Tensorflow not running on GPU

Question

I have aldready spent a considerable of time digging around on stack overflow and else looking for the answer, but couldn't find anything

Hi all,

I am running Tensorflow with Keras on top. I am 90% sure I installed Tensorflow GPU, is there any way to check which install I did?

I was trying to do run some CNN models from Jupyter notebook and I noticed that Keras was running the model on the CPU (checked task manager, CPU was at 100%).

I tried running this code from the tensorflow website:

# 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)) 

And this is what I got:

MatMul: (MatMul): /job:localhost/replica:0/task:0/cpu:0 2017-06-29 17:09:38.783183: I c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\common_runtime\simple_placer.cc:847] MatMul: (MatMul)/job:localhost/replica:0/task:0/cpu:0 b: (Const): /job:localhost/replica:0/task:0/cpu:0 2017-06-29 17:09:38.784779: I c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\common_runtime\simple_placer.cc:847] b: (Const)/job:localhost/replica:0/task:0/cpu:0 a: (Const): /job:localhost/replica:0/task:0/cpu:0 2017-06-29 17:09:38.786128: I c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\common_runtime\simple_placer.cc:847] a: (Const)/job:localhost/replica:0/task:0/cpu:0 [[ 22.  28.]  [ 49.  64.]] 

Which to me shows I am running on my CPU, for some reason.

I have a GTX1050 (driver version 382.53), I installed CUDA, and Cudnn, and tensorflow installed without any problems. I installed Visual Studio 2015 as well since it was listed as a compatible version.

I remember CUDA mentioning something about an incompatible driver being installed, but if I recall correctly CUDA should have installed its own driver.

Edit: I ran theses commands to list the available devices

from tensorflow.python.client import device_lib print(device_lib.list_local_devices()) 

and this is what I get

[name: "/cpu:0" device_type: "CPU" memory_limit: 268435456 locality { } incarnation: 14922788031522107450 ] 

and a whole lot of warnings like this

2017-06-29 17:32:45.401429: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations. 

Edit 2

Tried running

pip3 install --upgrade tensorflow-gpu 

and I get

Requirement already up-to-date: tensorflow-gpu in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages Requirement already up-to-date: markdown==2.2.0 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu) Requirement already up-to-date: html5lib==0.9999999 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu) Requirement already up-to-date: werkzeug>=0.11.10 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu) Requirement already up-to-date: wheel>=0.26 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu) Requirement already up-to-date: bleach==1.5.0 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu) Requirement already up-to-date: six>=1.10.0 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu) Requirement already up-to-date: protobuf>=3.2.0 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu) Requirement already up-to-date: backports.weakref==1.0rc1 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu) Requirement already up-to-date: numpy>=1.11.0 in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from tensorflow-gpu) Requirement already up-to-date: setuptools in c:\users\xxx\appdata\local\programs\python\python35\lib\site-packages (from protobuf>=3.2.0->tensorflow-gpu) 

Solved: Check comments for solution. Thanks to all who helped!

I am new to this, so any help is greatly appreciated! Thank you.

Answer 1

To check which devices are available to TensorFlow you can use this and see if the GPU cards are available:

from tensorflow.python.client import device_lib print(device_lib.list_local_devices()) 

Edit Also, you should see this kind of logs if you use TensorFlow Cuda version :

I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcublas.so.*.* locally I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcudnn.so.*.*  locally I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcufft.so.*.*  locally