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tensorflow-ipy

About

This project provides a Ubuntu (14.04) Vagrant Virtual Machine (VM) with the TensorFlow library from Google and IPython (now know as Jupyter) notebooks.

Follow the Requirements section below for a one-time setup of Virtualbox, Vagrant and Git before running the commands below. These instructions should work on Windows, Mac and Linux operating systems.

The list of releases of this project with a description of the main changes are included here.

Running TensorFlow

1. Start the VM

  1. Change to the tensorflow-ipy root directory

    cd tensorflow-ipy
    
  2. Start the Virtual machine (VM)

    vagrant up
    
  3. Login to the VM

    vagrant ssh
    

2. Run your first TensorFlow command line program

First run section 1.

  1. Change to the python directory

    cd /vagrant/python
    
  2. Run the first program

    python3 first-tensorflow.py
    # to disable warnings type
    TF_CPP_MIN_LOG_LEVEL=2 python3 first-tensorflow.py
    
  3. Make sure the version printed on the first line of the output is the version you expect. The releases are documented on this page

3. Start the IPython (Jupyter) notebooks

First run section 1.

  1. Change to the notebooks directory

    cd /vagrant/notebooks
    
  2. Run the IPython notebook server

    chmod +x ipython-run.sh
    ./ipython-run.sh
    
  3. Open your browser to http://192.168.33.10:8888/ to view the notebooks

4. Get the TensorFlow source code and examples

First run section 1.

  1. Make the tensorflow directory if does not exist.

    mkdir /vagrant/tensorflow_source
    
  2. Change to the tensorflow directory (will not be checked in to git)

    cd /vagrant/tensorflow_source
    
  3. Clone the tensorflow repository

    git clone https://github.com/tensorflow/tensorflow.git
    

5. Run the Udacity TensorFlow examples

First run section 1.

  1. Change to the notebooks directory

    cd /vagrant/scripts
    
  2. Run the IPython notebook server with Udacity TensorFlow notebooks

    chmod +x ./ipy-udacity.sh
    ./ipy-udacity.sh
    
  3. Open your browser to http://192.168.33.10:8888/ to view the notebooks

6. Using Tensorboard

  1. Run Tensorboard from the command line
tensorboard --logdir=/home/ubuntu/tensorflow-logs
  1. Open a web browser to Tensorboard at http://192.168.33.10:6006/

Tensorflow links

Jupyter notebook extensions

  1. Install Jupyter notebook extensions

    jupyter contrib nbextension install --user
    
  2. Install vim extension (optional)

    cd $(jupyter --data-dir)/nbextensions
    git clone https://github.com/lambdalisue/jupyter-vim-binding vim_binding
    

Requirements

The following software is needed to get the software from github and run Vagrant. The Git environment also provides an SSH client for Windows.

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tensorflow-ipy's Issues

Error while running vagrant up

When i run the command vagrant up i get an error.

==> tensorflow-ipy: fatal: [localhost]: FAILED! => {"changed": false, "cmd": "/usr/bin/pip3 install httpie", "failed": true, "msg": "\n:stderr: Traceback (most recent call last):\n File "/usr/bin/pip3", line 5, in \n from pkg_resources import load_entry_point\n File "/usr/local/lib/python3.4/dist-packages/pkg_resources/init.py", line 70, in \n import packaging.version\nImportError: No module named 'packaging'\n"}
==> tensorflow-ipy: to retry, use: --limit @/vagrant/ansible/playbook.retry
==> tensorflow-ipy:
==> tensorflow-ipy: PLAY RECAP *********************************************************************
==> tensorflow-ipy: localhost : ok=22 changed=0 unreachable=0 failed=1
The SSH command responded with a non-zero exit status. Vagrant
assumes that this means the command failed. The output for this command
should be in the log above. Please read the output to determine what
went wrong.

It says "to retry, use: --limit @/vagrant/ansible/playbook.retry" so i tried ssh-ing into vagrant and running

sudo ansible-playbook ansible/playbook.yml

But i receive the same error

Any thoughts?

Missing python-tk dependency

Error when running the MNIST example:

No module named _tkinter, please install the python-tk package

When running the block containing

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
%pylab inline

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