TensorFlow and ROS Kinetic with Python 2.7

TensorFlow and ROS Kinetic with Python 2.7

  1. Create a working directory $ mkdir ~/tf_ros && cd ~/tf_ros
  2. Download and Install an NVIDIA Driver >= 384.x (https://www.nvidia.co.jp/Download/index.aspx) We recommend RUN files, please check our other post on this topic.

  3. Download and Install CUDA 9.0 (https://developer.nvidia.com/cuda-90-download-archive)

  4. Download and Install CUDNN for CUDA 9.0 (https://developer.nvidia.com/rdp/cudnn-download; https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#installlinux)

  5. Download TensorFlow for Python 2.7 $ wget https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.10.1-cp27-none-linux_x86_64.whl

  6. Install Python VirtualEnv $ sudo apt-get install python-virtualenv

  7. Create Python 2.7 virtual environment. $ virtualenv --system-site-packages -p python2 p2tf_venv (p2tf_venv can be any name)

  8. Activate environment $ source p2tf_venv/bin/activate

  9. Install TensorFlow (p2_venv) $ pip install --upgrade tensorflow_gpu-1.10.1-cp27-none-linux_x86_64.whl

  10. Make sure you have in LD_LIBARY_PATH, the cuda 9 libraries and binaries.

$ export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH && export PATH=/usr/local/cuda/bin:$PATH