tensorflow starter

tf.py

import tensorflow as tf
import uuid

x = tf.Variable(tf.random_normal(shape=[1,1], mean=5, stddev=2))
y = tf.sin(x) + tf.sin(x**2/2) - tf.abs(x)

optimizer = tf.train.RMSPropOptimizer(0.001).minimize(-y)
init = tf.global_variables_initializer()

tf.summary.scalar("x-val", tf.reduce_mean(x))
tf.summary.scalar("y-val", tf.reduce_mean(y))
merged_summary_op = tf.summary.merge_all()

with tf.Session() as sess:
    sess.run(init)
    uniq_id = "/tmp/tensorboard-gradient/" + uuid.uuid1().__str__()[:6]
    summary_writer = tf.summary.FileWriter(uniq_id, graph=tf.get_default_graph())
    for step in range(3000):
        _, val, summary = sess.run([optimizer, y, merged_summary_op])
        if step % 5 == 0:
            print("step: {}, value: {}".format(step, val[0][0]))
            summary_writer.add_summary(summary, step)