<commit_before>#!/bin/bash

# Install latest Linux headers
sudo apt-get install -y linux-source linux-headers-`uname -r`

# Install CUDA 8.0 (note – don't use any other version)
wget https://developer.nvidia.com/compute/cuda/9.1/Prod/local_installers/cuda_9.1.85_387.26_linux
mv cuda_9.1.85_387.26_linux-run cuda_9.1.85_387.26_linux.run
chmod +x cuda_9.1.85_387.26_linux.run
./cuda_9.1.85_387.26_linux.run -extract=`pwd`/nvidia_installers
cd nvidia_installers
sudo ./NVIDIA-Linux-x86_64-387.26.run
sudo modprobe nvidia
sudo ./cuda-linux.9.1.85-23083092.run -silent
cd ..

# Install CUDNN 6.0 (note – don't use any other version)
wget https://s3.amazonaws.com/kaggle-stuff/cudnn-8.0-linux-x64-v6.0.tgz
tar -xzf cudnn-8.0-linux-x64-v6.0.tgz
sudo cp -P cuda/lib64/* /usr/local/cuda/lib64
sudo cp -P cuda/include/* /usr/local/cuda/include/

# Set up the CUDA home, path, and library path
echo 'export CUDA_HOME=/usr/local/cuda' >> ~/.bashrc
echo 'export PATH=$PATH:$CUDA_HOME/bin' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_HOME/lib64' >> ~/.bashrc

# Do some cleanup
sudo rm cuda_9.1.85_387.26_linux.run
sudo rm cudnn-8.0-linux-x64-v6.0.tgz
sudo rm -rf cuda
sudo rm -rf nvidia_installers

# Install tensorflow
sudo pip3 install --upgrade pip
sudo pip3 install tensorflow-gpu==1.5.0

# Install keras
sudo pip3 install keras
sudo pip3 install h5py

# Install PyTorch and PyJet
sudo pip3 install http://download.pytorch.org/whl/cu90/torch-0.3.0.post4-cp35-cp35m-linux_x86_64.whl
sudo pip3 install torchvision
git clone https://github.com/abhmul/PyJet
cd PyJet
sudo pip3 install -e .
cd ..<commit_msg>updated the cudnn version<commit_after>#!/bin/bash

# Install latest Linux headers
sudo apt-get install -y linux-source linux-headers-`uname -r`

# Install CUDA 8.0 (note – don't use any other version)
wget https://developer.nvidia.com/compute/cuda/9.1/Prod/local_installers/cuda_9.1.85_387.26_linux
mv cuda_9.1.85_387.26_linux-run cuda_9.1.85_387.26_linux.run
chmod +x cuda_9.1.85_387.26_linux.run
./cuda_9.1.85_387.26_linux.run -extract=`pwd`/nvidia_installers
cd nvidia_installers
sudo ./NVIDIA-Linux-x86_64-387.26.run
sudo modprobe nvidia
sudo ./cuda-linux.9.1.85-23083092.run -silent
cd ..

# Install CUDNN 6.0 (note – don't use any other version)
wget https://s3.amazonaws.com/kaggle-stuff/cudnn-9.1-linux-x64-v7.tgz
tar -xzf cudnn-9.1-linux-x64-v7.tgz
sudo cp -P cuda/lib64/* /usr/local/cuda/lib64
sudo cp -P cuda/include/* /usr/local/cuda/include/

# Set up the CUDA home, path, and library path
echo 'export CUDA_HOME=/usr/local/cuda' >> ~/.bashrc
echo 'export PATH=$PATH:$CUDA_HOME/bin' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_HOME/lib64' >> ~/.bashrc

# Do some cleanup
sudo rm cuda_9.1.85_387.26_linux.run
sudo rm cudnn-9.1-linux-x64-v7.tgz
sudo rm -rf cuda
sudo rm -rf nvidia_installers

# Install tensorflow
sudo pip3 install --upgrade pip
sudo pip3 install tensorflow-gpu==1.5.0

# Install keras
sudo pip3 install keras
sudo pip3 install h5py

# Install PyTorch and PyJet
sudo pip3 install http://download.pytorch.org/whl/cu90/torch-0.3.0.post4-cp35-cp35m-linux_x86_64.whl
sudo pip3 install torchvision
git clone https://github.com/abhmul/PyJet
cd PyJet
sudo pip3 install -e .
cd ..
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