Quick install script for MXNet with Python on Ubuntu. Fixing few brok…

…en links and header renaming (apache#3560) * Adding quick installation procedure for Ubuntu and Python interface. * Fixing broken links. Renaming tutorials. MXNet roadmap link in community page.
reminisce · Oct 18, 2016 · cd86d5e · cd86d5e
1 parent cf00ca0
commit cd86d5e
Show file tree

Hide file tree

Showing 13 changed files with 84 additions and 47 deletions.
diff --git a/docs/api/julia/index.md b/docs/api/julia/index.md
@@ -1,4 +1,5 @@
-# MXNet - Julia API
+MXNet - Julia API
+=================
 MXNet supports Julia programming language. The MXNet Julia package brings flexible and efficient GPU
 computing and state-of-art deep learning to Julia.
 

diff --git a/docs/architecture/analogy.md b/docs/architecture/analogy.md
diff --git a/docs/architecture/index.md b/docs/architecture/index.md
@@ -18,15 +18,14 @@ In this section, we will describe general design concepts of Deep Learning syste
 Refer below sections for more details
 * [Programming Models for Deep Learning](http://mxnet.io/architecture/program_model.html)
 * [Dependency Engine for Deep Learning](http://mxnet.io/architecture/note_engine.html)
-* [Squeeze the Memory Consumption of Deep Learning](http://mxnet.io/architecture/note_memory.html)
+* [Optimizing the Memory Consumption in Deep Learning](http://mxnet.io/architecture/note_memory.html)
 * [Efficient Data Loading Module for Deep Learning](http://mxnet.io/architecture/note_data_loading.html)
 * [Survey of RNN Interface](http://mxnet.io/architecture/rnn_interface.html)
 
 # MXNet System Design and Architecture
 
 In this section, we will describe MXNet System architecture and various components.
 * [MXNet System Overview](http://mxnet.io/architecture/overview.html)
-* [Analogy to other DL systems](http://mxnet.io/architecture/analogy.html)
 * [How to read the code](http://mxnet.io/architecture/read_code.html)
 * [Develop and hack MXNet](http://mxnet.io/how_to/develop_and_hack.html)
 

diff --git a/docs/architecture/note_memory.md b/docs/architecture/note_memory.md
@@ -1,4 +1,4 @@
-Squeeze the Memory Consumption of Deep Learning
+Optimizing the Memory Consumption in Deep Learning
 ===============================================
 One important theme about deep learning is to train deeper and larger nets.
 While the hardware has been upgraded rapidly in recent years, the huge deepnet monsters are

diff --git a/docs/community/contribute.md b/docs/community/contribute.md
@@ -2,7 +2,7 @@ Contribute to MXNet
 ===================
 MXNet has been developed and used by a group of active community members.
 Everyone is more than welcome to contribute. It is a way to make the project better and more accessible to more users.
-* Please add your name to [CONTRIBUTORS.md](../CONTRIBUTORS.md) after your patch has been merged.
+* Please add your name to [CONTRIBUTORS.md](https://github.com/dmlc/mxnet/blob/master/CONTRIBUTORS.md) after your patch has been merged.
 
 Guidelines
 ----------
@@ -30,7 +30,7 @@ git rebase upstream/master
   it might be good to merge them together(use git rebase then squash) into more meaningful groups.
 * Send the pull request!
   - Fix the problems reported by automatic checks
-  - If you are contributing a new module, consider add a test case in [tests](../tests)
+  - If you are contributing a new module, consider add a test case in [tests](https://github.com/dmlc/mxnet/tree/master/tests)
 
 Git Workflow Howtos
 -------------------
@@ -86,12 +86,12 @@ Documents
 
 Testcases
 ---------
-* All the test cases are in [tests](../tests)
+* All the test cases are in [tests](https://github.com/dmlc/mxnet/tree/master/tests)
 * We use python nose for python test cases and gtest for c++ unit tests.
 
