How do I use TensorFlow GPU?

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:

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 4:

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 5:

I tried following the above tutorial. Thing is tensorflow changes a lot and so do the NVIDIA versions needed for running on a GPU. The next issue is that your driver version determines your toolkit version etc. As of today this information about the software requirements should shed some light on how they interplay:

NVIDIA® GPU drivers —CUDA 9.0 requires 384.x or higher.
CUDA® Toolkit —TensorFlow supports CUDA 9.0.
CUPTI ships with the CUDA Toolkit.
cuDNN SDK (>= 7.2) Note: Make sure your GPU has compute compatibility >3.0
(Optional) NCCL 2.2 for multiple GPU support.
(Optional) TensorRT 4.0 to improve latency and throughput for inference on some models.

And here you'll find the up-to-date requirements stated by tensorflow (which will hopefully be updated by them on a regular basis).