Installation Instructions¶
PlaidML supports Ubuntu, macOS , and Microsoft Windows operating systems.
If necessary, install Python’s pip tool. OpenCL 1.2 or greater is alsorequired.
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:
Isolate it to your venv as follows:
pip install -U plaidml-keras
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 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.
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
These instructions assume Windows 10 without Python installed; adapt accordingly.
First install 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'))
You’ll likely need to reboot your shell at this point.
Install Python:
choco install -y python git vcredist2015
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