pass bundle object to make_tf_function (pytorch#5708)

* Pass bundle object to make_tf_function, so that it will include tf.variables as args to the XlaCallModule op.

* fix format

torch_xla/tf_saved_model_integration.py

@@ -36,9 +36,12 @@ def inner(*args):
   return inner
 
 
-def make_tf_function(stablehlo_program: stablehlo.StableHLOGraphModule):
-  return _wrap_as_tf_func(stablehlo_program._bundle.stablehlo_funcs[0],
-                          stablehlo_program._bundle)
+def make_tf_function(stablehlo_program: stablehlo.StableHLOGraphModule,
+                     bundle=None):
+  if bundle is None:
+    return _wrap_as_tf_func(stablehlo_program._bundle.stablehlo_funcs[0],
+                            stablehlo_program._bundle)
+  return _wrap_as_tf_func(stablehlo_program._bundle.stablehlo_funcs[0], bundle)
 
 
 def _make_input_signatures(
@@ -86,7 +89,8 @@ def save_stablehlo_graph_as_tf(
   input_signatures = list(
       _make_input_signatures(bundle.stablehlo_funcs[0].meta))
   tfm.f = tf.function(
-      make_tf_function(stablehlo_program), input_signature=input_signatures)
+      make_tf_function(stablehlo_program, bundle),
+      input_signature=input_signatures)
   tfm._variables = (
       list(bundle.state_dict.values()) + bundle.additional_constants)
   signatures = {serving_key: tfm.f.get_concrete_function(*input_signatures)}