tensorflow-gpu-exacloud/gpu-tutorial.py at master · schaugf/tensorflow-gpu-exacloud · GitHub

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import tensorflow as tf

print('running on default hardware...')

# creates a graph.

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)

# Creates a session with log_device_placement set to True.

sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))

# Runs the op.

print(sess.run(c))

print('running on gpu hardware...')

# Creates a graph.

with tf.device('/gpu:0'):
  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)

# Creates a session with log_device_placement set to True.

sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))

# Runs the op

print(sess.run(c))