import tensorflow as tf

#  multiple devices (executors) in TensorFlow.

import tensorflow as tf
from tensorflow.python.framework import ops
ops.reset_default_graph()

# To find out where placement occurs, set 'log_device_placement'
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))

a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
c = tf.matmul(a, b)

# Runs the op.
print(sess.run(c))


# If we load a graph and want device placement to be forgotten,
#  we set a parameter in our session:
config = tf.ConfigProto()
