fix wierd bug with reshape (AI)

Author: mcDandy

more_math/Parser/UnifiedMathVisitor.py

@@ -176,6 +176,21 @@ def _reduction_op(self, val, torch_op, list_op):
             return list_op(val)
         return val
 
+    def _to_int(self, x, ctx, context_name="operation"):
+        """Convert value to int, handling tensors and nested lists recursively"""
+        if self._is_tensor(x):
+            if x.numel() == 1:
+                return int(x.item())
+            else:
+                raise ValueError(f"{ctx.start.line}:{ctx.start.column}: {context_name} expects scalar dimensions, got tensor with shape {x.shape}")
+        elif self._is_list(x):
+            if len(x) == 1:
+                return self._to_int(x[0], ctx, context_name)
+            else:
+                raise ValueError(f"{ctx.start.line}:{ctx.start.column}: {context_name} expects scalar dimensions, got list with {len(x)} elements")
+        else:
+            return int(float(x))
+
     # ========================
     # Visitors
     # ========================
@@ -996,14 +1011,7 @@ def visitReshapeFunc(self, ctx):
         elif isinstance(new_shape, (list, tuple)):
             result = []
             for d in new_shape:
-                if self._is_tensor(d):
-                    # Handle tensor elements in list
-                    if d.numel() == 1:
-                        result.append(int(d.item()))
-                    else:
-                        raise ValueError(f"{ctx.start.line}:{ctx.start.column}: reshape expects scalar dimensions, got tensor with shape {d.shape}")
-                else:
-                    result.append(int(float(d)))
+                result.append(self._to_int(d, ctx, "reshape"))
             new_shape = result
         elif isinstance(new_shape, (int, float)):
             new_shape = [int(float(new_shape))]