How do I use TensorFlow GPU?

Question

How do I use TensorFlow GPU version instead of CPU version in Python 3.6 x64?

import tensorflow as tf

Python is using my CPU for calculations.
I can notice it because I have an error:

Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2

I have installed tensorflow and tensorflow-gpu.

How do I switch to GPU version?

Solution 1

Follow this tutorial Tensorflow GPU I did it and it works perfect.

Attention! - install version 9.0! newer version is not supported by Tensorflow-gpu

Steps:

1. Uninstall your old tensorflow
2. Install tensorflow-gpu pip install tensorflow-gpu
3. Install Nvidia Graphics Card & Drivers (you probably already have)
4. Download & Install CUDA
5. Download & Install cuDNN
6. Verify by simple program

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

Solution 2

The 'new' way to install tensorflow GPU if you have Nvidia, is with Anaconda. Works on Windows too. With 1 line.

conda create --name tf_gpu tensorflow-gpu 

This is a shortcut for 3 commands, which you can execute separately if you want or if you already have a conda environment and do not need to create one.

1. Create an anaconda environment conda create --name tf_gpu

2. Activate the environment conda activate tf_gpu

3. Install tensorflow-GPU conda install tensorflow-gpu

You can use the conda environment.

Solution 3

Follow the steps in the latest version of the documentation. Note: GPU and CPU functionality is now combined in a single tensorflow package

pip install tensorflow

# OLDER VERSIONS pip install tensorflow-gpu

https://www.tensorflow.org/install/gpu

This is a great guide for installing drivers and CUDA if needed: https://www.quantstart.com/articles/installing-tensorflow-22-on-ubuntu-1804-with-an-nvidia-gpu/

Solution 4

First you need to install tensorflow-gpu, because this package is responsible for gpu computations. Also remember to run your code with environment variable CUDA_VISIBLE_DEVICES = 0 (or if you have multiple gpus, put their indices with comma). There might be some issues related to using gpu. if your tensorflow does not use gpu anyway, try this

Solution 5

For conda environment.

• conda search tensorflow to search the available versions of tensorflow. The ones that have mkl are optimized for CPU. You can choose the ones with gpu.
• Then check the version of your cuda using nvcc --version and find the proper version of tensorflow in this page, according to your version of cuda.
• For example, for cuda/10.1,and python3.8, you can use
  • conda install tensorflow=2.2.0=gpu_py38hb782248_0

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Comments

[Jorge Leitao]

Have you tried uninstalling tensorflow and just keep the tensorflow-gpu installed?

[CtrlAltF2]

Try downloading CUDA and installing the GPU version.

[iacolippo]

That's just a warning, if you have an NVIDIA GPU, Tensorflow-gpu will automatically use that. To know more and how to disable the warning: stackoverflow.com/a/47227886/4892874 To check that you're using the GPU: sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))

[Mohan Radhakrishnan]

Are you using Anaconda ? if you are you have to switch the interpreter of the particular environment in PyCharm.

[Guruku]

Device mapping: no known devices. I do not use Anaconda

[Mathieu]

What is your GPU?

[Guruku]

NVIDIA 940mx, it is relative new Nvidia card. @JorgeLeitão yes, then I have no TensorFlow

[Guruku]

So, CUDA 9.2 can be the problem? Should I install 9.0 then? Yesterday I had an error after installing CUDA 9.2. It said that I need DLL from CUDA 9.0 and I knew it was using GPU version, today all the time I see the error about CPU, so it is using CPU. I will try it step by step, thanks.

[Ashwel]

Yea, i had same problem about 2 month ago. I tried CUDA 9.1 and Tensorflow doesn't support it..Then i uninstall everything and repeat all steps with CUDA 9.0 and now it works without problems.

[Guruku]

Maybe I should ask in another question, but is tensorflow on GPU is faster than CPU at your PC? I tried with linear regression model and for 10000 epos and step 0.01 my CPU can calculate it in 13 second and when I use GPU it takes 39 second.

[Ashwel]

Ofc i have CPU i7 8700k and GPU nVidia GTX 1060 STRING 6GB and on GPU is faster 20 times aproximate.

[Paul Bendevis]

Note that newer versions of tensorflow combine the cpu and gpu packages together into a single package. tensorflow.org/install/gpu

[dato nefaridze]

I did the same, and does tensors need to be uploaded on gpu, like they need in pytorch?

[Rodrigo Hjort]

In 2: conda activate tf_gpu