Preserve the UNSPECIFIED conversion status when not converting by default. Fix the conversion decorator tot only apply functools.wraps if the target is a function.

PiperOrigin-RevId: 254323896

tensorflow/python/autograph/impl/api.py

@@ -159,14 +159,18 @@ def tf_convert(f, ctx, convert_by_default=True, force_conversion=False):
   f_wrapper = f
   decorators, f = tf_decorator.unwrap(f)
 
-  apply_autograph = ((ctx.status == ag_ctx.Status.ENABLED) or
-                     (convert_by_default and
-                      ctx.status == ag_ctx.Status.UNSPECIFIED))
-  if apply_autograph:
   # TODO(mdan): Grab features from context.
+  if ctx.status == ag_ctx.Status.ENABLED:
+    wrapper = convert(recursive=True, force_conversion=force_conversion)(f)
+  elif ctx.status == ag_ctx.Status.DISABLED:
+    wrapper = do_not_convert(f)
+  elif ctx.status == ag_ctx.Status.UNSPECIFIED:
+    if convert_by_default:
       wrapper = convert(recursive=True, force_conversion=force_conversion)(f)
     else:
-    wrapper = do_not_convert(f)
+      wrapper = call_with_unspecified_conversion_status(f)
+  else:
+    raise ValueError(ctx.status)
 
   if decorators:
     wrapper = tf_decorator.rewrap(f_wrapper, f, wrapper)
@@ -246,6 +250,19 @@ class RunMode(Enum):
   PY_FUNC = 2
 
 
+def call_with_unspecified_conversion_status(func):
+  """Decorator that resets the conversion context to the unspecified status."""
+  def wrapper(*args, **kwargs):
+    with ag_ctx.ControlStatusCtx(status=ag_ctx.Status.UNSPECIFIED):
+      return func(*args, **kwargs)
+
+  if inspect.isfunction(func) or inspect.ismethod(func):
+    wrapper = functools.update_wrapper(wrapper, func)
+
+  setattr(wrapper, '__ag_compiled', True)
+  return wrapper
+
+
 def do_not_convert_internal(f):
   """Decorator that marks internal functions which do not need conversion."""
   setattr(f, '__ag_compiled', True)
@@ -279,12 +296,10 @@ def do_not_convert(func=None, run_as=RunMode.GRAPH, return_dtypes=None):
         run_as=run_as,
         return_dtypes=return_dtypes)
 
-  @functools.wraps(func)
   def graph_wrapper(*args, **kwargs):
     with ag_ctx.ControlStatusCtx(status=ag_ctx.Status.DISABLED):
       return func(*args, **kwargs)
 
-  @functools.wraps(func)
   def py_func_wrapper(*args, **kwargs):
     if kwargs:
       raise NotImplementedError('RunMode.PY_FUNC does not yet support kwargs')
@@ -299,6 +314,9 @@ def do_not_convert(func=None, run_as=RunMode.GRAPH, return_dtypes=None):
   else:
     raise ValueError('unknown value for run_as: %s' % run_as)
 
+  if inspect.isfunction(func) or inspect.ismethod(func):
+    wrapper = functools.update_wrapper(wrapper, func)
+
   setattr(wrapper, '__ag_compiled', True)
   return wrapper
 

tensorflow/python/autograph/impl/api_test.py

@@ -212,6 +212,16 @@ class ApiTest(test.TestCase):
     self.assertEqual((),
                      tuple(function_utils.fn_args(tc.test_method_whitelisted)))
 
+  def test_do_not_convert_callable_object(self):
+
+    class TestClass(object):
+
+      def __call__(self):
+        return 1
+
+    tc = TestClass()
+    self.assertEqual(1, api.do_not_convert(tc)())
+
   @test_util.run_deprecated_v1
   def test_convert_call_site_decorator(self):
 
@@ -729,6 +739,12 @@ class ApiTest(test.TestCase):
     self.assertEqual(
         ag_ctx.control_status_ctx().status, ag_ctx.Status.UNSPECIFIED)
 
+    @api.call_with_unspecified_conversion_status
+    def unspecified_fn():
+      self.assertEqual(
+          ag_ctx.control_status_ctx().status, ag_ctx.Status.UNSPECIFIED)
+    unspecified_fn()
+
   def test_to_graph_basic(self):
 
     def test_fn(x, s):
@@ -888,6 +904,23 @@ class ApiTest(test.TestCase):
       # The code in `f` is only valid with AutoGraph.
       test_fn(ag_ctx.ControlStatusCtx(status=ag_ctx.Status.DISABLED))
 
+  def test_tf_convert_unspecified_not_converted_by_default(self):
+
+    def f():
+      self.assertEqual(
+          ag_ctx.control_status_ctx().status, ag_ctx.Status.UNSPECIFIED)
+      if tf.reduce_sum([1, 2]) > 0:
+        return -1
+      return 1
+
+    @def_function.function
+    def test_fn(ctx):
+      return api.tf_convert(f, ctx, convert_by_default=False)()
+
+    with self.assertRaisesRegex(TypeError, 'tf.Tensor.*bool'):
+      # The code in `f` is only valid with AutoGraph.
+      test_fn(ag_ctx.ControlStatusCtx(status=ag_ctx.Status.UNSPECIFIED))
+
   def test_tf_convert_whitelisted_method(self):
 
     model = sequential.Sequential([