarily disabled on Windows')
     def test_save_image_single_pixel(self):
         with tempfile.NamedTemporaryFile(suffix='.png') as f:
             t = torch.rand(1, 3, 1, 1)
             utils.save_image(t, f.name)
-            assert os.path.exists(f.name), 'The pixel image is not present after save'
+            self.assertTrue(os.path.exists(f.name), 'The pixel image is not present after save')
 
     @unittest.skipIf('win' in sys.platform, 'temporarily disabled on Windows')
     def test_save_image_file_object(self):
@@ -64,7 +64,8 @@ def test_save_image_file_object(self):
             fp = BytesIO()
             utils.save_image(t, fp, format='png')
             img_bytes = Image.open(fp)
-            assert torch.equal(F.to_tensor(img_orig), F.to_tensor(img_bytes)), 'Image not stored in file object'
+            self.assertTrue(torch.equal(F.to_tensor(img_orig), F.to_tensor(img_bytes)),
+                            'Image not stored in file object')
 
     @unittest.skipIf('win' in sys.platform, 'temporarily disabled on Windows')
     def test_save_image_single_pixel_file_object(self):
@@ -75,7 +76,8 @@ def test_save_image_single_pixel_file_object(self):
             fp = BytesIO()
             utils.save_image(t, fp, format='png')
             img_bytes = Image.open(fp)
-            assert torch.equal(F.to_tensor(img_orig), F.to_tensor(img_bytes)), 'Pixel Image not stored in file object'
+            self.assertTrue(torch.equal(F.to_tensor(img_orig), F.to_tensor(img_bytes)),
+                            'Pixel Image not stored in file object')
 
 
 if __name__ == '__main__':