 Examples
 --------
-* Usecases and examples will be in [example](../example)
+* Usecases and examples will be in [example](https://github.com/dmlc/mxnet/tree/master/example)
 * We are super excited to hear about your story, if you have blog posts,
   tutorials code solutions using MXNet, please tell us and we will add
   a link in the example pages.
@@ -137,7 +137,7 @@ make roxygen
 ```
 
 ### Rmarkdown Vignettes
-Rmarkdown vignettes are placed in [R-package/vignettes](../R-package/vignettes)
+Rmarkdown vignettes are placed in [R-package/vignettes](https://github.com/dmlc/mxnet/tree/master/R-package/vignettes)
 These Rmarkdown files are not compiled. We host the compiled version on [doc/R-package](R-package)
 
 The following steps are followed to add a new Rmarkdown vignettes:

diff --git a/docs/community/index.md b/docs/community/index.md
@@ -10,4 +10,8 @@ Refer here for guide to [contributions](http://mxnet.io/community/contribute.htm
 
 ## Roadmap
 
-Coming soon..
+MXNet is evolving fast with community contributions. To better understand what next in MXNet and what we are working on internally, refer here - [MXNet Roadmap](https://github.com/dmlc/mxnet/labels/Roadmap)
+
+
+&nbsp;
+We welcome community contributions. Refer here for guide to [contributions](http://mxnet.io/community/contribute.html).
diff --git a/docs/get_started/setup.md b/docs/get_started/setup.md
@@ -13,7 +13,7 @@ This topic covers the following:
 
 &nbsp;
 
-You can just get started with MXNet, without reading further, by directly jumping to [Quick Installation Guide](#Quick-Installation) to set up MXNet with a set of bash scripts.
+You can just get started with MXNet, without reading further, by directly jumping to [Quick Installation Guide](#quick-installation) to set up MXNet with a set of bash scripts.
 
 
 &nbsp;
@@ -73,8 +73,33 @@ For users of Python on Amazon Linux and Ubuntu operating systems, MXNet provides
 
 ### Quick Installation on Ubuntu
 
-```<Coming Soon>```
+We provide simple installation scripts for setting up MXNet for Python on Ubuntu 12+ machine. We will install MXNet in your home folder ```~/MXNet```.
+
+
+&nbsp;
+
+We need ```git``` to clone MXNet source code repository to your machine. 
+```bash
+# Install git if not already installed.
+sudo apt-get update
+sudo apt-get -y install git
+```
+
+Clone MXNet source code repository to your machine, run installation script and refresh environment variables. Installation script, along with installing MXNet, will also install all MXNet dependencies namely ```Numpy```, ```LibBLAS``` and ```OpenCV```.
+
+```bash
+# Clone mxnet repository. In terminal, run the commands WITHOUT "sudo"
+git clone https://github.com/dmlc/mxnet.git ~/MXNet/mxnet --recursive
+
+# Install MXNet dependencies
+cd ~/MXNet/mxnet/setup-utils
+bash install-mxnet-ubuntu.sh
+
+# We have added MXNet Python package path in your ~/.bashrc. 
+# Run below command to refresh environment variables.
+$ source ~/.bashrc
 
+You can view the installation script we just used to install MXNet for Python [here](https://raw.githubusercontent.com/dmlc/mxnet/master/setup-utils/install-mxnet-ubuntu.sh).
 
 &nbsp;
 

diff --git a/docs/how_to/index.md b/docs/how_to/index.md
@@ -3,13 +3,13 @@
 This page contains guidelines to use and develop MXNets.
 
 ## Use MXNet on Specific Tasks
-- [Train with multiple CPU/GPUs in data parallelism](multi_devices.md)
-- [Train LSTM with multiple GPUs in model parallelism](model_parallel_lstm.md)
-- [Run MXNet on smart devices](smart_device.md)
-- [Run MXNet on cloud](cloud.md)
-- [Use pre-trained models](pretrained.md)
-- [Use MXNet on variable input length/size (bucketing)](bucketing.md)
-- [Improve performance tips](perf.md)
+- [How to train with multiple CPU/GPUs with data parallelism](multi_devices.md)
