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https://stackoverflow.com/questions/46499808/pip-throws-typeerror-parse-got-an-unexpected-keyword-argument-transport-enco#_=_
=New (by Wei and Minh): Tensorflow 1.9.0 with GPU Installation Log='''Important note: install '''<br> 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.When upgrading tensorflow, do it very carefully. As of July 2018, Tensorflow is [https://github.com/tensorflow/tensorflow/issues/17629 notoriously easy to break] with careless installation. DO NOT attempt to install Tensorflow under your user account. Tensorflow has been installed for all users, and a new local install will interfere with it. ==Synopsis==Tensorflow was previously installed. In 2018 Summer, a new piece of graphics card was installed on DB Server. Wei and Minh hence-force installed and configured '''tensorflow-gpu 1.9.0 for Python3.6''' for all users of DB Server. ==Using Tensorflow==It is important to know that, on DB Server, Tensorflow-gpu 1.9.0 is installed for ''python3.6'', instead of either the default ''python3'' which is Python 3.5, or the default ''python' ' which is Python 2.7 . In case that the system default ''python3'' might be changed, type in terminal to find out: which python3and which python3.6  A quick test of whether tensorflow-gpu is working for ''python3.6'', type the following into a terminal: python3.6 -c "import tensorflow as tf; sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))" This will report back which CPU and GPU devices the tensorflow is using. If there is no information for the GPU device, there is something wrong. 
==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
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).
nvcc -V
[[File:nvcc.png]]
 
===Install cuDNN v7.1.4===
*5. Downloaded cuDNN v7.1.4 for CUDA 9.0:
So far it does not affect the functionality of tensorflow, but it will probably affect libcupti-dev library.
==Tensorflow with GPU support Installation Resourcein a virtual environment==To install tensorflow, follow We followed this instruction here: https://www.tensorflow.org/install/install_linux#InstallingVirtualenv and install tensorflow.===Install Tensorflow using the Virtual EnvironmentInstallation===
Install on DBServer under the user McNair. Password: askEd
*1.install virtualenv:
[[FILE:tensorflow.png]]
===Testing Tensorflow with GPUin virtual environment===
Create a python file with the following:
import tensorflow as tf
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
Run it in the virtual environment.
[[FILE:TensorflowGPU.png]]
==Installing Tensorflow with GPU support Installation as root for All users=='''Important note: Currently on DB Server, pip/pip3 is working with Python3.6 rather than Python3. Hence the following installs a copy of tensorflow-gpu 1.9.0 for Python3.6 for all users''' ===Installation===We followed instructions here: https://www.tensorflow.org/install/install_linux#InstallingNativePip *0. Deleted previously installed tensorflow with CPU support: sudo pip3 uninstall tensorflow*1. Used this commandto install tensorflow-gpu:
sudo pip3 install -U tensorflow-gpu
Ran ===Path variable (crucial)===If you logged on as a user using tensorflow for the first time, you need to set the CUDA Toolkit 9.0 environment variables. Type into a problem with python3terminal nano .bashrc Add the following: export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}} export LD_LIBRARY_PATH=/usr/local/cuda-9.5 0/lib64\ ${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}} Save and pip3 compatibility issueexit (CTRL + O and CTRL + X). pip3 supported Type source .bashrc  ===Testing Tensorflow with GPU as (non-root) user===After ssh onto DB Server, type the following command into a terminal: python3.6-c "import tensorflow as tf; print(tf.__version__);sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))" [[FILE:TensorflowGPUGlobal. We'll look into that tomorrowpng]]

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