[Tensorflow] Correct way to write summary when using multiple graphs

https://www.tensorflow.org/programmers_guide/summaries_and_tensorboard
This official sample illustrates how to write summary of tensorflow.
But when you're using more then two graphs, you should provide graph key to specify which tensor goes into which graph, like:

	import tensorflow as tf

	class Net:
	def __init__(self, session, name, multiplier):
	self.session = session
	self.name = name
	with tf.variable_scope(name):
	self.x1 = tf.placeholder(tf.int32)
	# Don't do this
	# tf.summary.histogram('in', self.x1)

	# Do this
	# Add summary to collection
	tf.summary.histogram('in', self.x1, collections=[self.name])
	a1 = tf.constant(multiplier)

	self.y1 = tf.multiply(self.x1, a1)
	tf.summary.histogram('out', self.y1)

	def __enter__(self):
	self._prepare_log_dir()
	# Don't do this
	# self.merged_summery = tf.summary.merge_all()

	# Do this
	# Collect necessary summaries only by specifying collection key
	self.merged_summery = tf.summary.merge_all(key=self.name)
	self.train_writer = tf.summary.FileWriter(self.name, self.session.graph)

	def __exit__(self, exception_type, exception_value, traceback):
	self.train_writer.close()

	def predict(self, x):
	result, _ = sess.run([self.y1, self.merged_summery], feed_dict={self.x1: x})
	return result

	def _prepare_log_dir(self):
	if tf.gfile.Exists(self.name):
	tf.gfile.DeleteRecursively(self.name)
	tf.gfile.MakeDirs(self.name)

	with tf.Session() as sess:
	net1 = Net(sess, 'graph-1', 2)
	net2 = Net(sess, 'graph-2', 3)

	with net1, net2:
	tf.global_variables_initializer().run()
	print(net1.predict(3))
	print(net2.predict(3))

Music/Computer