[Solved] TensorFlow with GPU in Anaconda env [Ubuntu 16.04 + CUDA 7.5 + cuDNN]

Accelerated Computing CUDA CUDA Setup and Installation
1

Install Driver from Xenial + ppa:
$ sudo add-apt-repository ppa:graphics-drivers/ppa
$ sudo apt-get update
$ sudo ubuntu-drivers autoinstall
$ sudo reboot

Software & Updates > Additional Drivers
Change from nvidia-364 (open source) to "Using NVIDIA - version 361.42 from nvidia-361 (proprietary)

Download the CUDA toolkit from

The toolkit runfile uses an older driver than we’ve installed above. So select “No” to driver.
$ chmod 755 cuda_7.5.18_linux.run
$ sudo ./cuda_7.5.18_linux.run --override

Download cuDNN 4 from

Extract. Rename the cuda directory as cudnn. We’ll keep cudnn separate from cuda.
$ mv cuda cudnn
$ sudo cp -r cudnn /usr/local

Create symlinks in /usr/local/cuda/lib64 to /usr/local/cudnn/lib64
$ sudo ln -s /usr/local/cuda/lib64/libcudnn.so /usr/local/cudnn/lib64/libcudnn.so
$ sudo ln -s /usr/local/cuda/lib64/libcudnn.so.4 /usr/local/cudnn/lib64/libcudnn.so.4
$ sudo ln -s /usr/local/cuda/lib64/libcudnn.so.4.0.7 /usr/local/cudnn/lib64/libcudnn.so.4.0.7
$ sudo ln -s /usr/local/cuda/lib64/libcudnn_static.a /usr/local/cudnn/lib64/libcudnn_static.a

Set up ~/.bashrc
$ sudo nano ~/.bashrc
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cudnn/lib64
export CUDA_HOME=/usr/local/cuda
export PATH=/usr/local/cuda/bin:$PATH

Environment Variables:

$ sudo nano /etc/profile.d/cuda.sh
export PATH=$PATH:/usr/local/cuda/bin

$ sudo nano /etc/ld.so.conf.d/cuda.conf
/usr/local/cuda/lib64

$ sudo nano /etc/ld.so.conf.d/cudnn.conf
/usr/local/cudnn/lib64

$ sudo ldconfig
$ source ~/.bashrc

Force it to work with gcc 5:

$ sudo nano /usr/local/cuda/include/host_config.h
line: 115 comment out error
//#error – unsupported GNU version! gcc versions later than 4.9 are not supported!

Verify your driver & CUDA version and directory
$ nvidia-smi
$ nvcc -V
$ which nvcc

Download Anaconda - Either Python 2.7 or 3.5
https://www.continuum.io/downloads
$ bash Anaconda2-4.0.0-Linux-x86_64.sh

Create a tensorflow environment using Python 3.5:
$ conda create -n tensorflow python=3.5

Download tensorflow & rename the whl:
$ wget https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.8.0-cp34-cp34m-linux_x86_64.whl
$ mv tensorflow-0.8.0-cp34-cp34m-linux_x86_64.whl tensorflow-0.8.0-cp35-none-linux_x86_64.whl

Start the “tensorflow” env
$ source activate tensorflow
(tensorflow) $ pip install --ignore-installed --upgrade tensorflow-0.8.0-cp35-none-linux_x86_64.whl
To exit the env
(tensorflow) $ source deactivate

2

THANK YOU!! Finally managed to get it installed and running. Thanks so much!

3

I was able to use tensorflow with Ubuntu’s built-in CUDA packages.

  • Turn off Secure Boot (necessary to load NVIDIA driver in Ubuntu kernels 4.4.0-20 and up)
  • sudo apt-get install nvidia-cuda-dev libcupti-dev
  • Download CUDNN5 and copy the include files to /usr/include and the libraries to /usr/lib/x86_64-linux-gnu
  • Create symlinks to fool TensorFlow 
    sudo mkdir -p /usr/local/cuda/include
sudo mkdir -p /usr/local/cuda/lib64
sudo mkdir -p /usr/local/cuda/extras/CUPTI/include
sudo mkdir -p /usr/local/cuda/extras/CUPTI/lib64
sudo ln -s /usr/include/cuda.h /usr/local/cuda/include/cuda.h
sudo ln -s /usr/include/cublas.h /usr/local/cuda/include/cublas.h
sudo ln -s /usr/include/cudnn.h /usr/local/cuda/include/cudnn.h
sudo ln -s /usr/include/cupti.h /usr/local/cuda/extras/CUPTI/include/cupti.h
sudo ln -s /usr/lib/x86_64-linux-gnu/libcudart_static.a /usr/local/cuda/lib64/libcudart_static.a
sudo ln -s /usr/lib/x86_64-linux-gnu/libcublas.so /usr/local/cuda/lib64/libcublas.so
sudo ln -s /usr/lib/x86_64-linux-gnu/libcudart.so /usr/local/cuda/lib64/libcudart.so
sudo ln -s /usr/lib/x86_64-linux-gnu/libcudnn.so /usr/local/cuda/lib64/libcudnn.so
sudo ln -s /usr/lib/x86_64-linux-gnu/libcufft.so /usr/local/cuda/lib64/libcufft.so
sudo ln -s /usr/lib/x86_64-linux-gnu/libcupti.so /usr/local/cuda/extras/CUPTI/lib64/libcupti.so
  • Install TensorFlow with Anaconda as above or directly like this: 
    wget https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.8.0-cp34-cp34m-linux_x86_64.whl
mv tensorflow-0.8.0-cp34-cp34m-linux_x86_64.whl tensorflow-0.8.0-cp35-none-linux_x86_64.whl
sudo -H pip3 install --ignore-installed --upgrade tensorflow-0.8.0-cp35-none-linux_x86_64.whl