tensorflow常用基本操作

青旅半醒 2023-07-11 08:41 4阅读 0赞

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norm = tf.random_normal([2, 3], mean=-1, stddev=4)
    
    # Shuffle the first dimension of a tensor
    c = tf.constant([[1, 2], [3, 4], [5, 6]])
    shuff = tf.random_shuffle(c)
    
    # Each time we run these ops, different results are generated
    sess = tf.Session()
    print (sess.run(norm))
    print (sess.run(shuff))

![在这里插入图片描述][20200304202933322.png]

state = tf.Variable(0)
    new_value = tf.add(state, tf.constant(1))
    update = tf.assign(state, new_value)
    
    with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())
        print(sess.run(state))    
        for _ in range(3):
            sess.run(update)
            print(sess.run(state))

![在这里插入图片描述][20200304203000877.png]

#tf.train.Saver
    w = tf.Variable([[0.5,1.0]])
    x = tf.Variable([[2.0],[1.0]])
    y = tf.matmul(w, x)
    init_op = tf.global_variables_initializer()
    saver = tf.train.Saver()
    with tf.Session() as sess:
        sess.run(init_op)
    # Do some work with the model.
    # Save the variables to disk.
        save_path = saver.save(sess, "C://tensorflow//model//test")
        print ("Model saved in file: ", save_path)

import numpy as np
    a = np.zeros((3,3))
    ta = tf.convert_to_tensor(a)
    with tf.Session() as sess:
         print(sess.run(ta))

![在这里插入图片描述][20200304203043635.png]

input1 = tf.placeholder(tf.float32)
    input2 = tf.placeholder(tf.float32)
    output = tf.multiply(input1, input2)
    with tf.Session() as sess:
        print(sess.run([output], feed_dict={ input1:[7.], input2:[2.]}))

![在这里插入图片描述][2020030420310880.png]

[20200304202933322.png]: https://img-blog.csdnimg.cn/20200304202933322.png
[20200304203000877.png]: https://img-blog.csdnimg.cn/20200304203000877.png
[20200304203043635.png]: https://img-blog.csdnimg.cn/20200304203043635.png
[2020030420310880.png]: https://img-blog.csdnimg.cn/2020030420310880.png