Clarify generic tuple inference

This hoist a loop invariant conditional check outside the loop
making it clearer and one branch more obviously similar to the
general type handling.

jedi/inference/gradual/annotation.py

@@ -445,17 +445,6 @@ def _infer_type_vars(annotation_value, value_set, is_class_value=False):
                         )
                     )
         elif annotation_name == 'Tuple':
-            # TODO: this logic is pretty similar to the general logic below, can
-            # we combine them?
-
-            for element in value_set:
-                py_class = element.get_annotated_class_object()
-                if not isinstance(py_class, GenericClass):
-                    py_class = element
-
-                if not isinstance(py_class, DefineGenericBase):
-                    continue
-
             annotation_generics = annotation_value.get_generics()
             tuple_annotation, = annotation_value.execute_annotation()
             # TODO: is can we avoid using this private method?
@@ -477,6 +466,17 @@ def _infer_type_vars(annotation_value, value_set, is_class_value=False):
                 # treat the incoming values as needing to match the annotation
                 # exactly, just as we would for non-tuple annotations.
 
+                # TODO: this logic is pretty similar to the general logic below, can
+                # we combine them?
+
+                for element in value_set:
+                    py_class = element.get_annotated_class_object()
+                    if not isinstance(py_class, GenericClass):
+                        py_class = element
+
+                    if not isinstance(py_class, DefineGenericBase):
+                        continue
+
                     actual_generics = py_class.get_generics()
                     merge_pairwise_generics(annotation_generics, actual_generics)