Don't add noise to the alpha channel in the Add Noise to Image node

ImageAddNoise added gaussian noise across every channel, so RGBA input came
back with random transparency speckle. Noise belongs on the colour channels;
leave alpha alone.

CORE-392

comfy_extras/nodes_images.py

@@ -189,6 +189,8 @@ class ImageAddNoise(IO.ComfyNode):
     def execute(cls, image, seed, strength) -> IO.NodeOutput:
         generator = torch.manual_seed(seed)
         s = torch.clip((image + strength * torch.randn(image.size(), generator=generator, device="cpu").to(image)), min=0.0, max=1.0)
+        if image.shape[-1] == 4:  # alpha stores transparency, not color
+            s[..., 3] = image[..., 3]
         return IO.NodeOutput(s)
 
     repeat = execute  # TODO: remove

tests-unit/comfy_extras_test/image_add_noise_alpha_test.py

@@ -0,0 +1,63 @@
+import torch
+
+from comfy.cli_args import args as cli_args
+
+if not torch.cuda.is_available():
+    cli_args.cpu = True
+
+from comfy_extras.nodes_images import ImageAddNoise  # noqa: E402
+
+
+def image(channels, value=0.5, alpha=0.5, size=8):
+    t = torch.full((1, size, size, channels), value)
+    if channels == 4:
+        t[..., 3] = alpha
+    return t
+
+
+def test_rgb_gets_noise_on_every_channel():
+    src = image(3)
+
+    s = ImageAddNoise.execute(src, 0, 0.5).result[0]
+
+    assert s.shape == src.shape
+    assert not torch.equal(s, src)
+
+
+def test_rgba_keeps_alpha_untouched():
+    src = image(4)
+
+    s = ImageAddNoise.execute(src, 0, 0.5).result[0]
+
+    assert s.shape[-1] == 4
+    assert torch.equal(s[..., 3], src[..., 3])
+    assert not torch.equal(s[..., :3], src[..., :3])
+
+
+def test_fully_transparent_pixels_stay_transparent():
+    src = image(4, alpha=0.0)
+
+    s = ImageAddNoise.execute(src, 0, 1.0).result[0]
+
+    assert torch.all(s[..., 3] == 0.0)
+
+
+def test_only_the_alpha_channel_is_guarded():
+    """Colour channels must still get exactly the unguarded noise result."""
+    src = image(4)
+    generator = torch.manual_seed(0)
+    unguarded = torch.clip(src + 0.5 * torch.randn(src.size(), generator=generator), min=0.0, max=1.0)
+
+    s = ImageAddNoise.execute(src, 0, 0.5).result[0]
+
+    assert torch.equal(s[..., :3], unguarded[..., :3])
+    assert torch.equal(s[..., 3], src[..., 3])
+
+
+def test_does_not_mutate_input():
+    src = image(4)
+    before = src.clone()
+
+    ImageAddNoise.execute(src, 0, 0.5)
+
+    assert torch.equal(src, before)