Installing TensorFlow - Revision history

WeiWu: /* Tensorflow (with GPU support) Installation */

2018-07-16T19:19:23Z

Tensorflow (with GPU support) Installation

2018-07-16T19:18:31Z

Installing Tensorflow as root for All users

2018-07-16T19:17:19Z

Installing Tensorflow as root for All users

2018-07-16T19:15:29Z

Using Tensorflow

2018-07-14T02:36:00Z

Using Tensorflow

2018-07-13T17:58:52Z

Tensorflow 1.9.0 with GPU Installation Log

2018-07-13T17:58:21Z

Tensorflow 1.9.0 with GPU Installation Log

2018-07-13T04:03:37Z

Tensorflow 1.9.0 with GPU Installation Log

2018-07-13T04:02:34Z

Installing Tensorflow as root for All users

2018-07-13T03:59:19Z

Install CUDA Toolkit 9.0

@@ Line 103: / Line 103: @@
 So far it does not affect the functionality of tensorflow, but it will probably affect libcupti-dev library.
-==Tensorflow (with GPU support) Installation==
+==Tensorflow with GPU support Installation in a virtual environment==
-We followed this instruction here: https://www.tensorflow.org/install/install_linux#InstallingVirtualenv to install tensorflow.
+We followed this instruction here: https://www.tensorflow.org/install/install_linux#InstallingVirtualenv
-===Install Tensorflow using the Virtual Environment===
+===Installation===
 Install on DBServer under the user McNair. Password: askEd
 *1.install virtualenv:

@@ Line 135: / Line 135: @@
 [[FILE:TensorflowGPU.png]]
-==Installing Tensorflow as root for All users==
+==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'''

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 ===Installation===
 *0. Deleted previously installed tensorflow with CPU support:
   sudo pip3 uninstall tensorflow

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 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))
+  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.

@@ Line 21: / Line 21: @@
 ==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 to find out:
+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 python3
 and

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 =Tensorflow 1.9.0 with GPU Installation Log=
 '''Important note:'''<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.
+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.
 ==NVIDIA configuration==

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 '''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==
+===Installation===
 *0. Deleted previously installed tensorflow with CPU support:
   sudo pip3 uninstall tensorflow
@@ Line 133: / Line 133: @@
    sudo pip3 install -U tensorflow-gpu
-==Path variable (crucial)==
+===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 terminal
   nano .bashrc

@@ Line 43: / Line 43: @@
 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}}
+  export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64\
 Save and exit. Close and open the terminal (or source .bashrc).
@@ Line 49: / Line 50: @@
   nvcc -V
 [[File:nvcc.png]]
 ===Install cuDNN v7.1.4===
 *5. Downloaded cuDNN v7.1.4 for CUDA 9.0: