fix longstanding bug of tensor OP list

more_math/Parser/UnifiedMathVisitor.py

@@ -101,13 +101,13 @@ class UnifiedMathVisitor(MathExprVisitor):
         # one of them is a list and one is tensor
         if self._is_tensor(a) and self._is_list(b):
              if(a.shape[0]==len(b)):
-                c = torch.split(a,1)
-                return torch.cat([self._bin_op(x, y, torch_op, scalar_op) for x,y in zip(a,c)],dim=0)
+                A = torch.split(a,1)
+                return torch.cat([self._bin_op(x, y, torch_op, scalar_op) for x,y in zip(A,b)],dim=0)
              return torch.cat([self._bin_op(a, x, torch_op, scalar_op) for x in b], dim=0)
         if self._is_list(a) and self._is_tensor(b):
             if(b.shape[0]==len(a)):
-                c = torch.split(a,1)
-                return torch.cat([self._bin_op(x, y, torch_op, scalar_op) for x,y in zip(c,b)],dim=0)
+                B = torch.split(b,1)
+                return torch.cat([self._bin_op(x, y, torch_op, scalar_op) for x,y in zip(a,B)],dim=0)
             return torch.cat([self._bin_op(x, b, torch_op, scalar_op) for x in a], dim=0)
 
         if self._is_list(a) and not self._is_tensor(b):

more_math/helper_functions.py

@@ -22,8 +22,8 @@ def as_tensor(value, shape):
         return value.contiguous()
     if isinstance(value, (float, int)):
         value = (value,)
-    # If it's a scalar or list, broadcast to the reference shape provided.
-    return torch.broadcast_to(torch.Tensor(value).to(dtype=torch.float32), shape).contiguous()
+        return torch.broadcast_to(torch.Tensor(value).to(dtype=torch.float32), shape).contiguous()
+    return torch.cat(value)
 
 
 def parse_expr(expr: str):