add new tests for F.adjust_saturation

test/test_transforms_v2_refactored.py

@@ -4494,3 +4494,45 @@ def test_correctness_image(self, hue_factor):
 
         mae = (actual.float() - expected.float()).abs().mean()
         assert mae < 2
+
+
+class TestAdjustSaturation:
+    @pytest.mark.parametrize("dtype", [torch.uint8, torch.float32])
+    @pytest.mark.parametrize("device", cpu_and_cuda())
+    def test_kernel_image(self, dtype, device):
+        check_kernel(F.adjust_saturation_image, make_image(dtype=dtype, device=device), saturation_factor=0.5)
+
+    def test_kernel_video(self):
+        check_kernel(F.adjust_saturation_video, make_video(), saturation_factor=0.5)
+
+    @pytest.mark.parametrize("make_input", [make_image_tensor, make_image, make_image_pil, make_video])
+    def test_functional(self, make_input):
+        check_functional(F.adjust_saturation, make_input(), saturation_factor=0.5)
+
+    @pytest.mark.parametrize(
+        ("kernel", "input_type"),
+        [
+            (F.adjust_saturation_image, torch.Tensor),
+            (F._adjust_saturation_image_pil, PIL.Image.Image),
+            (F.adjust_saturation_image, tv_tensors.Image),
+            (F.adjust_saturation_video, tv_tensors.Video),
+        ],
+    )
+    def test_functional_signature(self, kernel, input_type):
+        check_functional_kernel_signature_match(F.adjust_saturation, kernel=kernel, input_type=input_type)
+
+    def test_functional_error(self):
+        with pytest.raises(TypeError, match="permitted channel values are 1 or 3"):
+            F.adjust_saturation(make_image(color_space="RGBA"), saturation_factor=0.5)
+
+        with pytest.raises(ValueError, match="is not non-negative"):
+            F.adjust_saturation(make_image(), saturation_factor=-1)
+
+    @pytest.mark.parametrize("saturation_factor", [0.1, 0.5, 1.0])
+    def test_correctness_image(self, saturation_factor):
+        image = make_image(dtype=torch.uint8, device="cpu")
+
+        actual = F.adjust_saturation(image, saturation_factor=saturation_factor)
+        expected = F.to_image(F.adjust_saturation(F.to_pil_image(image), saturation_factor=saturation_factor))
+
+        assert_close(actual, expected, rtol=0, atol=1)