- #INSTALL LATEST NVIDIA DRIVERS UBUNTU 14.04 HOW TO#
- #INSTALL LATEST NVIDIA DRIVERS UBUNTU 14.04 INSTALL#
- #INSTALL LATEST NVIDIA DRIVERS UBUNTU 14.04 DRIVER#
- #INSTALL LATEST NVIDIA DRIVERS UBUNTU 14.04 LICENSE#
- #INSTALL LATEST NVIDIA DRIVERS UBUNTU 14.04 DOWNLOAD#
Ted your system since these files were written. WARNING: One or more modprobe configuration files to disable Nouveau are already present at: /etc/modprobe.d/nf. > The distribution-provided pre-install script failed! Are you sure you want to continue? (Answer: Continue installation)
#INSTALL LATEST NVIDIA DRIVERS UBUNTU 14.04 DRIVER#
As part of installing this driver (version: 352.39), the existing driver will be uninstalled.Īre you sure you want to continue? (Answer: Continue installation)Įxecuting: '/usr/lib/nvidia/pre-install'. > There appears to already be a driver installed on your system (version: 352.39). > Installing NVIDIA driver version 352.39.
#INSTALL LATEST NVIDIA DRIVERS UBUNTU 14.04 LICENSE#
> License accepted by command line option. > Detected 8 CPUs online setting concurrency level to 8. Вот журнал: Using built-in stream user interface There you have it, you should now have TensorFlow installed on your computer.
#INSTALL LATEST NVIDIA DRIVERS UBUNTU 14.04 HOW TO#
TensorFlow also has instructions on how to do a basic test and a list of common installation problems. If you get a import or library error you can try opening a new terminal or restarting your computer.
#INSTALL LATEST NVIDIA DRIVERS UBUNTU 14.04 INSTALL#
$ sudo pip install /tmp/tensorflow_pkg/tensorflowĬlose all terminals and open a new terminal. # with no spaces after tensorflow hit tab before hitting enter to fill in blanks $ sudo pip3 install /tmp/tensorflow_pkg/tensorflow This will build the pip package required for installing TensorFlow in your /tmp/ folder $ bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg If you want to build TensorFlow with GPU support enter: $ bazel build -config=opt -config=cuda //tensorflow/tools/pip_package:build_pip_packageįor CPU only enter: $ bazel build -config=opt //tensorflow/tools/pip_package:build_pip_package Warning Resource Intensive I recommend having at least 8GB of computer memory. If all was done correctly you should see: You can find the compute capability of your device at: Please specify the Cudnn version you want to use. Please specify the Cuda SDK version you want to use, e.g. Default is :įor Python 2 use default or If you wish to build for Python 3 enter: $ /usr/local/lib/python3.4/dist-packages Please input the desired Python library path to use. :įor Python 2 use default or If you wish to build for Python 3 enter: $ /usr/bin/python3
Use defaults by pressing enter for all except: bashrc file: $ source ~/.bashrcĬonfigure TensorFlow Installation $ cd ~/tensorflow Once you save and close the text file you can return to your original terminal and type this command to reload your. This will open your bash file in a text editor which you will scroll to the bottom and add these lines: export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64"Įxport DYLD_LIBRARY_PATH="$DYLD_LIBRARY_PATH:$CUDA_HOME/lib" $ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn* $ sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 $ sudo cp cuda/include/cudnn.h /usr/local/cuda/include
#INSTALL LATEST NVIDIA DRIVERS UBUNTU 14.04 DOWNLOAD#
To install CudNN download cudNN v5 for Cuda 7.5 from Nvidia website and extract into /usr/local/cuda via: $ tar xvzf cudnn-7.5-linux-圆 This will install cuda into: /usr/local/cuda $ sudo dpkg -i cuda-repo-ubuntu-local_7.5-18_b
deb file from Nvidia website $ cd ~/Downloads # or directory to where you downloaded file Instructions also on Bazel website $ echo "deb stable jdk1.8" | sudo tee /etc/apt//bazel.list $ sudo apt-get install oracle-java8-installer git python-dev python3-dev build-essential python-pip python3-pip python-virtualenv swig python-wheel libcurl3-dev Paste each line one at a time (without the $) using Shift + Ctrl + V $ sudo add-apt-repository ppa:webupd8team/java Open a terminal by pressing Ctrl + Alt + T Getting started I am going to assume you know some of the basics of using a terminal in Linux. If you experience any troubles booting linux, try disabling fast & safe boot in your bios and modifying your grub boot options to enable nomodeset. You must also have the 352.63 NVidia drivers installed, this can easily be done from Ubuntu’s built in additional drivers. In order to use TensorFlow with GPU support you must have a Nvidia graphic card with a minimum compute capability of 3.0. I prefer to use Python 3 but I have included options for Python 2 as well. If you would prefer to use Ubuntu 16.04 please follow my other tutorial here. In this tutorial I will be going through the process of building TensorFlow 0.10 from sources for Ubuntu 14.04.
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