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Improve error message when Keras is unable to find a custom object.

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PiperOrigin-RevId: 342918274
Change-Id: I882e96c55d75fa1edf9688215b6738624ad93c63
This commit is contained in:
Katherine Wu 2020-11-17 12:15:40 -08:00 committed by TensorFlower Gardener
parent f096affea0
commit 5186e8295c
2 changed files with 26 additions and 2 deletions
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14
tensorflow/python/keras/utils/generic_utils.py
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@ -293,7 +293,12 @@ def class_and_config_for_serialized_keras_object(
class_name = config['class_name']
cls = get_registered_object(class_name, custom_objects, module_objects)
if cls is None:
raise ValueError('Unknown ' + printable_module_name + ': ' + class_name)
raise ValueError(
'Unknown {}: {}. Please ensure this object is '
'passed to the `custom_objects` argument. See '
'https://www.tensorflow.org/guide/keras/save_and_serialize'
'#registering_the_custom_object for details.'
.format(printable_module_name, class_name))
cls_config = config['config']
# Check if `cls_config` is a list. If it is a list, return the class and the
@ -375,7 +380,12 @@ def deserialize_keras_object(identifier,
obj = module_objects.get(object_name)
if obj is None:
raise ValueError(
'Unknown ' + printable_module_name + ': ' + object_name)
'Unknown {}: {}. Please ensure this object is '
'passed to the `custom_objects` argument. See '
'https://www.tensorflow.org/guide/keras/save_and_serialize'
'#registering_the_custom_object for details.'
.format(printable_module_name, object_name))
# Classes passed by name are instantiated with no args, functions are
# returned as-is.
if tf_inspect.isclass(obj):

14
tensorflow/python/keras/utils/generic_utils_test.py
View File

@ -354,6 +354,20 @@ class SerializeKerasObjectTest(test.TestCase):
expected_output = new_model.predict(input_data)
self.assertAllEqual(output, expected_output)
def test_deserialize_unknown_object(self):
class CustomLayer(keras.layers.Layer):
pass
layer = CustomLayer()
config = keras.utils.generic_utils.serialize_keras_object(layer)
with self.assertRaisesRegexp(ValueError,
'passed to the `custom_objects` arg'):
keras.utils.generic_utils.deserialize_keras_object(config)
restored = keras.utils.generic_utils.deserialize_keras_object(
config, custom_objects={'CustomLayer': CustomLayer})
self.assertIsInstance(restored, CustomLayer)
class SliceArraysTest(test.TestCase):