Messed up and switched width and height

Author: mcDandy

src/more_math/ImageMathNode.py

@@ -97,13 +97,13 @@ def imgMathNode(self, Image, a, b=None, c=None, d=None, w=0.0, x=0.0, y=0.0, z=0
         d = torch.zeros_like(a) if d is None else d
 
         batch = range(0,a.shape[0],1)
-        width = range(0,a.shape[1],1)
-        height = range(0,a.shape[2],1)
+        width = range(0,a.shape[2],1)
+        height = range(0,a.shape[1],1)
         color = range(0,a.shape[3],1)
 
         B = getIndexTensorAlongDim(a, 0)
-        W = getIndexTensorAlongDim(a, 1)
-        H = getIndexTensorAlongDim(a, 2)
+        W = getIndexTensorAlongDim(a, 2)
+        H = getIndexTensorAlongDim(a, 1)
         C = getIndexTensorAlongDim(a, 3)
 
         variables = {'a': a, 'b': b, 'c': c, 'd': d, 'w': w, 'x': x, 'y': y, 'z': z,'B':B,'X':W,'Y':H,'C':C,'W':a.shape[1],'H':a.shape[2] }

src/more_math/LatentMathNode.py

@@ -95,11 +95,11 @@ def latMathNode(self, Latent, a, b=None, c=None, d=None, w=0.0, x=0.0, y=0.0, z=
         d = torch.zeros_like(a) if d is None else d["samples"]
 
         B = getIndexTensorAlongDim(a, 0)
-        W = getIndexTensorAlongDim(a, 2)
-        H = getIndexTensorAlongDim(a, 3)
+        W = getIndexTensorAlongDim(a, 3)
+        H = getIndexTensorAlongDim(a, 2)
         C = getIndexTensorAlongDim(a, 1)
 
-        variables = {'a': a, 'b': b, 'c': c, 'd': d, 'w': w, 'x': x, 'y': y, 'z': z,'B':B,'X':W,'Y':H,'C':C,'W':a.shape[2],'H':a.shape[3]}
+        variables = {'a': a, 'b': b, 'c': c, 'd': d, 'w': w, 'x': x, 'y': y, 'z': z,'B':B,'X':W,'Y':H,'C':C,'W':a.shape[3],'H':a.shape[2]}
         input_stream = InputStream(Latent)
         lexer = MathExprLexer(input_stream)
         stream = CommonTokenStream(lexer)

src/more_math/NoiseMathNode.py

@@ -136,11 +136,11 @@ def generate_noise(self, input_latent:torch.Tensor) -> torch.Tensor:
             self.vd = self.vd.generate_noise(input_latent)
 
         B = getIndexTensorAlongDim(input_latent["samples"], 0)
-        W = getIndexTensorAlongDim(input_latent["samples"], 2)
-        H = getIndexTensorAlongDim(input_latent["samples"], 3)
+        W = getIndexTensorAlongDim(input_latent["samples"], 3)
+        H = getIndexTensorAlongDim(input_latent["samples"], 2)
         C = getIndexTensorAlongDim(input_latent["samples"], 1)
 
-        variables = {'a': self.va.generate_noise(input_latent), 'b': self.vb, 'c': self.vc, 'd': self.vd, 'w': self.vw, 'x': self.vx, 'y': self.vy, 'z': self.vz,'B':B,'X':W,'Y':H,'C':C,'W':input_latent["samples"].shape[2],'H':input_latent["samples"].shape[3],'I':input_latent["samples"]}
+        variables = {'a': self.va.generate_noise(input_latent), 'b': self.vb, 'c': self.vc, 'd': self.vd, 'w': self.vw, 'x': self.vx, 'y': self.vy, 'z': self.vz,'B':B,'X':W,'Y':H,'C':C,'W':input_latent["samples"].shape[3],'H':input_latent["samples"].shape[2],'I':input_latent["samples"]}
         input_stream = InputStream(self.expr)
         lexer = MathExprLexer(input_stream)
         stream = CommonTokenStream(lexer)