Last active
September 30, 2017 16:55
-
-
Save aferral/55a9849018c94b7c2818bc11e03059b1 to your computer and use it in GitHub Desktop.
Test tensorflow and gpu
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import sys | |
import numpy as np | |
import tensorflow as tf | |
from datetime import datetime | |
device_name = sys.argv[1] # Choose device from cmd line. Options: gpu or cpu | |
shape = (int(sys.argv[2]), int(sys.argv[2])) | |
if device_name == "gpu": | |
device_name = "/gpu:0" | |
else: | |
device_name = "/cpu:0" | |
with tf.device(device_name): | |
random_matrix = tf.random_uniform(shape=shape, minval=0, maxval=1) | |
dot_operation = tf.matmul(random_matrix, tf.transpose(random_matrix)) | |
sum_operation = tf.reduce_sum(dot_operation) | |
startTime = datetime.now() | |
with tf.Session(config=tf.ConfigProto(log_device_placement=True)) as session: | |
result = session.run(sum_operation) | |
print(result) | |
# It can be hard to see the results on the terminal with lots of output -- add some newlines to improve readability. | |
print("\n" * 5) | |
print("Shape:", shape, "Device:", device_name) | |
print("Time taken:", datetime.now() - startTime) | |
print("\n" * 5) |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment