Installing TensorFlow

Revision as of 18:15, 12 July 2018 by Leminh.ams (talk | contribs)
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Currently installed with Anaconda Python 3.

with cpu support only

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:

Install CUDA Toolkit 9.0

  • 1. Installed CUDA Toolkit 9.0 Base Installer with the Runfile option. The toolkit is in

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

  • 2. Installed Patch 1, 2 and 3. The command to install was
sudo sh # ( for patch 1 and 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


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

your cuDNN download path is referred to as


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

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

Install Tensorflow using the Virtual Environment

Install on DBServer under the user McNair. Password: askEd