+- [How to train with multiple GPUs in model parallelism - train LSTM](model_parallel_lstm.md)
+- [How to run MXNet on smart-devices/mobiles](smart_device.md)
+- [How To Setup MXNet on the AWS cloud using EC2 and S3](cloud.md)
+- [How to use pre-trained models](pretrained.md)
+- [How to use MXNet on variable input length/size (bucketing)](bucketing.md)
+- [How to improve MXNet Performance(perf.md)
 
 ## Develop and Hack MXNet
 - [Create new operators](new_op.md)

diff --git a/docs/tutorials/computer_vision/detection.md b/docs/tutorials/computer_vision/detection.md
@@ -1,4 +1,4 @@
-# Detection
+# Object Detection using Faster R-CNN
 You can get the source code for below example [here](https://github.com/dmlc/mxnet/tree/master/example/rcnn).
 
 # Faster R-CNN in MXNet with distributed implementation and data parallelization

diff --git a/docs/tutorials/computer_vision/segmentation.md b/docs/tutorials/computer_vision/segmentation.md
@@ -1,4 +1,4 @@
-# Segmentation
+# Image Segmentation
 
 You can get the source code for below example [here](https://github.com/dmlc/mxnet/tree/master/example/fcn-xs)
 

diff --git a/docs/tutorials/index.md b/docs/tutorials/index.md
@@ -6,14 +6,14 @@
 
 #### [Training Deep Net on 14 Million Images by Using A Single Machine](http://mxnet.io/tutorials/computer_vision/imagenet_full.html)
 #### [Image Classification](http://mxnet.io/tutorials/computer_vision/image_classification.html)
-#### [Segmentation](http://mxnet.io/tutorials/computer_vision/segmentation.html)
-#### [Detection](http://mxnet.io/tutorials/computer_vision/detection.html)
+#### [Image Segmentation](http://mxnet.io/tutorials/computer_vision/segmentation.html)
+#### [Object Detection using Faster R-CNN](http://mxnet.io/tutorials/computer_vision/detection.html)
 #### [Neural Art](http://mxnet.io/tutorials/computer_vision/neural_art.html)
 
 ### Natural Language Processing
 
 #### [Recurrent Neural Networks](http://mxnet.io/tutorials/nlp/rnn.html)
-#### [Convnet Text Classification](http://mxnet.io/tutorials/nlp/cnn.html)
+#### [Text Classification using Convolutional Neural Network](http://mxnet.io/tutorials/nlp/cnn.html)
 #### [NCE Loss](http://mxnet.io/tutorials/nlp/nce_loss.html)
 
 ### Speech Recognition

diff --git a/docs/tutorials/nlp/cnn.md b/docs/tutorials/nlp/cnn.md
@@ -1,5 +1,5 @@
-Implementing CNN for Text Classification in MXNet
-============
+# Text Classification using Convolutional Neural Network on MXNet
+
 You can get the source code for below example [here](https://github.com/dmlc/mxnet/tree/master/example/cnn_text_classification)
 
 It is slightly simplified implementation of Kim's [Convolutional Neural Networks for Sentence Classification](http://arxiv.org/abs/1408.5882) paper in MXNet.

diff --git a/setup-utils/install-mxnet-ubuntu.sh b/setup-utils/install-mxnet-ubuntu.sh
@@ -0,0 +1,29 @@
+#!/usr/bin/env bash
+######################################################################
+# This script installs MXNet for Python along with all required dependencies on a Ubuntu Machine.
+# Tested on Ubuntu 14.0 + distro.
+######################################################################
+set -e
+
+echo "Installing build-essential, libatlas-base-dev, libopencv-dev..."
+
+sudo apt-get update
+sudo apt-get install -y build-essential libatlas-base-dev libopencv-dev
+
+echo "Installing MXNet core. This can take few minutes..."
+cd ~/MXNet/mxnet/
+make -j$(nproc)
+
+echo "Installing Numpy..."
+sudo apt-get install python-numpy
+
+echo "Installing Python setuptools..."
+sudo apt-get install python-setuptools
+
+echo "Installing Python package for MXNet..."
+cd python; sudo python setup.py install
+
+echo "Adding MXNet path to your ~/.bashrc file"
+echo "export PYTHONPATH=~/MXNet/mxnet/python" >> ~/.bashrc
+
+echo "Done! MXNet for Python installation is complete. Go ahead and explore MXNet with Python :-)"