def fit(self, train_set, train_labels, validation_set=None, validation_labels=None, mode='supervised'):

        print('Starting ' + mode + ' finetuning...')

        with tf.Session() as self.tf_session:
            self._initialize_tf_utilities_and_ops()
            self._train_model(train_set, train_labels, validation_set, validation_labels, mode)
            self.tf_saver.save(self.tf_session, self.model_path)
Create a new floating ip from attributes
dataset/ETHPy150Open blackecho/Deep-Learning-TensorFlow/models/autoencoder_models/stacked_denoising_autoencoder.py/StackedDenoisingAutoencoder.fit--crossover with--dataset/ETHPy150Open openstack/python-openstacksdk/openstack/network/v2/_proxy.py/Proxy.create_ip