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Installation Instructions

PlaidML supports Ubuntu* Linux, macOS* and Microsoft Windows* operating systems.

Ubuntu Linux

If necessary, install Python's 'pip tool. OpenCL is also required.

sudo add-apt-repository universe && sudo apt update
sudo apt install python3-pip
sudo apt install clinfo

Run clinfo, and if it reports "Number of platforms" == 0, you can install a driver (GPU) or enable a CPU via one of these options:

  • Nvidia -- For Nvidia GPUs, run:

    sudo add-apt-repository ppa:graphics-drivers/ppa && sudo apt update
sudo apt install nvidia-modprobe nvidia-384 nvidia-opencl-icd-384 libcuda1-384

  • AMD -- For AMD graphics cards, download the AMDGPU PRO driver and follow the instructions provided by AMD for the chip.

  • Intel® Xeon® Processors OR Intel® Core™ Processors -- In lieu of installing specific drivers, you can install nGraph with pip, or you can build the nGraph Library with the cmake flag `-DNGRAPH_PLAIDML_ENABLE=TRUE.

Python

Although PlaidML can be run with Python2, we recommend Python3, as well as judicious use of a Virtualenv. To create one just for using PlaidML:

python3 -m venv plaidml-venv
source plaidml-venv/bin/activate

Keras

There are two ways to get Keras working on your system:

  1. Isolate it to your venv as follows:

    pip install -U plaidml-keras

  2. Alternatively, install the PlaidML wheels system-wide with:

    sudo -H pip install -U plaidml-keras

Finally, set up PlaidML to use a preferred computing device:

plaidml-setup

You can test the installation by running MobileNet in plaidbench. Remember to use sudo -H if you're working outside of a virtual environment.

pip install plaidml-keras plaidbench
plaidbench keras mobilenet

You can adapt any Keras code by using the PlaidML backend instead of the TensorFlow*, CNTK*, or Theano* backend that you'd normally use; simply change the Keras backend to plaidml.keras.backend. You can do this by modifying ~/.keras/keras.json so that the backend line reads "backend": "plaidml.keras.backend" If this file does not exist, see the Backend instructions for Keras. If you don't need anything special in your keras settings, you can set the ~/.keras/keras.json as follows:

{
    "epsilon": 1e-07,
    "floatx": "float32",
    "image_data_format": "channels_last",
    "backend": "plaidml.keras.backend"
 }

Another option is to globally set the KERAS_BACKEND environment variable to :envvar:`plaidml.keras.backend`.

A monkey-patch technique involving plaidml.keras.install_backend() may still work, but should be considered deprecated in favor of the above methods.

macOS

A computer listed on Apple's compatibility list with support for OpenCL 1.2 is required; those from 2011 and later usually fit this requirement.

Python

Although PlaidML can be run with Python2, we recommend Python3, as well as judicious use of a Virtualenv. To create one just for using PlaidML:

python3 -m venv plaidml-venv
source plaidml-venv/bin/activate

Keras

To install PlaidML with Keras, run the following:

pip install -U plaidml-keras

Finally, set up PlaidML to use a preferred computing device:

plaidml-setup

PlaidML should now be installed! You can test the installation by running MobileNet in plaidbench.

pip install plaidml-keras plaidbench
plaidbench keras mobilenet

Windows

These instructions assume Windows 10 without Python installed; adapt accordingly.

  1. First install :command:`Chocolatey` by starting an Administrator PowerShell and running:

    Set-ExecutionPolicy Bypass -Scope Process -Force; iex ((New-Object System.Net.WebClient).DownloadString('https://chocolatey.org/install.ps1'))

  2. You'll likely need to reboot your shell at this point.

  3. Install Python:

    choco install -y python git vcredist2015

  4. Switch to an unprivileged PowerShell to install and set up PlaidML with Keras

    pip install -U plaidml-keras
plaidml-setup

PlaidML should now be installed! You can test the installation by running MobileNet in plaidbench.

pip install plaidml-keras plaidbench
plaidbench keras mobilenet