gd_with_data.py

import tensorflow as tf

x_1 = tf.placeholder(tf.float32)
x_2 = tf.placeholder(tf.float32)
x_3 = tf.placeholder(tf.float32)

x = tf.Variable(2, name='x', dtype=tf.float32)
log_x = tf.log(x)
result = (x_1 + x_2 + x_3) * tf.square(log_x)

optimizer = tf.train.GradientDescentOptimizer(0.5)
train = optimizer.minimize(result)

init = tf.initialize_all_variables()

def optimize():
  with tf.Session() as session:
    session.run(init)
    feed_dict = {
        x_1: 1.0,
        x_2: -1.0,
        x_3: 1.0
      }
    print("starting at", "x:", session.run(x, feed_dict=feed_dict), "log(x)^2:", session.run(result, feed_dict=feed_dict))
    for step in range(10):  
      session.run(train, feed_dict=feed_dict)
      print(step, "x:", session.run(x, feed_dict=feed_dict), "log(x)^2:", session.run(result, feed_dict=feed_dict))
        

optimize()