Update docs and README

snap-stanford · Apr 7, 2021 · 80262da · 80262da
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diff --git a/README.md b/README.md
@@ -2,7 +2,7 @@
 
 [![PyPI](https://img.shields.io/pypi/v/deepsnap.svg?color=brightgreen)](https://pypi.org/project/deepsnap/) [![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/snap-stanford/deepsnap/blob/master/LICENSE) [![Build Status](https://travis-ci.org/snap-stanford/deepsnap.svg?branch=master)](https://travis-ci.org/github/snap-stanford/deepsnap) [![Downloads](https://pepy.tech/badge/deepsnap)](https://pepy.tech/project/deepsnap) [![Repo size](https://img.shields.io/github/repo-size/snap-stanford/deepsnap?color=yellow)](https://github.com/snap-stanford/deepsnap/archive/refs/heads/master.zip)
 
-**[Documentation](https://snap.stanford.edu/deepsnap/)** | **[Examples](https://github.com/snap-stanford/deepsnap/tree/master/examples)**
+**[Documentation](https://snap.stanford.edu/deepsnap/)** | **[Examples](https://github.com/snap-stanford/deepsnap/tree/master/examples)** | **[Colab Notebooks](http://snap.stanford.edu/deepsnap/notes/colab.html)**
 
 DeepSNAP is a Python library to assist efficient deep learning on graphs. 
 DeepSNAP features in its support for flexible graph manipulation, standard pipeline, heterogeneous graphs and simple API.

diff --git a/docs/source/notes/introduction.rst b/docs/source/notes/introduction.rst
@@ -404,8 +404,8 @@ Dataset splitting for heterogeneous graph encompasses the following additional d
   of object in its corresponding :attr:`task`, having :attr:`edge_split_mode` set to `approximate` could give the user some performance gain.
 
 
-Heterogeneous GNN in DeepSNAP
------------------------------
+DeepSNAP Heterogeneous GNN
+--------------------------
 
 The Heterogeneous GNN layer is a PyTorch :class:`nn.Module` that supports easy creation of heterogeneous GNN, building on top of PyTorch Geometric. Users can easily specify the message passing model for each message type.
 The message passing models are straightforward adaptation of Pytorch Geometric homogeneous models (such as GraphSAGE, GCN, GIN). In future release, we will provide even easier utilities to create such heterogeneous message passing models.

diff --git a/tests/README.md b/tests/README.md
@@ -0,0 +1,7 @@
+## Tests
+
+To test, `nose` is required.
+
+```sh
+pip install nose
+```