import tensorflow as tf


    import numpy as np
    x_input = np.array([[1,2,3,4,5]])
    y_input = np.array([[10]])


    x = tf.placeholder(tf.float32, [None, 5])
    y = tf.placeholder(tf.float32, [None, 1])


    W = tf.Variable(tf.zeros([5, 1]))
    b = tf.Variable(tf.zeros([1]))
    y_pred = tf.matmul(x, W)+b


    loss = tf.reduce_sum(tf.pow((y-y_pred), 2))


    train = tf.train.GradientDescentOptimizer(0.0001).minimize(loss)


    init = tf.global_variables_initializer()


    sess = tf.Session()
    sess.run(init)
    for i in range(10):
        feed_dict = {x: x_input, y: y_input}
        sess.run(train, feed_dict=feed_dict)


    sess = tf.Session()
    sess.run(init)
    for i in range(10):
        feed_dict = {x: x_input, y: y_input}
        _, loss_value = sess.run([train, loss], feed_dict=feed_dict)
        print(loss_value)

100.0
97.77255
95.594696
93.46538
91.38347
89.34794
87.357765
85.41191
83.5094
81.64925