attempt to fix lazy inputs

Author: mcDandy

more_math/AudioMathNode.py

@@ -48,7 +48,7 @@ def define_schema(cls) -> io.Schema:
         )
     @classmethod
     def check_lazy_status(cls, AudioExpr, a, b=[], c=[], d=[],w=0,x=0,y=0,z=0):
-        return comonLazy(AudioExpr, a, b, c, d)
+        return comonLazy(AudioExpr, a, b, c, d,w,x,y,z)
     @classmethod
     def execute(cls, a, AudioExpr, b=None, c=None, d=None, w=0.0, x=0.0, y=0.0, z=0.0):
 

more_math/ClipMathNode.py

@@ -32,7 +32,7 @@ def define_schema(cls) -> io.Schema:
     tooltip = cleandoc(__doc__)
     @classmethod
     def check_lazy_status(cls, Model, a, b=[], c=[], d=[],w=0,x=0,y=0,z=0):
-        return comonLazy(Model, a, b, c, d)
+        return comonLazy(Model, a, b, c, d,w,x,y,z)
 
     @classmethod
     def execute(cls, Model, a, b=None, c=None, d=None, w=0.0, x=0.0, y=0.0, z=0.0) -> io.NodeOutput:

more_math/FloatMathNode.py

@@ -26,9 +26,9 @@ class FloatMathNode(io.ComfyNode):
     """
     def __init__(self):
         pass
-        @classmethod
+    @classmethod
     def check_lazy_status(cls, Model, a, b=[], c=[], d=[],w=0,x=0,y=0,z=0):
-        return comonLazy(Model, a, b, c, d)
+        return comonLazy(Model, a, b, c, d,w,x,y,z)
     @classmethod
     def define_schema(cls) -> io.Schema:
         """

more_math/ImageMathNode.py

@@ -53,7 +53,7 @@ def define_schema(cls) -> io.Schema:
         )
     @classmethod
     def check_lazy_status(cls, Image, a, b=[], c=[], d=[],w=0,x=0,y=0,z=0):
-        return comonLazy(Image, a, b, c, d)
+        return comonLazy(Image, a, b, c, d,w,x,y,z)
     @classmethod
     def execute(scls, Image, a, b=None, c=None, d=None, w=0.0, x=0.0, y=0.0, z=0.0):
         b = torch.zeros_like(a) if b is None else b

more_math/LatentMathNode.py

@@ -68,7 +68,7 @@ def define_schema(cls) -> io.Schema:
     #OUTPUT_TOOLTIPS = ("",) # Tooltips for the output node
     @classmethod
     def check_lazy_status(cls, Latent, a, b=[], c=[], d=[],w=0,x=0,y=0,z=0):
-        return comonLazy(Latent, a, b, c, d)
+        return comonLazy(Latent, a, b, c, d,w,x,y,z)
     @classmethod
     def execute(cls, Latent, a, b=None, c=None, d=None, w=0.0, x=0.0, y=0.0, z=0.0) -> io.NodeOutput:
         # Extract raw sample tensors (may be Tensor or NestedTensor)

more_math/ModelMathNode.py

@@ -36,7 +36,7 @@ def define_schema(cls) -> io.Schema:
 
     @classmethod
     def check_lazy_status(cls, Model, a, b=[], c=[], d=[],w=0,x=0,y=0,z=0):
-        return comonLazy(Model, a, b, c, d)
+        return comonLazy(Model, a, b, c, d,w,x,y,z)
 
     @classmethod
     def execute(cls, Model, a, b=None, c=None, d=None, w=0.0, x=0.0, y=0.0, z=0.0) -> io.NodeOutput:

more_math/NoiseMathNode.py

@@ -64,7 +64,7 @@ def define_schema(cls) -> io.Schema:
     CATEGORY = "More math"
     @classmethod
     def check_lazy_status(cls, Noise, a, b=[], c=[], d=[],w=0,x=0,y=0,z=0):
-        return comonLazy(Noise, a, b, c, d)
+        return comonLazy(Noise, a, b, c, d,w,x,y,z)
     @classmethod
     def execute(cls, Noise, a, b=None, c=None, d=None, w=0.0, x=0.0, y=0.0, z=0.0):
         return (NoiseExecutor(a, b, c, d, w, x, y, z, Noise),)

more_math/VaeMathNode.py

@@ -33,7 +33,7 @@ def define_schema(cls) -> io.Schema:
     tooltip = cleandoc(__doc__)
     @classmethod
     def check_lazy_status(cls, Model, a, b=[], c=[], d=[],w=0,x=0,y=0,z=0):
-        return comonLazy(Model, a, b, c, d)
+        return comonLazy(Model, a, b, c, d,w,x,y,z)
     @classmethod
     def execute(cls, Model, a, b=None, c=None, d=None, w=0.0, x=0.0, y=0.0, z=0.0) -> io.NodeOutput:
         patcher_a = a.patcher

more_math/helper_functions.py

@@ -40,10 +40,18 @@ def syntaxError(self, recognizer, offendingSymbol, line, column, msg, e):
 def comonLazy(expr, a, b=None, c=None, d=None, w=0.0, x=0.0, y=0.0, z=0.0):
     variables = {'a':a,'b':b,'c':c,'d':d,'w':w,'x':x,'y':y,'z':z}
     need_eval = []
+    print(a,b,c,d,w,x,y,z)
     input_stream = InputStream(expr)
+
     lexer = MathExprLexer(input_stream)
     stream = CommonTokenStream(lexer)
+    stream.fill()
+    print("Tokens:", stream.tokens)
     for token in filter(lambda t: t.type == MathExprParser.VARIABLE, stream.tokens):
-        if token in variables and variables[token] is None:
-            need_eval.append(token)
+        print("Token:", token.text)
+        print("Variables:", variables)
+        print("Token in variables:", token.text in variables)
+        print("Variable is None:", variables.get(token.text) is None)
+        if token.text in variables and variables[token.text] is None:
+            need_eval.append(token.text)
     print ("Need eval:", need_eval)