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Tensorflow 0.8 on AWS GPU instance installati
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# Install build tools | |
sudo apt-get update | |
sudo apt-get install -y build-essential git python-pip libfreetype6-dev libxft-dev libncurses-dev libopenblas-dev gfortran python3-matplotlib libblas-dev liblapack-dev libatlas-base-dev python3-dev python3-pydot linux-headers-generic linux-image-extra-virtual unzip python3-numpy swig python3-pandas python-sklearn unzip python3-pip | |
sudo pip3 install -U pip | |
sudo pip3 install -U ipython jupyter scikit-learn | |
# Install CUDA 7 | |
# wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1410/x86_64/cuda-repo-ubuntu1410_7.0-28_amd64.deb | |
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1504/x86_64/cuda-repo-ubuntu1504_7.5-18_amd64.deb | |
sudo dpkg -i cuda-repo-ubuntu1504_7.5-18_amd64.deb && rm cuda-repo-ubuntu1504_7.5-18_amd64.deb | |
sudo apt-get update | |
sudo apt-get install -y cuda | |
# Install cuDNN | |
# You get the CUDNN_URL by logging into your nivida account and downloading cuDNN | |
# https://developer.nvidia.com/rdp/cudnn-archive (cudnn 7.0) | |
export CUDNN_URL="" | |
wget $CUDNN_URL -O cudnn-7.0-linux-x64-v3.0-prod.tgz | |
tar -zxf cudnn-7.0-linux-x64-v3.0-prod.tgz && rm cudnn-7.0-linux-x64-v3.0-prod.tgz | |
sudo cp ./cuda/lib64/* /usr/local/cuda/lib64/ | |
sudo cp ./cuda/include/* /usr/local/cuda/include/ | |
# Reboot for CUDA | |
sudo reboot | |
# Set CUDA env vars | |
export CUDA_HOME=/usr/local/cuda | |
export CUDA_ROOT=$CUDA_HOME | |
export PATH=$PATH:$CUDA_ROOT/bin | |
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_ROOT/lib64 | |
# Install Tensorflow | |
sudo pip3 install --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.8.0-cp34-cp34m-linux_x86_64.whl |
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