Difference between revisions of "Installing TensorFlow"
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nvcc -V | nvcc -V | ||
[[File:nvcc.png]] | [[File:nvcc.png]] | ||
+ | |||
+ | *5. Downloaded cuDNN: | ||
+ | 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* | ||
+ | |||
*'''Problem encountered''': | *'''Problem encountered''': | ||
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3. <s>If installed correctly, type nvcc- V should verify installation. But currently it returns 'the program nvcc is currently not installed'.</s><br> | 3. <s>If installed correctly, type nvcc- V should verify installation. But currently it returns 'the program nvcc is currently not installed'.</s><br> | ||
− | ==Tensorflow Installation== | + | ==Tensorflow Installation Resource== |
− | *(TODO) To install tensorflow, follow this instruction here: https://www.tensorflow.org/install/install_linux#InstallingVirtualenv and install tensorflow | + | *(TODO) To install tensorflow, follow this instruction here: https://www.tensorflow.org/install/install_linux#InstallingVirtualenv and install tensorflow. |
Revision as of 16:58, 12 July 2018
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
- 5. Downloaded cuDNN:
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*
- 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
- (TODO) To install tensorflow, follow this instruction here: https://www.tensorflow.org/install/install_linux#InstallingVirtualenv and install tensorflow.