do not wrap bool

torch_xla/stablehlo.py

@@ -237,16 +237,16 @@ def call_function(self, target, args: Tuple, kwargs: Dict) -> Any:
     # Under `fake_tensor_mode` a fake tensor will be created. This is not a
     # use case for XLAExportInterpreter right now, adding to be future-proof.
     with torch.utils._python_dispatch._disable_current_modes():
-      # If the op spec expects a `Tensor` input, we wrap the python primitive
-      # type to a torch.tensor. The dtype for float respects
+      # If the op spec expects a `Tensor` input, we wrap the python float/int
+      # to a torch.tensor. The dtype for float respects
       # `torch.get_default_dtype`. Without this wrapping, the python float
       # will be wrapped before it enters dispatcher, and it doesn't respect
       # the global default dtype.
       args_and_specs = tuple(zip(args, target._schema.arguments))
       args = tuple(
           map(
               lambda arg_spec: torch.tensor(arg_spec[0])
-              if isinstance(arg_spec[0], (float, int, bool)) and type(arg_spec[
+              if isinstance(arg_spec[0], (float, int)) and type(arg_spec[
                   1].type) == torch.TensorType else arg_spec[0],
               args_and_specss))
     return super().call_function(target, args, new_kwargs)