* add examples in traversal.py
* message propagate methods
* use the new message propagation for tree-lstm
* update to the new name
* update propagate API doc
* update doc
* add propagate utest
* Add SH tutorials
* setup sphinx-gallery; work on graph tutorial
* draft dglgraph tutorial
* update readme to include document url
* rm obsolete file
* Draft the message passing tutorial
* Capsule code (#102)
* add capsule example
* clean code
* better naming
* better naming
* [GCN]tutorial scaffold
* fix capsule example code
* remove previous capsule example code
* graph struc edit
* modified: 2_graph.py
* update doc of capsule
* update capsule docs
* update capsule docs
* add msg passing prime
* GCN-GAT tutorial Section 1 and 2
* comment for API improvement
* section 3
* Tutorial API change (#115)
* change the API as discusses; toy example
* enable the new set/get syntax
* fixed pytorch utest
* fixed gcn example
* fixed gat example
* fixed mx utests
* fix mx utest
* delete apply edges; add utest for update_edges
* small change on toy example
* fix utest
* fix out in degrees bug
* update pagerank example and add it to CI
* add delitem for dataview
* make edges() return form that is compatible with send/update_edges etc
* fix index bug when the given data is one-int-tensor
* fix doc
* Fix
1. Fix two typos in gcn.py and gcn_spmv.py
2. Update README
* Fix GCN module
1. Update the outdated graph convolution layer class
2. Fix a bug in the code where dropout never works. Modules like dropout/batch norm depend on whether we are in the training stage or inference stage.
* Fix a bug in dropout
1. dropout depends on nn.Module.training
* Update GCN module
* Fix README
* Fix dropout & remove self.msg_field
* Fix
* Align with TF implementation
* Make g an argument for forward
* Remove features from the argument of GraphConv layer
* Support for create nodes/edges after setting representations
* Remove redundant commit
* Delete test_init_repr.py
* Test case for dynamic addition
* Base 'add_rows' upon 'append'
* Move test function
* Fix
* test by assertion
* changed add_rows to adding blank rows only; adding convert_to to backend
* moving test to basics
* oops mxnet
1. Update `examples/pytorch/gcn` and `python/dgl/nn/pytorch` based on the latest APIs
2. Add full support for dropout in `examples/pytorch/gcn` and `python/dgl/nn/pytorch`
3. Rename `GCN` class in `python/dgl/nn/pytorch` to be `GraphConvolutionLayer` class
4. Make node field an argument that can be configured by users in GraphConvolutionLayer
Note that adjacency normalization has not been supported yet in the examples.
To fix the compiler error on Mac OSX:
/dgl/src/c_api_common.cc:27:16: error: conversion from 'tvm::runtime::TVMArgValue' to 'size_t' (aka 'unsigned long') is ambiguous
size_t which = args[0];
Gan Quan