Installing TensorFlow
Contents
Old
Currently installed with Anaconda Python 3.
https://stackoverflow.com/questions/36355073/upgrading-numpy-fails-with-permission-denied-error
https://www.tensorflow.org/install/install_windows
with cpu support only
https://www.tensorflow.org/install/install_linux
need to logoff other users via server manager
New (by Wei and Minh)
Important note: install the version of software/packages strictly according to the instructions provided by Tensorflow. A different version of software, for example CUDA toolkit 9.2 instead of 9.0, might lead to failure in tensorflow.
NVIDIA configuration
(In progress) Before installing tensorflow with GPU, configure the NVIDIA® software by following instruction: https://www.tensorflow.org/install/install_linux#NVIDIARequirements
Install CUDA Toolkit 9.0
- 1. Installed CUDA Toolkit 9.0 Base Installer with the Runfile option. The toolkit is in
/usr/local/cuda-9.0
for the toolkit. Did NOT install NVDIA accelerated Graphics Driver for Linux-x86_64 384.81 (We believe we have a different graphic driver. we have a much Newer version(396.26)). Installed the CUDA 9.0 samples in
HOME/MCNAIR/CUDA-SAMPLES.
- 2. Installed Patch 1, 2 and 3. The command to install was
sudo sh cuda_9.0.176.2_linux.run # (9.0.176.1 for patch 1 and 9.0.176.3 for patch 3)
- 3. Set up the environment variables:
The PATH variable needs to include /usr/local/cuda-9.0/bin To add this path to the PATH variable:
export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}}
In addition, when using the runfile installation method, the LD_LIBRARY_PATH variable needs to contain /usr/local/cuda-9.0/lib64 on a 64-bit system To change the environment variables for 64-bit operating systems:
export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64\${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
Note that the above paths change when using a custom install path with the runfile installation method.
To accomplish this:
nano /home/mcnair/.bashrc
Add
export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64\${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
Save and exit. Close and open the terminal (or source .bashrc).
- 4. To verify CUDA Toolkit 9.0 is installed, type
nvcc -V
Install cuDNN v7.1.4
- 5. Downloaded cuDNN v7.1.4 for CUDA 9.0:
In order to download cuDNN, ensure you are registered for the NVIDIA Developer Program. Then Go to: NVIDIA cuDNN home page. -> Click Download. -> Complete the short survey and click Submit. -> Accept the Terms and Conditions. A list of available download versions of cuDNN displays. -> Select the cuDNN version you want to install. Chose the tar file.
- 6. Install cuDNN: your CUDA directory path is referred to as
/usr/local/cuda/
your cuDNN download path is referred to as
<cudnnpath>
Follow these commands: a. Navigate to your <cudnnpath> directory containing the cuDNN Tar file. b. Unzip the cuDNN package.
$ tar -xzvf cudnn-9.0-linux-x64-v7.tgz
c. Copy the following files into the CUDA Toolkit directory.
$ sudo cp cuda/include/cudnn.h /usr/local/cuda/include $ sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 $ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
Install GPU drivers
- 7. Did not need to install the GPU drivers because we already had the correct version.
Install libcupti-dev library
- 8.Tried to install the libcupti-dev library with:
sudo apt-get install cuda-command-line-tools-9-0
but apparently it was already installed. (How surprising!)
LD-LIBRARY_PATH environment variable modification
- 9. Added the following path to the LD-LIBRARY_PATH environment variable by accessing bash as per above:
export LD_LIBRARY_PATH=${LD_LIBRARY_PATH:+${LD_LIBRARY_PATH}:}/usr/local/cuda/extras/CUPTI/lib64
Install TensorRT 3.0 (optional)
- 10.Did not install TensorRT 3.0
- Problem encountered:
1. In usr/local/ we found files 'CUDA-9.2' and 'CUDA-8.0'. These were probably installed in the past.
2. When execute the following command in a terminal, it returns 'PATH: command not found'.
$ export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}}
3. If installed correctly, type nvcc- V should verify installation. But currently it returns 'the program nvcc is currently not installed'.
Tensorflow Installation Resource
- To install tensorflow, follow this instruction here: https://www.tensorflow.org/install/install_linux#InstallingVirtualenv and install tensorflow.
Install Tensorflow using the Virtual Environment
Install on DBServer under the user McNair. Password: askEd
