fix subtraction broadcasted access memory wrong values

norch/tensor.py

@@ -316,6 +316,8 @@ class Tensor:
         if isinstance(other, (int, float)):
             other = other * self.ones_like()
 
+        broadcasted_shape = []
+
         # Function to determine if broadcasting is needed and get the broadcasted shape
         def broadcast_shape(shape1, shape2):
             if shape1 == shape2:
@@ -325,7 +327,6 @@ class Tensor:
             shape1 = [1] * (max_len - len(shape1)) + shape1
             shape2 = [1] * (max_len - len(shape2)) + shape2
 
-            broadcasted_shape = []
             for dim1, dim2 in zip(shape1, shape2):
                 if dim1 != dim2 and dim1 != 1 and dim2 != 1:
                     raise ValueError("Shapes are not compatible for broadcasting")

test.py

@@ -9,7 +9,7 @@ W2 = norch.Tensor([[1], [2], [3], [4], [5], [6], [7], [8], [9], [10]], requires_
 B2 = norch.Tensor([[1, 2, 3, 4, 5]], requires_grad=True)
 
 
-Z1 = W1 @ X + B1
+Z1 = W1 @ X - B1
 
 # Perform matrix multiplication