Update on "std/var: Deprecate overloads with "unbiased" argument"

peterbell10 · peterbell10 · commit 5189f9281023 · 2021-04-27T19:37:21.000+01:00
[ghstack-poisoned]
diff --git a/test/test_fx_experimental.py b/test/test_fx_experimental.py
@@ -1264,7 +1264,8 @@ class TestNormalizeOperators(JitTestCase):
     @ops(op_db, allowed_dtypes=(torch.float,))
     def test_normalize_operator_exhaustive(self, device, dtype, op):
         # Unsupported input types
-        if op.name in {'index_put', '__getitem__', 'unfold', 'repeat', 'polygamma'}:
+        if op.name in {'index_put', '__getitem__', 'unfold', 'repeat', 'polygamma',
+                       'std', 'var'}:
             return
         # These ops currently don't trace in FX for various reasons (i.e. they take a list of tensors)
         fx_fail = {'stack', 'hstack', 'vstack', 'dstack',
diff --git a/torch/fx/operator_schemas.py b/torch/fx/operator_schemas.py
@@ -126,9 +126,9 @@ def is_homogeneous_int_tuple(t):
             return True
         return all(c is int or (c is Ellipsis) for c in contained)
 
-    if signature_type is List[int]:
+    if signature_type is List[int] and is_homogeneous_int_tuple(argument_type):
         # Tuple[int] is accepted for List[int] parameters
-        return is_homogeneous_int_tuple(argument_type)
+        return True
 
     # Dtype is an int in schemas
     if signature_type is int and argument_type is torch.dtype:
@@ -207,16 +207,14 @@ def normalize_function(
                     arg_types = arg_types if arg_types else cast(Tuple[Any], ())
                     kwarg_types = kwarg_types if kwarg_types else {}
                     for candidate_signature in torch_op_schemas:
+                        sig_matches = True
                         try:
                             bound_types = candidate_signature.bind(*arg_types, **kwarg_types)
+                            for arg_name, arg_type in bound_types.arguments.items():
+                                param = candidate_signature.parameters[arg_name]
+                                sig_matches = sig_matches and type_matches(param.annotation, arg_type)
                         except TypeError as e:
-                            continue
-
-                        sig_matches = True
-                        for arg_name, arg_type in bound_types.arguments.items():
-                            param = candidate_signature.parameters[arg_name]
-                            sig_matches = sig_matches and type_matches(param.annotation, arg_type)
-
+                            sig_matches = False
                         if sig_matches:
                             new_kwargs = _args_kwargs_to_normalized_kwargs(candidate_signature, args, kwargs)
                             break
