神经网络模型的保存和读取

简略保存过程

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mode_path = "save/model.ckpt"
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#saver 保存模型
saver = tf.train.Saver()
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#保持模型的权重和偏移量
save_path = saver.save(sess, model_path)

读取模型

print "第二个session"
with tf.Session() as sess:
    sess.run(init)
    
    load_path = saver.restore(sess, model_path###例如 ./save/cnn_train.model-900###)
    for epoch in range(7):
        ...
        ...
        ...