import tensorflow as tf

        tf.logging.info('Starting a training cycle.')
        fashionAI.train(input_fn=lambda : input_pipeline(True, model_scope, epochs_per_eval), hooks=[logging_hook], max_steps=(steps_per_epoch*train_epochs))

        tf.logging.info('Starting to evaluate.')
        eval_results = fashionAI.evaluate(input_fn=lambda : input_pipeline(False, model_scope, 1))
        tf.logging.info(eval_results)
    tf.logging.info('Finished model {}.'.format(model_scope))

def main(_):
    # Using the Winograd non-fused algorithms provides a small performance boost.
