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import os
from keras.datasets import mnist
from autokeras import ImageClassifier
from autokeras.utils import pickle_from_file
# Customer temp dir by your own
TEMP_DIR = '/tmp/autokeras_U8KEOQ'
model_file_name = os.path.join(TEMP_DIR, 'test_autokeras_model.pkl')
if __name__ == '__main__':
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train = x_train.reshape(x_train.shape + (1,))
x_test = x_test.reshape(x_test.shape + (1,))
clf = ImageClassifier(verbose=True, augment=False, path=TEMP_DIR, resume=True)
clf.fit(x_train, y_train, time_limit=30 * 60)
clf.final_fit(x_train, y_train, x_test, y_test)
clf.export_autokeras_model(model_file_name)
model = pickle_from_file(model_file_name)
results = model.evaluate(x_test, y_test)
print(results)
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