Do not catch and warn for exceptions raised while calling a function without conversion. Fixes #36792.

PiperOrigin-RevId: 303366732
Change-Id: I579793f5625bf90e07ab8ea1cb97bd324bae9935

tensorflow/python/autograph/impl/api.py

@@ -375,6 +375,44 @@ def _is_known_loaded_type(f, module_name, entity_name):
   return False
 
 
+def _fall_back_unconverted(f, args, kwargs, options, exc):
+  """Falls back to calling the function unconverted, in case of error."""
+  # TODO(mdan): Consider adding an internal metric.
+  warning_template = (
+      'AutoGraph could not transform %s and will run it as-is.\n'
+      '%s'
+      'Cause: %s\n'
+      'To silence this warning, decorate the function with'
+      ' @tf.autograph.experimental.do_not_convert')
+  if isinstance(exc, errors.UnsupportedLanguageElementError):
+    if not conversion.is_in_whitelist_cache(f, options):
+      logging.warn(warning_template, f, '', exc)
+  else:
+    file_bug_message = (
+        'Please report this to the TensorFlow team. When filing the bug, set'
+        ' the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and'
+        ' attach the full output.\n')
+    logging.warn(warning_template, f, file_bug_message, exc)
+
+  return _call_unconverted(f, args, kwargs, options)
+
+
+def _log_callargs(f, args, kwargs):
+  """Logging helper."""
+  logging.log(2, 'Defaults of %s : %s', f, f.__defaults__)
+  if not six.PY2:
+    logging.log(2, 'KW defaults of %s : %s', f, f.__kwdefaults__)
+
+  if kwargs is not None:
+    callargs = tf_inspect.getcallargs(f, *args, **kwargs)
+  else:
+    callargs = tf_inspect.getcallargs(f, *args)
+
+  formatted_callargs = '\n'.join(
+      '    {}: {}'.format(k, v) for k, v in callargs.items())
+  logging.log(2, 'Calling %s with\n%s\n', f, formatted_callargs)
+
+
 def converted_call(f,
                    args,
                    kwargs,
@@ -498,9 +536,7 @@ def converted_call(f,
   if not options.internal_convert_user_code:
     return _call_unconverted(f, args, kwargs, options)
 
-  # TODO(mdan): Move this entire block inside to_graph.
-  try:  # Begin of transformation error guards
-
+  try:
     if inspect.ismethod(f) or inspect.isfunction(f):
       target_entity = f
       effective_args = args
@@ -514,6 +550,8 @@ def converted_call(f,
     elif hasattr(f, '__class__') and hasattr(f.__class__, '__call__'):
       # Callable objects. Dunder methods have special lookup rules, see:
       # https://docs.python.org/3/reference/datamodel.html#specialnames
+      # TODO(mdan): Recurse into converted_call to simplify other verifications.
+      # This should be handled in the same way as partials.
       target_entity = f.__class__.__call__
       effective_args = (f,) + args
 
@@ -521,63 +559,34 @@ def converted_call(f,
       target_entity = f
       raise NotImplementedError('unknown callable type "%s"' % type(f))
 
