torch: allow python scalars in result_type

array_api_compat/torch/_aliases.py

@@ -119,6 +119,9 @@ def _fix_promotion(x1, x2, only_scalar=True):
         x1 = x1.to(dtype)
     return x1, x2
 
+
+_torch_dtype_and_py_scalars = (torch.dtype, bool, int, float, complex)
+
 def result_type(*arrays_and_dtypes: Union[array, Dtype]) -> Dtype:
     if len(arrays_and_dtypes) == 0:
         raise TypeError("At least one array or dtype must be provided")
@@ -140,8 +143,8 @@ def result_type(*arrays_and_dtypes: Union[array, Dtype]) -> Dtype:
     # This doesn't result_type(dtype, dtype) for non-array API dtypes
     # because torch.result_type only accepts tensors. This does however, allow
     # cross-kind promotion.
-    x = torch.tensor([], dtype=x) if isinstance(x, torch.dtype) else x
-    y = torch.tensor([], dtype=y) if isinstance(y, torch.dtype) else y
+    x = torch.tensor([], dtype=x) if isinstance(x, _torch_dtype_and_py_scalars) else x
+    y = torch.tensor([], dtype=y) if isinstance(y, _torch_dtype_and_py_scalars) else y
     return torch.result_type(x, y)
 
 def can_cast(from_: Union[Dtype, array], to: Dtype, /) -> bool: