I am currently doing a project on deep learning for my masters degree. I wanted to install keras library, so when I started installing Theano and tensorflow i saw that i hav
You can install and use keras without cuda, but you can't get gpu accelerating with intel hd graphics.
If you use Theano as keras' backend, first install Theano:
# for python2
pip install theano
# for python3
pip3 install theano
Then set ~/.theanorc file like this:
[global]
floatX = float32
device = cpu
allow_gc = True
[blas]
ldflags = -lopenblas
If you use TensorFlow as keras' backend, just install the CPU version of TensorFlow.
# for python2.7
pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.0-cp27-none-linux_x86_64.whl
# for python3.4
pip3 install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.0-cp34-cp34m-linux_x86_64.whl
# for python3.5
pip3 install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.0-cp35-cp35m-linux_x86_64.whl
Then install keras:
# for python2
pip install keras
# for python3
pip3 install keras
Edit: As of now, you can directly use OpenCL based clDNN (https://github.com/01org/clDNN) instead of using OpenVX, in order to perform Deep Learning inference on Intel Graphics. You will have to do the training on a powerful GPU like Nvidia or AMD and use the pre-trained model and use it in clDNN.
You can start using Intel's Computer Vision SDK (https://software.intel.com/en-us/computer-vision-sdk) in order to write Deep Learning Applications using OpenCV or OpenVX.
OpenVX (https://www.khronos.org/openvx/) programming model allows you to write simple Neural Network pipelines using the following SPEC (https://www.khronos.org/registry/OpenVX/extensions/neural_network/html/)
Alternatively you can use Model Optimizer that converts Caffe/TensorFlow model into OpenVX, and you can accelerate the OpenVX Neural Network graph on Intel Integrated HD Graphics.
Hope it helps.
Their is a PlaidML with that you train deep learning model on Intel and AMD gpu.