GitLab

* 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

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. 

* add capsule example

* clean code

* better naming

* better naming

* Clean Codes based on pytorch MNIST example

* Clean codes

* Add README

* refactor frame codes

* fix unit test

* fix gcn example

* minor doc/message changes

* raise errors for non-exist columns in FrameRef; sanity check when append

* fix unittest; change error msg

* Add warning for none initializer

* fix unittest

* use warnings package

* junction tree vae example

* added README and moved data to dropbox

* auto download; some fix in python3

* WIP: API renaming

* API rewrite and node function refactor

* builtin functions

* builtin functions tested

* fix test

* send and recv spmv test

* WIP: fix examples

* Fix examples using new APIs

* WIP

* WIP

* treelstm dataloader

* Main training loop.

* trainable treelstm script

* fix dependency

* cuda training

* Add tensorized topological traversal

* allowing update_to() with no incoming messages

* fixing partial cases

* fix dgl.batch edge ordering bug

* add graph batching test cases

* fix partial spmv ctx.

* add dataset generating for dgmg

* subgraph copy from

* WIP

* cached members

* Change all usage of id tensor to the new Index object; remove set device in DGLGraph;

* subgraph merge API tested

* add dict type reduced msg test

* model code for generative graphs

* batched version for dynamic graph generation using padding

* renaming function train back to forward

* remove old util function for padding DGMG

* override networkx clear to reset state, add dgl.nn

* Dynamic graph without batching

* use relative import path

* load dataset, pad batch

* bug fix

* experimental batch and unbatch

* dgmg batched version

* minor tweak

* move preprocessing padding into data loading

* batch graph test code

* minor

* batched graph class and test cases

* make dgl.nn.gcn a simple layer plus minor fix

* update dgmg model

* test forward using attribute field

* use frame append, minor changes

* moving networkx operations out of forward

* revert some changes

* remove structural immutability check

* GAT model

* fix output projection to have only one head

* synthetic dataset

* some fix

* gcn readme

* fix edge list order problem in cached graph.

* minor fix

* fix bug in edge iter

* SPMV works

* gcn spmv on CPU

* change gcn style

* fix cached graph performance; fixed gcn dataset bug

* reorg dir

* non-batch spmv; partial update problem with shape change

* fix reorder problem; finish gcn-batch impl

* pop API

* GPU context

Correctly handling lstm model creation

* Change ; fix corner cases in issue20

* Change recvfrom to recv

cleaning and documentation

Initial example file for ginipath

* add reduce_msg related api to dgl graph

* add reduce_sum, switch backend from numpy to pytorch

* update gat gcn to use reduce msg api

* remove reduce_sum

* add built-in reduce functions

* cdgnn example & minor fixes in dgl/graph.py

* incomplete TreeLSTM

* add data preprocess of SST

* fix nx_SST.py

* TreeLSTM completed