GitLab

[Doc] Basic tutorials & two model tutorials

* backend interface

* small fix

* more comments to the data type dict

* WIP

* convert_to and narrow

* WIP

* pytorch and numpy backend; WIP on mxnet backend

* mxnet backend

* narrow

* Fix all usages

* fix for mx

* fix for mx

* fix mx

* fix mx

* fix mx

* fix mx

* fix mx

* fix mx

* fix mx

* revert jenkins

* add sparse_matrix api

* sparse matrix api

* some fixme

* Fix as requested

* pretty printer

* Conflicts:
	python/dgl/data/sbm.py

* refined line_graph implementation

* fix broken api calls

* small fix to trigger CI

* requested change

* 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

* cherry picking optimization from jtnn

* unbatch by slicing frames

* reduce pack

* oops

* support frame read/write with slices

* reverting to unbatch by splitting; slicing is unfriendly to backward

* replacing lru cache with static object factory

* replacing Scheme object with namedtuple

* remove comment

* forgot the find edges interface

* subclassing namedtuple

* 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 Update the outdated graph convolution layer class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. 

* add capsule example

* clean code

* better naming

* better naming

* Clean Codes based on pytorch MNIST example

* Clean codes

* Add README

* add immutable graph index.

* update ImmutableGraphIndex.

* add benchmarks of subgraph generation.

* fix node_subgraphs.

* use scipy synthetic data in immutable graph.

* create immutable_graph.

* use spmv in gcn.

* fix immutable graph index.

* update graph index.

* create ImmutableSubgraphIndex.

* return subgraph node and edge mapping.

* fix benchmark.

* add mapping to subgraph nid.

* test in_edges and out_edges.

* update benchmark.

* Fix immutable subgraph.

* complete in_edges and out_edges.

* fix benchmarks.

* add test on node_subgraphs

* add sse.

* construct subgraphs in parallel.

* add in/out degree(s).

* make immutable graph index backend-specific.

* implement has_edge(s) and edge_id(s).

* Revert "use spmv in gcn."

This reverts commit 9cfed5f5fb3dd2ed9b98745348b1c0e9731ed7f7.

* implement node_subgraphs in GraphIndex.

* fix sse.

* address comments.

* address comments.

* Update mxnet docker.

* fix tests.

* enable mxnet CI.

* add mxnet tests.

* update jenkins.

* update mxnet docker image.

[Doc] fixed installation document

Doc

* setup sphinx-gallery; work on graph tutorial

* draft dglgraph tutorial

* update readme to include document url

* rm obsolete file

* Draft the message passing tutorial

Doc

Sync with upstream

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];

* fixing networkx conversion with 0 edges

* fixes as required

* remove obsolete comment

Sync with latest commit