I wanted to use my GPU instead of CPU in Keras, after knowing that it supports CUDA, for a simple deep learning example training, so I had to do some search on how to set it up and ended with this summary:
Pre requisites :
1- Anaconda installed
2- setup Nividia CUDA 9.0 https://developer.nvidia.com/cuda-90-download-archive
3- setup Nividia cuDNN 7 (for CUDA 9.0) https://developer.nvidia.com/rdp/cudnn-download
0) run Anaconda Prompt
1) install conda packages
conda create --name tf-gpu-keras-p35 python=3.5 pip
conda install jupyter
conda install scipy
conda install scikit-learn
conda install pandas
pip install tensorflow-gpu
pip install keras
The following didn't work for me:
(didn't work with keras, keras installed tensorflow 1.1.0) keras keeps overriding the tensorflow-gpu
you get empty tensorflow module
conda install -c conda-forge keras
conda install -c conda-forge keras-gpu
conda install -c conda-forge tensorflow
conda install -c anaconda tensorflow-gpu
2) Set keras to use tensorflow backend, in case it uses theano (default)
go to Anaconda3/envs/<env name>/etc/activate.d/keras_activate.bat
go to <User home directory>\.keras\keras.json and change to tensorflow
3) run jupyter:
Monday, August 6, 2018
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