CNN中的关于mini_batch的一些疑问？

最新推荐文章于 2025-04-21 22:43:22 发布

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最新推荐文章于 2025-04-21 22:43:22 发布 · 711 阅读

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N_CLASSES=2#2个输出神经元 [1,0],[0,1]猫或者狗的概率
IMG_W=208#重新定义图片的尺寸
IMG_H=208
BATCH_SIZE=32#每批数据的大小
CAPACITY=256
MAX_STEP=12000#训练的步数
learning_rate=0.0001#学习率

saver=tf.train.Saver()

sess.run(tf.global_variables_initializer())
coord=tf.train.Coordinator()
threads=tf.train.start_queue_runners(sess=sess,coord=coord)

try:
    for step in np.arange(MAX_STEP):
        if coord.should_stop():
            break
        _,tra_loss,tra_acc=sess.run([train_op,train_loss,train_acc])

        if step%50==0:
            print('Step %d, train loss = %.2f, train accuracy = %.2f%%' % (step, tra_loss, tra_acc * 100.0))
            summary_str=sess.run(summary_op)
            train_writer.add_summary(summary_str,step)

        if step%2000==0 or (step+1)==MAX_STEP:
            checkpoint_path=os.path.join(logs_train_dir,'model.ckpt')
            saver.save(sess,checkpoint_path,global_step=step)

except tf.errors.OutOfRangeError:
    print('Done training -- epoch limit reached')
finally:
    coo