import tensorflow as tf

            m.ph.train_images: np.zeros((1, w, h, in_ch)),
            m.ph.train_classes: np.zeros((1,)),
            m.ph.pred_images: np.zeros((1, w, h, in_ch)),
            m.ph.pred_classes: np.zeros((1,))
        })

    def _make_session(self):
        config = tf.ConfigProto(allow_soft_placement=True)
        config.gpu_options.allow_growth = True
        sess = tf.Session(config=config)
        return sess

    def _feed_dataset_to_model(self, images, classes=None, is_train=False):
        m = self._model
        utils.logger.log('Feeding dataset to model...')

        # Mock classes if required
        classes = classes or [0 for _ in range(len(images))]
