TensorFlow install using virtualenv on ubuntu

TensorFlow install using virtualenv on ubuntu environment.

The method is same with pip install.

But this post is helpful when you forgot virtualenv commend.

1. install virtualenv
$ $ sudo apt-get install python-pip python-dev python-virtualenv

2. make folder for your own virtual space
$ virtualenv --system-site-packages ~/tensorflow

3. run virtualenv
$ source ~/tensorflow/bin/activate  # If using

4. exit virtualenv
(tensorflow)$ deactivate

5. install tensorflow
this state is that running virtualenv step 3.

# Ubuntu/Linux 64-bit, CPU only:
(tensorflow)$ pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp34-none-linux_x86_64.whl

TensorFlow install

On window.

1. Anaconda possible? I don't know yet.

2. using docker (Inconvenience)

On linux(ubuntu)

1. install using by pip (good but not easy to modify computer setting)

2. virtualenv (good!)

3. anaconda (may be good!)
--not try yet.


TensorFlow install using pip

TensorFlow install on ubuntu
(This is referenced pip install tutorial on tensorflow.org -> https://www.tensorflow.org/versions/r0.7/get_started/os_setup.html#pip-installation)

Firstly, I install virtual box for using linux ubuntu on my window environment.
(Tensorflow cannot use on original window system.)

Virtual Box is that possible run virtual machine such as VMware, Parallels and so on.

One thing, after install ubuntu using Virtual box, screen resolution is not normal, then you have to install  'guest extension cd'.

refer to virtual box usage and install ubuntu in the web.

So suppose our system is ubuntu.

run terminal and type this command after install tensor flow.

# Ubuntu/Linux 64-bit
$ sudo apt-get install python-pip python-dev

$ sudo apt-get update

$ sudo easy_install pip

# Ubuntu/Linux 64-bit, CPU only:
$ sudo pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp27-none-linux_x86_64.whl

And test tensorflow is install well or not
$ python
>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
>>> print(sess.run(hello))
Hello, TensorFlow!
>>> a = tf.constant(10)
>>> b = tf.constant(32)
>>> print(sess.run(a + b))