Export model config

Bug Description

Can’t export config properly from Autokeras classifier.

Bug Reproduction

Code for reproducing the bug:

from sklearn.datasets import load_iris
import autokeras as ak
import tensorflow as tf

X, y = load_iris(return_X_y=True)

# Initialize the image classifier.
clf = ak.StructuredDataClassifier(max_trials=2)
# Feed the image classifier with training data.
clf.fit(X, y, epochs=2)
# Export as a Keras Model.
clf.evaluate(X, y)
model = clf.export_model()

config = model.get_config()
yaml_config = model.to_yaml()
json_config = model.to_json()

json_model = tf.keras.models.model_from_json(json_config, custom_objects=ak.CUSTOM_OBJECTS)
# yaml_model = tf.keras.models.model_from_yaml(yaml_config, custom_objects=ak.CUSTOM_OBJECTS)
# model = tf.keras.models.model_from_config(config, custom_objects=ak.CUSTOM_OBJECTS)
json_model.compile(loss='categorical_crossentropy', metrics=['accuracy'])

binary_y = tf.keras.utils.to_categorical(y)
json_model.fit(X, binary_y)

Error messages:

Rebuild model from yaml is a comment, because it failed with the following message:

C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\keras\saving\model_config.py:76: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
  config = yaml.load(yaml_string)
Traceback (most recent call last):
  File "C:/PyCharmProjects/datascience-phd-automl/autokeras_test.py", line 20, in <module>
    yaml_model = tf.keras.models.model_from_yaml(yaml_config, custom_objects=ak.CUSTOM_OBJECTS)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\keras\saving\model_config.py", line 76, in model_from_yaml
    config = yaml.load(yaml_string)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\yaml\__init__.py", line 114, in load
    return loader.get_single_data()
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\yaml\constructor.py", line 43, in get_single_data
    return self.construct_document(node)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\yaml\constructor.py", line 52, in construct_document
    for dummy in generator:
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\yaml\constructor.py", line 405, in construct_yaml_map
    value = self.construct_mapping(node)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\yaml\constructor.py", line 210, in construct_mapping
    return super().construct_mapping(node, deep=deep)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\yaml\constructor.py", line 135, in construct_mapping
    value = self.construct_object(value_node, deep=deep)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\yaml\constructor.py", line 92, in construct_object
    data = constructor(self, node)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\yaml\constructor.py", line 421, in construct_undefined
    node.start_mark)
yaml.constructor.ConstructorError: could not determine a constructor for the tag 'tag:yaml.org,2002:python/object/apply:tensorflow.python.training.tracking.data_structures.ListWrapper'
  in "<unicode string>", line 23, column 17:
          encoding: !!python/object/apply:tensorflow ... 

Rebuild model from config is a comment, because it failed with the following message:

Traceback (most recent call last):
  File "C:/PyCharmProjects/datascience-phd-automl/autokeras_test.py", line 21, in <module>
    model = tf.keras.models.model_from_config(config, custom_objects=ak.CUSTOM_OBJECTS)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\keras\saving\model_config.py", line 55, in model_from_config
    return deserialize(config, custom_objects=custom_objects)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\keras\layers\serialization.py", line 98, in deserialize
    layer_class_name = config['class_name']
KeyError: 'class_name'

Rebuilding model with json architecture seems to be ok, but I have the following error message when fitting the model:

 32/150 [=====>........................] - ETA: 1sTraceback (most recent call last):
  File "C:/PyCharmProjects/datascience-phd-automl/autokeras_test.py", line 25, in <module>
    json_model.fit(X, binary_y)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\keras\engine\training.py", line 819, in fit
    use_multiprocessing=use_multiprocessing)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\keras\engine\training_v2.py", line 342, in fit
    total_epochs=epochs)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\keras\engine\training_v2.py", line 128, in run_one_epoch
    batch_outs = execution_function(iterator)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\keras\engine\training_v2_utils.py", line 98, in execution_function
    distributed_function(input_fn))
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\eager\def_function.py", line 568, in __call__
    result = self._call(*args, **kwds)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\eager\def_function.py", line 632, in _call
    return self._stateless_fn(*args, **kwds)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\eager\function.py", line 2363, in __call__
    return graph_function._filtered_call(args, kwargs)  # pylint: disable=protected-access
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\eager\function.py", line 1611, in _filtered_call
    self.captured_inputs)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\eager\function.py", line 1692, in _call_flat
    ctx, args, cancellation_manager=cancellation_manager))
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\eager\function.py", line 545, in call
    ctx=ctx)
  File "C:\PyCharmProjects\datascience-phd-automl\venv\lib\site-packages\tensorflow_core\python\eager\execute.py", line 67, in quick_execute
    six.raise_from(core._status_to_exception(e.code, message), None)
  File "<string>", line 3, in raise_from
tensorflow.python.framework.errors_impl.UnimplementedError:  Cast double to string is not supported
	 [[node Cast (defined at /PyCharmProjects/datascience-phd-automl/autokeras_test.py:25) ]] [Op:__inference_distributed_function_5726]

Function call stack:
distributed_function

Expected Behavior

Create an unweighted model, with the hyperparameters find by Autokeras.

Setup Details

Include the details about the versions of:

• OS type and version: Windows 10
• Python: 3.7.6
• autokeras: 1.0.2
• keras-tuner: 1.0.1
• scikit-learn: 0.22
• numpy: 1.18.1
• pandas: 1.0.1
• tensorflow: 2.1.0

[StephenGoedhart]

Got the exact same issue.

...
network = ak.StructuredDataClassifier(max_trials=1, num_classes=2) #1 trial to speed the process up for testing purposes
network.fit(x_train, y_train, epochs=1) #1  epoch to speed the process up for testing purposes

network.evaluate(x_test, y_test) #works fine

model = network.export_model()
model.save("model_autokeras.h5")

loaded_model = load_model("./model_autokeras.h5", custom_objects=ak.CUSTOM_OBJECTS)
loaded_model.evaluate(x_test, y_test) #UnimplementedError: Cast double to string is not supported

[Jacobsjj2]

I currently have the same issue. The model seems to work just fine when not exported, but the loaded model complains of casting involving strings and floats - neither of which are present in my training data after checking.