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

User · Answer

Strangely  even though the tensorflow website 1 mentions that CUDA 10 1 is compatible with tensorflow-gpu-1 13 1  it doesn t work so far  tensorflow-gpu gets installed properly though but it throws out weird errors when running   So far  the best configuration to run tensorflow with GPU is CUDA 9 0 with tensorflow gpu-1 12 0 under python3 6   Following this configuration with the steps mentioned in https   stackoverflow com a 51307381 2562870  the answer above   worked for me

User · Answer

Uninstall tensorflow and install only tensorflow-gpu  this should be sufficient  By default  this should run on the GPU and not the CPU  However  further you can do the following to specify which GPU you want it to run on   If you have an nvidia GPU  find out your GPU id using the command nvidia-smi on the terminal  After that  add these lines in your script   os environ  CUDA DEVICE ORDER      PCI BUS ID  os environ  CUDA VISIBLE DEVICES      GPU ID from earlier  config   tf ConfigProto   sess   tf Session config config    For the functions where you wish to use GPUs  write something like the following   with tf device tf DeviceSpec device type  GPU   device index gpu id

User · Answer

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   gt   7 2  Note  Make sure your GPU has compute compatibility  gt 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

User · Answer

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    Uninstall your old tensorflow Install tensorflow-gpu pip install tensorflow-gpu Install Nvidia Graphics Card  amp  Drivers  you probably already have  Download  amp  Install CUDA Download  amp  Install cuDNN Verify by simple program   from tensorflow python client import device lib   print device lib list local devices

User · Answer

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

User · Answer

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   Create an anaconda environment conda create --name tf gpu  Activate the environment activate tf gpu  Install tensorflow-GPU conda install tensorflow-gpu   You can use the conda environment

User · Answer

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

[python] How do I use TensorFlow GPU?

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