Fix a bug where cached outputs affected IS_CHANGED

execution.py

@@ -47,7 +47,8 @@ def get(self, node_id):
  self.is_changed[node_id] = node["is_changed"]
  return self.is_changed[node_id]
 
- input_data_all, _ = get_input_data(node["inputs"], class_def, node_id, self.outputs_cache)
+ # Intentionally do not use cached outputs here. We only want constants in IS_CHANGED
+ input_data_all, _ = get_input_data(node["inputs"], class_def, node_id, None)
  try:
  is_changed = _map_node_over_list(class_def, input_data_all, "IS_CHANGED")
  node["is_changed"] = [None if isinstance(x, ExecutionBlocker) else x for x in is_changed]

tests/inference/test_execution.py

@@ -459,3 +459,22 @@ def test_output_reuse(self, client: ComfyClient, builder: GraphBuilder):
  assert len(images1) == 1, "Should have 1 image"
  assert len(images2) == 1, "Should have 1 image"
 
+
+ # This tests that only constant outputs are used in the call to `IS_CHANGED`
+ def test_is_changed_with_outputs(self, client: ComfyClient, builder: GraphBuilder):
+ g = builder
+ input1 = g.node("StubConstantImage", value=0.5, height=512, width=512, batch_size=1)
+ test_node = g.node("TestIsChangedWithConstants", image=input1.out(0), value=0.5)
+
+ output = g.node("PreviewImage", images=test_node.out(0))
+
+ result = client.run(g)
+ images = result.get_images(output)
+ assert len(images) == 1, "Should have 1 image"
+ assert numpy.array(images[0]).min() == 63 and numpy.array(images[0]).max() == 63, "Image should have value 0.25"
+
+ result = client.run(g)
+ images = result.get_images(output)
+ assert len(images) == 1, "Should have 1 image"
+ assert numpy.array(images[0]).min() == 63 and numpy.array(images[0]).max() == 63, "Image should have value 0.25"
+ assert not result.did_run(test_node), "The execution should have been cached"

tests/inference/testing_nodes/testing-pack/specific_tests.py

@@ -95,6 +95,31 @@ def IS_CHANGED(cls, should_change=False, *args, **kwargs):
  else:
  return False
 
+class TestIsChangedWithConstants:
+ @classmethod
+ def INPUT_TYPES(cls):
+ return {
+ "required": {
+ "image": ("IMAGE",),
+ "value": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0}),
+ },
+ }
+
+ RETURN_TYPES = ("IMAGE",)
+ FUNCTION = "custom_is_changed"
+
+ CATEGORY = "Testing/Nodes"
+
+ def custom_is_changed(self, image, value):
+ return (image * value,)
+
+ @classmethod
+ def IS_CHANGED(cls, image, value):
+ if image is None:
+ return value
+ else:
+ return image.mean().item() * value
+
 class TestCustomValidation1:
  @classmethod
  def INPUT_TYPES(cls):
@@ -312,6 +337,7 @@ def mixed_expansion_returns(self, input1):
  "TestLazyMixImages": TestLazyMixImages,
  "TestVariadicAverage": TestVariadicAverage,
  "TestCustomIsChanged": TestCustomIsChanged,
+ "TestIsChangedWithConstants": TestIsChangedWithConstants,
  "TestCustomValidation1": TestCustomValidation1,
  "TestCustomValidation2": TestCustomValidation2,
  "TestCustomValidation3": TestCustomValidation3,
@@ -325,6 +351,7 @@ def mixed_expansion_returns(self, input1):
  "TestLazyMixImages": "Lazy Mix Images",
  "TestVariadicAverage": "Variadic Average",
  "TestCustomIsChanged": "Custom IsChanged",
+ "TestIsChangedWithConstants": "IsChanged With Constants",
  "TestCustomValidation1": "Custom Validation 1",
  "TestCustomValidation2": "Custom Validation 2",
  "TestCustomValidation3": "Custom Validation 3",

tests/inference/testing_nodes/testing-pack/stubs.py

@@ -28,6 +28,28 @@ def stub_image(self, content, height, width, batch_size):
  elif content == "NOISE":
  return (torch.rand(batch_size, height, width, 3),)
 
+class StubConstantImage:
+ def __init__(self):
+ pass
+ @classmethod
+ def INPUT_TYPES(cls):
+ return {
+ "required": {
+ "value": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
+ "height": ("INT", {"default": 512, "min": 1, "max": 1024 ** 3, "step": 1}),
+ "width": ("INT", {"default": 512, "min": 1, "max": 4096 ** 3, "step": 1}),
+ "batch_size": ("INT", {"default": 1, "min": 1, "max": 1024 ** 3, "step": 1}),
+ },
+ }
+
+ RETURN_TYPES = ("IMAGE",)
+ FUNCTION = "stub_constant_image"
+
+ CATEGORY = "Testing/Stub Nodes"
+
+ def stub_constant_image(self, value, height, width, batch_size):
+ return (torch.ones(batch_size, height, width, 3) * value,)
+
 class StubMask:
  def __init__(self):
  pass
@@ -93,12 +115,14 @@ def stub_float(self, value):
 
 TEST_STUB_NODE_CLASS_MAPPINGS = {
  "StubImage": StubImage,
+ "StubConstantImage": StubConstantImage,
  "StubMask": StubMask,
  "StubInt": StubInt,
  "StubFloat": StubFloat,
 }
 TEST_STUB_NODE_DISPLAY_NAME_MAPPINGS = {
  "StubImage": "Stub Image",
+ "StubConstantImage": "Stub Constant Image",
  "StubMask": "Stub Mask",
  "StubInt": "Stub Int",
  "StubFloat": "Stub Float",