stack is now partial execution safe

more_math/AudioMathNode.py

@@ -91,7 +91,7 @@ class AudioMathNode(io.ComfyNode):
         tensor_keys = [k for k, v in V.items() if v is not None and isinstance(v, dict) and "waveform" in v]
         if not tensor_keys:
              raise ValueError("At least one audio input is required.")
-
+        stack = stack.deepcopy() if stack is not None else {}
         waveforms = {k: V[k]["waveform"] for k in tensor_keys}
         sample_rates = {k + "sr": V[k].get("sample_rate", 44100) for k in tensor_keys}
 

more_math/ClipMathNode.py

@@ -75,6 +75,7 @@ class CLIPMathNode(io.ComfyNode):
     def execute(cls, V, F, Expression, length_mismatch="tile",stack={}) -> io.NodeOutput:
         # Determine reference CLIP
         a = V.get("V0")
+        stack = stack.deepcopy() if stack is not None else {}
         if a is None:
              for m in V.values():
                  if m is not None:

more_math/ConditioningMathNode.py

@@ -90,6 +90,7 @@ class ConditioningMathNode(io.ComfyNode):
         tensor_keys = [k for k, v in V.items() if v is not None and isinstance(v, list) and len(v) > 0]
         if not tensor_keys:
              raise ValueError("At least one input is required.")
+        stack = stack.deepcopy() if stack is not None else {}
 
         # Extract tensors and pooled outputs
         tensors = {}

more_math/FloatMathNode.py

@@ -84,6 +84,7 @@ class FloatMathNode(io.ComfyNode):
         variables["x"] = V.get("V5", 0.0)
         variables["y"] = V.get("V6", 0.0)
         variables["z"] = V.get("V7", 0.0)
+        stack = stack.deepcopy() if stack is not None else {}
 
         # Populate all V inputs
         for k, val in V.items():

more_math/GuiderMathNode.py

@@ -83,6 +83,7 @@ class GuiderMathNode(io.ComfyNode):
 
     @classmethod
     def execute(cls, V, F, Expression,Expression1,stack={}):
+        stack = stack.deepcopy() if stack is not None else {}
         return (MathGuider(V, F, Expression,Expression1),stack)
 
 

more_math/ImageMathNode.py

@@ -86,6 +86,7 @@ class ImageMathNode(io.ComfyNode):
              raise ValueError("At least one input is required.")
 
         tensors = [V[k] for k in tensor_keys]
+        stack = stack.deepcopy() if stack is not None else {}
 
         # Normalize all tensors together to find the common target shape
         normalized_tensors = normalize_to_common_shape(*tensors, mode=length_mismatch)

more_math/LatentMathNode.py

@@ -100,6 +100,7 @@ class LatentMathNode(io.ComfyNode):
 
         if ref_latent is None:
              raise ValueError("At least one input is required.")
+        stack = stack.deepcopy() if stack is not None else {}
 
         # Identify if any input is a NestedTensor and track original sizes for restoration
         stacked = False

more_math/MaskMathNode.py

@@ -85,7 +85,7 @@ class MaskMathNode(io.ComfyNode):
              raise ValueError("At least one input is required.")
 
         tensors = [V[k] for k in tensor_keys]
-
+        stack = stack.deepcopy() if stack is not None else {}
         # Normalize all tensors together
         normalized_tensors = normalize_to_common_shape(*tensors, mode=length_mismatch)
         V_norm = dict(zip(tensor_keys, normalized_tensors))

more_math/ModelMathNode.py

@@ -76,6 +76,8 @@ class ModelMathNode(io.ComfyNode):
     def execute(cls, V, F, Expression, length_mismatch="tile",stack={}) -> io.NodeOutput:
         # Determine reference model for cloning
         a = V.get("V0")
+        stack = stack.deepcopy() if stack is not None else {}
+
         if a is None:
             # Try finding first valid model
             for m in V.values():

more_math/NoiseMathNode.py

@@ -74,6 +74,7 @@ class NoiseMathNode(io.ComfyNode):
 
     @classmethod
     def execute(cls, Noise, V,F,stack={}):
+        stack = stack.deepcopy() if stack is not None else {}
         return (NoiseExecutor(V,F, Noise,stack),)
 
 

more_math/SigmasMathNode.py

@@ -87,7 +87,7 @@ class SigmasMathNode(io.ComfyNode):
 
         if ref_image is None:
              raise ValueError("At least one input is required.")
-
+        stack = stack.deepcopy() if stack is not None else {}
         a = V.get("V0")
         b = V.get("V1")
         c = V.get("V2")

more_math/VaeMathNode.py

@@ -83,6 +83,7 @@ class VAEMathNode(io.ComfyNode):
                       break
         if a is None:
              raise ValueError("At least one input VAE is required.")
+        stack = stack.deepcopy() if stack is not None else {}
 
 
         # Prepare VAE patchers for calculation

more_math/VideoMathNode.py

@@ -95,6 +95,7 @@ class VideoMathNode(io.ComfyNode):
         # Use first normalized tensor to establish the reference shape
         ref_tensor = normalized_tensors[0]
         common_shape = ref_tensor.shape
+        stack = stack.deepcopy() if stack is not None else {}
 
         # Setup legacy variables a, b, c, d
         ae = V_norm.get("V0", make_zero_like(ref_tensor))