def provide_input(self) -> List[tf.Tensor]: with tf.name_scope('loading'): training_data = get_data_from_tfrecord("./data/train.tfrecord", self.BATCH_SIZE) with tf.name_scope('training'): parameters = self.build_training_graph(training_data) return parameters
def provide_input(self) -> List[tf.Tensor]: with tf.name_scope('loading'): prediction_input, expected_result = get_data_from_tfrecord("./data/test.tfrecord", self.BATCH_SIZE).get_next() with tf.name_scope('pre-processing'): prediction_input = tf.reshape(prediction_input, shape=(self.BATCH_SIZE, 1, 28, 28)) expected_result = tf.reshape(expected_result, shape=(self.BATCH_SIZE,)) return [prediction_input, expected_result]