* 0.1.2 release
* oops
* more fixes on windows
* [Bugfix] fix download dir (#275)
* fix download dir
* add doc for the env var
* windows 7 -> 10
* doc update
* [Bugfix] Fix conversion from networkx (#286)
* fix from_nx when no edge id available
* add test cases
* more detailed tests
* more comments
* [Bugfix] Switch to sparse_coo_matrix for torch 1.0+ (#282)
* switch to sparse_coo_matrix for torch 1.0+
* fix bug when the version is 0.4.1.post2
* change to distutils
* fix a bug in creating immutable graph index.
* fix for new changes in the backend API.
* fix for creating immutable graph index from coo matrix.
* retrigger
* add sse tutorial
* add mxnet tutorial ci
* fix ci
* fix ci
* fix ci
* fix ci
* fix ci
* fix ci
* Fix ci
* Fix ci
* Fix ci
* fix ci
* fix ci
* fix ci
* fix ci
* fix ci
* fix ci
* Fix CI
Fix CI image
* permission fix
* fix a bug in the code.
* small fix
* fix doc
* fix ci
* shorten the iters
* fix
* remove extra file
* add load_backend api to dynamically switch to another backend
* try fix
* fix tutorial
* fix tutorial
* fix bug in tutorial
* lazy eval edge ids.
* parallelize node id lookup.
* fix a bug.
* use mxnet for index.
* use update_all in the subgraph training.
* sample neighbors.
* Revert "parallelize node id lookup."
This reverts commit e661f69bb06cb5a7c246f0e106f245e27800e220.
* update README.
* cache subgraphs.
* support all degrees.
* cache adj in CPU.
* fix a bug in sse.
* print.
* raise error on mutable graphs.
* measure train time per epoch.
* fix a bug in graph_index.
* remove readonly in DGLSubGraph.
* cache subgraph properly.
* accelerate getting adjacency.
* split infer.
* lazy eval edges.
* specify inference mode.
* update for new sampler.
* use new mxnet sampling api.
* fix indent.
* remove profiling code.
* remove mxnet from sampler.
* return a lambda function for graph edges.
* add docs for immutable subgraph.
* Revert "return a lambda function for graph edges."
This reverts commit 0de5d7f100e230c518a3fb8976a6227f474d09ee.
* get parent_eid.
* pickling support
* resorting to suggested way of pickling
* custom attribute pickling check
* working around a weird pytorch pickling bug
* including partial frame case
* pickling everything now
* fix as requested
* 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 Update the outdated graph convolution layer class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
* support mxnet.
* add mxnet version of GCN.
* rename mxnet.nd as F.
* add mxnet GAT.
* enable GPU for GCN.
* fix MXNet GCN train.
* Use adam to optimize GAT
* support more operators.
* support sparse arrays.
* update mxnet backend.
* support index_copy.
* remove NN.
* update mxnet backend.
* temp check in.
* fix data conversion.
* add test.
* clean up mxnet backend.
* update mxnet examples.
* Revert "remove NN."
This reverts commit d815d9a0ec619f9ce9099c48cd35db9d8e947483.
* temp disable MXNet version of NN.
* 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
* 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
* subgraph
* more test cases
* WIP
* new FrameRef and test
* separate nx init code
* WIP
* subgraph code and test
* line graph code and test
* adding new test for adding new features on line graphs
* no backtracking line graph
* fix inplace relabel
* 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
* 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
* 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
Minjie Wang