text: 
  # coding:utf-8
  
  import tensorflow as tf
  import numpy as np
  
  x_data = np.random.rand(100).astype(np.float32)
  
  y_data = x_data*0.1 + 0.3
  
  # create tensorflow structure
  Weights = tf.Variable(tf.random_uniform([1],-1.0,1.0))
  biases = tf.Variable(tf.zeros(1))
  
  y = Weights * x_data + biases
  
  loss = tf.reduce_mean(tf.square(y-y_data))
  optimizer = tf.train.GradientDescentOptimizer(0.5)
  train = optimizer.minimize(loss)
  
  init = tf.initialize_all_variables()
  
  sess = tf.Session()
  
  sess.run(init)
  
  for step in range(200):
      sess.run(train)
      if step % 20 ==0:
          print(step, sess.run(Weights),sess.run(biases))
  