关于tensorflow入门代码

import tensorflow as tfimport numpy as np# create datax_data = np.random.rand(100).astype(np.float32)y_date = x_data*0.1+0.3# create tensorflow struction startWeights = tf.Variable(tf.random_normal([1],-1.0,1.0))biases = tf.Variable(tf.zeros(1))y = Weights*x_data + biasesloss = tf.reduce_mean(tf.square(y-y_date))optimizer = tf.train.GradientDescentOptimizer(0.5)train = optimizer.minimize(loss)init = tf.initialize_all_variables()# create tensorflow struction end#  create sessionwith tf.Session() as sess:    sess.run(init)    for step in range(201):        sess.run(train)        if step % 20 == 0:            print(step,sess.run(Weights),sess.run(biases))