I just followed this tutorial of Keras.io https://keras.io/examples/nlp/semantic_similarity_with_bert/
I can run it and the model works. When i want to save the model with h5 format I have this error :
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
<ipython-input-29-549810e352cb> in <module>()
----> 1 model.save('my_model.h5')
9 frames
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py in get_config(self)
2252
2253 def get_config(self):
-> 2254 raise NotImplementedError
2255
2256 @classmethod
NotImplementedError:
-----------------------------------------------------------------------------
when i want to do the same things with the "SavedModel" format I can save the model but when i try to load it, i have this error:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/nest.py in assert_same_structure(nest1, nest2, check_types, expand_composites)
403 _pywrap_utils.AssertSameStructure(nest1, nest2, check_types,
--> 404 expand_composites)
405 except (ValueError, TypeError) as e:
ValueError: The two structures don't have the same nested structure.
First structure: type=dict str={'input_ids': TensorSpec(shape=(None, 5), dtype=tf.int32, name='inputs/input_ids')}
Second structure: type=TensorSpec str=TensorSpec(shape=(None, 128), dtype=tf.int32, name='inputs')
More specifically: Substructure "type=dict str={'input_ids': TensorSpec(shape=(None, 5), dtype=tf.int32, name='inputs/input_ids')}" is a sequence, while substructure "type=TensorSpec str=TensorSpec(shape=(None, 128), dtype=tf.int32, name='inputs')" is not
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
7 frames
<ipython-input-33-ae06d36f12a1> in <module>()
----> 1 new_model = tf.keras.models.load_model('saved_model/my_model2', compile=False)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/saving/save.py in load_model(filepath, custom_objects, compile, options)
210 if isinstance(filepath, six.string_types):
211 loader_impl.parse_saved_model(filepath)
--> 212 return saved_model_load.load(filepath, compile, options)
213
214 raise IOError(
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/saving/saved_model/load.py in load(path, compile, options)
145
146 # Finalize the loaded layers and remove the extra tracked dependencies.
--> 147 keras_loader.finalize_objects()
148 keras_loader.del_tracking()
149
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/saving/saved_model/load.py in finalize_objects(self)
594 layers_revived_from_config.append(node)
595
--> 596 _finalize_saved_model_layers(layers_revived_from_saved_model)
597 _finalize_config_layers(layers_revived_from_config)
598
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/saving/saved_model/load.py in _finalize_saved_model_layers(layers)
783 call_fn = _get_keras_attr(layer).call_and_return_conditional_losses
784 if call_fn.input_signature is None:
--> 785 inputs = infer_inputs_from_restored_call_function(call_fn)
786 else:
787 inputs = call_fn.input_signature[0]
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/saving/saved_model/load.py in infer_inputs_from_restored_call_function(fn)
1068 for concrete in fn.concrete_functions[1:]:
1069 spec2 = concrete.structured_input_signature[0][0]
-> 1070 spec = nest.map_structure(common_spec, spec, spec2)
1071 return spec
1072
/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/nest.py in map_structure(func, *structure, **kwargs)
651 for other in structure[1:]:
652 assert_same_structure(structure[0], other, check_types=check_types,
--> 653 expand_composites=expand_composites)
654
655 flat_structure = (flatten(s, expand_composites) for s in structure)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/nest.py in assert_same_structure(nest1, nest2, check_types, expand_composites)
409 "Entire first structure:\n%s\n"
410 "Entire second structure:\n%s"
--> 411 % (str(e), str1, str2))
412
413
ValueError: The two structures don't have the same nested structure.
First structure: type=dict str={'input_ids': TensorSpec(shape=(None, 5), dtype=tf.int32, name='inputs/input_ids')}
Second structure: type=TensorSpec str=TensorSpec(shape=(None, 128), dtype=tf.int32, name='inputs')
More specifically: Substructure "type=dict str={'input_ids': TensorSpec(shape=(None, 5), dtype=tf.int32, name='inputs/input_ids')}" is a sequence, while substructure "type=TensorSpec str=TensorSpec(shape=(None, 128), dtype=tf.int32, name='inputs')" is not
Entire first structure:
{'input_ids': .}
Entire second structure:
.
------------------------------------------------------------------------------
Any ideas?