-    if not inspect.isclass(target_entity):
-      if not hasattr(target_entity, '__code__'):
-        logging.log(2, 'Permanently whitelisted: %s: native binding',
-                    target_entity)
-        return _call_unconverted(f, args, kwargs, options)
-      elif (hasattr(target_entity.__code__, 'co_filename') and
-            target_entity.__code__.co_filename == '<string>'):
-        # TODO(mdan): __globals__['txt'] might work in Py3.
-        logging.log(2, 'Permanently whitelisted: %s: dynamic code (exec?)',
-                    target_entity)
-        return _call_unconverted(f, args, kwargs, options)
-
-    program_ctx = converter.ProgramContext(
-        options=options, autograph_module=tf_inspect.getmodule(converted_call))
-    converted_f = conversion.convert(target_entity, program_ctx)
-
-    if logging.has_verbosity(2):
-      logging.log(2, 'Defaults of %s : %s', converted_f,
-                  converted_f.__defaults__)
-      if not six.PY2:
-        logging.log(2, 'KW defaults of %s : %s',
-                    converted_f, converted_f.__kwdefaults__)
-
-      if kwargs is not None:
-        callargs = tf_inspect.getcallargs(converted_f, *effective_args,
-                                          **kwargs)
-      else:
-        callargs = tf_inspect.getcallargs(converted_f, *effective_args)
-
-      formatted_callargs = '\n'.join(
-          '    {}: {}'.format(k, v) for k, v in callargs.items())
-      logging.log(2, 'Calling %s with\n%s\n', converted_f, formatted_callargs)
-
   except Exception as e:  # pylint:disable=broad-except
     logging.log(1, 'Error transforming entity %s', target_entity, exc_info=True)
     if is_autograph_strict_conversion_mode():
       raise
+    return _fall_back_unconverted(f, args, kwargs, options, e)
 
-    warning_template = (
-        'AutoGraph could not transform %s and will run it as-is.\n'
-        '%s'
-        'Cause: %s\n'
-        'To silence this warning, decorate the function with'
-        ' @tf.autograph.experimental.do_not_convert')
-    if isinstance(e, errors.UnsupportedLanguageElementError):
-      # Repeating the check made upon function entry because the state might
-      # have updated in the meantime.
-      if not conversion.is_in_whitelist_cache(f, options):
-        logging.warn(warning_template, target_entity, '', e)
-    else:
-      file_bug_message = (
-          'Please report this to the TensorFlow team. When filing the bug, set'
-          ' the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and'
-          ' attach the full output.\n')
-      logging.warn(warning_template, target_entity, file_bug_message, e)
-
+  if not hasattr(target_entity, '__code__'):
+    logging.log(2, 'Permanently whitelisted: %s: native binding',
+                target_entity)
     return _call_unconverted(f, args, kwargs, options)
+  elif (hasattr(target_entity.__code__, 'co_filename') and
+        target_entity.__code__.co_filename == '<string>'):
+    # TODO(mdan): __globals__['txt'] might work in Py3.
+    logging.log(2, 'Permanently whitelisted: %s: dynamic code (exec?)',
+                target_entity)
+    return _call_unconverted(f, args, kwargs, options)
+
+  try:
+    program_ctx = converter.ProgramContext(
+        options=options, autograph_module=tf_inspect.getmodule(converted_call))
+    converted_f = conversion.convert(target_entity, program_ctx)
+    if logging.has_verbosity(2):
+      _log_callargs(converted_f, effective_args, kwargs)
+  except Exception as e:  # pylint:disable=broad-except
+    logging.log(1, 'Error transforming entity %s', target_entity, exc_info=True)
+    if is_autograph_strict_conversion_mode():
+      raise
+    return _fall_back_unconverted(f, args, kwargs, options, e)
 
   with StackTraceMapper(converted_f), tf_stack.CurrentModuleFilter():
     try:

tensorflow/python/autograph/impl/api_test.py

@@ -753,6 +753,27 @@ class ApiTest(test.TestCase):
 
     self.assertAllEqual(1, self.evaluate(x))
 
+  def test_converted_call_native_binding(self):
+    x = api.converted_call(np.power, (2, 2), None, options=DEFAULT_RECURSIVE)
+    self.assertAllEqual(x, 4)
+
+  def test_converted_call_native_binding_errorneous(self):
+
+    class FaultyBinding(object):
+
+      def __array__(self):
+        raise ValueError('fault')
+
+    bad_obj = FaultyBinding()
+
+    def fail_if_warning(*_):
+      self.fail('No warning should be issued')
+
+    with test.mock.patch.object(ag_logging, 'warn', fail_if_warning):
+      with self.assertRaisesRegex(ValueError, 'fault'):
+        api.converted_call(
+            np.power, (bad_obj, 2), None, options=DEFAULT_RECURSIVE)
+
   def test_converted_call_through_tf_dataset(self):
 
     def other_fn(x):