Fix tests.

test/test_operations.py

@@ -67,6 +67,22 @@ def _is_on_eager_debug_mode():
                                    'skip on eager debug mode')
 
 
+def _skipIfFunctionalization(disabled=True, reason=""):
+  verb = "is" if disabled else "is not"
+  reason = f" Reason: {reason}" if reason else ""
+  return unittest.skipIf(
+      XLA_DISABLE_FUNCTIONALIZATION,
+      f'Works only when functionalization {verb} disabled.{reason}.')
+
+
+def skipIfFunctionalizationEnabled(reason):
+  return _skipIfFunctionalization(disabled=False, reason=reason)
+
+
+def skipIfFunctionalizationDisabled(reason):
+  return _skipIfFunctionalization(disabled=True, reason=reason)
+
+
 def _gen_tensor(*args, **kwargs):
   return torch.randn(*args, **kwargs)
 
@@ -978,8 +994,7 @@ def func(a, b):
 
   # TODO - upstream behavior has changed and results in expected DestroyXlaTensor
   # counter as of 11/13/2023. Re-enable after reviewing the change.
-  @unittest.skipIf(True or XLA_DISABLE_FUNCTIONALIZATION,
-                   'Metrics differ when functionalization is disabled.')
+  @skipIfFunctionalizationDisabled("metrics differ")
   def test_set(self):
     met.clear_all()
 
@@ -997,8 +1012,7 @@ def test_set(self):
     # shouldn't crash
     self.assertTrue(torch.allclose(t2.cpu(), torch.zeros(10)))
 
-  @unittest.skipIf(XLA_DISABLE_FUNCTIONALIZATION,
-                   'Metrics differ when functionalization is disabled.')
+  @skipIfFunctionalizationDisabled("metrics differ")
   def test_replace_xla_tensor(self):
     met.clear_all()
 
@@ -1341,8 +1355,7 @@ def test_fn(t, c):
         ), dtype=torch.int64)
     self.runAtenTest([token_type_ids, cat_ids], test_fn)
 
-  @unittest.skipIf(not XLA_DISABLE_FUNCTIONALIZATION,
-                   'When functionalization is enabled, views do not exist.')
+  @skipIfFunctionalizationEnabled("views do not exist")
   def test_save_view_alias_check(self):
 
     class Nested(object):
@@ -1498,41 +1511,47 @@ def test_fn(r):
 
     self.runAtenTest([torch.arange(144, dtype=torch.int32)], test_fn)
 
+  @skipIfFunctionalizationDisabled("arbitrary as_strided unsupported")
   def test_as_strided_with_gap(self):
 
     def test_fn(r):
       return torch.as_strided(r, (4, 4), (8, 1))
 
     self.runAtenTest([torch.arange(28, dtype=torch.int32)], test_fn)
 
+  @skipIfFunctionalizationDisabled("arbitrary as_strided unsupported")
   def test_as_strided_with_gap_no_unit_stride(self):
 
     def test_fn(r):
       return torch.as_strided(r, (4, 4), (8, 2))
 
     self.runAtenTest([torch.arange(31, dtype=torch.int32)], test_fn)
 
+  @skipIfFunctionalizationDisabled("arbitrary as_strided unsupported")
   def test_as_strided_with_overlap(self):
 
     def test_fn(r):
       return torch.as_strided(r, (4, 4), (2, 1))
 
     self.runAtenTest([torch.arange(10, dtype=torch.int32)], test_fn)
 
+  @skipIfFunctionalizationDisabled("arbitrary as_strided unsupported")
   def test_as_strided_with_overlap_and_gap(self):
 
     def test_fn(r):
       return torch.as_strided(r, (4, 4), (4, 2))
 
     self.runAtenTest([torch.arange(19, dtype=torch.int32)], test_fn)
 
+  @skipIfFunctionalizationDisabled("arbitrary as_strided unsupported")
   def test_as_strided_with_overlap_zero_stride(self):
 
     def test_fn(r):
       return torch.as_strided(r, (4, 4), (0, 1))
 
     self.runAtenTest([torch.arange(19, dtype=torch.int32)], test_fn)
 
+  @skipIfFunctionalizationDisabled("arbitrary as_strided unsupported")
   def test_as_strided_with_gap_no_unit_stride(self):
 
     def test_fn(r):
@@ -1541,6 +1560,7 @@ def test_fn(r):
 
     self.runAtenTest([torch.arange(32, dtype=torch.int32)], test_fn)
 
+  @skipIfFunctionalizationDisabled("arbitrary as_strided unsupported")
   def test_as_strided_with_empty_args(self):
 
     def test_fn(r):