tfboard.py

import tensorflow as tf

with tf.name_scope("myvars"):
  a = tf.Variable(0.0, name="a")
  tf.summary.scalar('apple', a)
  b = tf.Variable(0.0, name="b")
  tf.summary.scalar('bananas', b)

training_epochs = 10
with tf.Session() as sess:
  merged = tf.summary.merge_all()
  train_writer = tf.summary.FileWriter('./train', sess.graph)

  sess.run(tf.global_variables_initializer())

  for epoch in range(training_epochs):
    a_op = a.assign_add(10)
    b_op = b.assign_add(100)
    _, _, summary = sess.run([a_op, b_op, merged])
    train_writer.add_summary(summary, epoch)