added tests for transforms.Normalize

test/test_transforms.py

@@ -430,6 +430,22 @@ class Tester(unittest.TestCase):
         random.setstate(random_state)
         assert p_value > 0.0001
 
+    @unittest.skipIf(stats is None, 'scipt.stats is not available')
+    def test_normalize(self):
+        def samples_from_standard_normal(tensor):
+            p_value = stats.kstest(list(tensor.view(-1)), 'norm', args=(0, 1)).pvalue
+            return p_value > 0.0001
+
+        random_state = random.getstate()
+        random.seed(42)
+        for channels in [1, 3]:
+            img = torch.rand(channels, 10, 10)
+            mean = [img[c].mean() for c in range(channels)]
+            std = [img[c].std() for c in range(channels)]
+            normalized = transforms.Normalize(mean, std)(img)
+            assert samples_from_standard_normal(normalized)
+        random.setstate(random_state)
+
     def test_adjust_brightness(self):
         x_shape = [2, 2, 3]
         x_data = [0, 5, 13, 54, 135, 226, 37, 8, 234, 90, 255, 1]