TensorBoard

In [1]:

    

import tensorflow as tf


    

In [2]:

    

with tf.name_scope("OPERATION_A"):
    a = tf.add(1, 2, name = "First_add")
    a1 = tf.add(100, 200, name = 'a_add')
    a2 = tf.multiply(a, a1)
    

with tf.name_scope("OPERATION_B"):
    b = tf.add(3,4, name = 'Second_add')
    b1 = tf.add(300,400,name = 'b_add')
    b2 = tf.multiply(b, b1)

c = tf.multiply(a2, b2, name = 'final_result')


    

In [3]:

    

with tf.Session() as sess:
    writer = tf.summary.FileWriter("./output", sess.graph)
    print(sess.run(c))
    writer.close()


    

    




4410000

In [4]:

    

k = tf.placeholder(tf.float32)

# Make a normal distribution, with a shifting mean
mean_moving_normal = tf.random_normal(shape = [1000], 
                                      mean = (5 * k), 
                                      stddev = 1)
# Record that distribution into a histogram summary
tf.summary.histogram("normal/moving_mean", mean_moving_normal)

# Setup a session and summary writer
with tf.Session() as sess:
    writer = tf.summary.FileWriter("./tmp/histogram_example")

    summaries = tf.summary.merge_all()

    # Setup a loop and write the summaries to disk
    N = 400
    for step in range(N):
        
        k_val = step/float(N)
        summ = sess.run(summaries, 
                        feed_dict = {k: k_val})
        writer.add_summary(summ, 
                           global_step = step)
        
    writer.close()