GitLab

* Fix DGMG epoch time

* Fix README for DGMG

* update

* move pytorch code to examples.

* fix.

* fix tutorial

* [Doc] updated readme

* contribution guide change

* small edits

* add perf #

* Update README.md

* Update README.md

* add others...

* rewrite scalability

* model & code links

* some note for treelstm

* rewrite scalability

* fix all code tutorial links and typos in texts

* sse readme format

* fix

* sse paper link

* gat readme

* fix

* update example readme

* mx example readme

* add results in readme

* mx rgcn readme

* entity classify work for examples

* add loop_msg

* remove wrong assert

* remove one reshape

* add readme

* add MRR

* remove mrr from entity task

* return seed ids.

* fix tests.

* implement.

* WIP

* lr -> 0.01

* new cora dataset

* normalization code

* minor format change

* normalization factor for deg bucket

* change Index.tolist -> Index.tonumpy; fix bug in traversal; remove dependencies in data

* fix import

* fix __all__ and some docstring

* fix.

* make it generic.

* add the API.

* fix.

* remove mxnet.

* update readme.

* update readme

* correct vid mapping API.

* fix sse.

* data preprocessing for rgcn

* edge subgraph

* WIP: RGCN

* use edge feature in spmv

* fix bugs

* match AIFB accuracy

* match mutag accuracy

* avoid materializing in featureless case

* remove untouched nodes and relabel nodes

* fix python list concatenate overhead

* sparsely store edge types

* refactor entity classify code for clean link prediction implementation

* further refactor code

* refactoring

* rgcn block decompose layers

* link predict dataset

* link predict model and eval code

* dropout, self-loop, regularization, etc, plus bug fixes

* update to new api

* dataset update

* bugs, WIP, need to impl early stopping and filtered metrics

* instruction to run, and minor

* group conv and early stop

* clean slow code

* some code comments

* use new api in model code

* change data preprocessing

* entity classify model

* WIP

* move dgl graph out of model

* hot fix for extract zip

* fix link predict model

* use latest dgl apis

* still have memory issue...

* bug fix and move inference to cpu

* move rgcn data processing to contrib

* th.allclose -> U.allclose

* minor change in readme

* fix memory issue in entity classify

* fix and testing code for link predict

* fix entity classify

* clean up

* fix comments

* revert erroneous git merge changes

* code clean up and more comments

* minor

* dependent package version

* clean up pr-188 and resubmit

* address Da comments

* 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.

* cherry picking optimization from jtnn

* adding official code.  TODO: fix DGLMolTree

* updating to current api.  vae test still failing

* reverting to list stacking

* reverting to list stacking

* cleaning x flags (stupid windows)

* cleaning x flags (stupid windows)

* adding stats

* optimization

* updating dgl stats

* update again

* more optimization

* looks like computation is faster

* removing profiling code

* cleaning obsolete code

* remove comparison warning

* readme update

* official implementation got a lot faster

* minor fixes

* unbatch by slicing frames

* working around unbatch

* reduce pack

* oops

* support frame read/write with slices

* reverting back to readout as unbatch-by-slicing slows down backward

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

* replacing lru cache with static object factory

* 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

* forgot the find edges interface

* subclassing namedtuple

* updating to the latest api spec

* bugfix

* bfs with edges

* dfs toy test case

* clean up

* style fix

* bugfix

* update to latest api; include traversal

* replacing with readout

* simplify decoder

* oops

* cleanup

* reducing number of sets

* more speed up

* profile results

* random fixes

* fixing tvmarray handling incontiguous dlpack input

* fancier dataloader

* fix a potential context mismatch

* todo: support pickling or using scipy in multiprocessing load

* pickling support

* resorting to suggested way of pickling

* custom attribute pickling check

* working around a weird pytorch pickling bug

* including partial frame case

* enabling multiprocessing dataloader

* pickling everything now

* really works

* oops

* updated profiling results

* cleanup

* fix as requested

* cleaning random blank lines

* removing profiler outputs

* starting decoding

* testing, WIP

* tree decoding

* graph decoding, WIP

* graph decoding works

* oops

* fixing legacy apis

* trimming number of candidate structures

* sampling cleanups

* removing comparison test

* updated description

* change the signature of node/edge filter

* upd filter

* Support multi-dimension node feature in SPMV

* stable version

* hotfix

* upd tutorial

* upd README

* fix memory leak & Remove unnecessary initializer

* change confused name

* fix name

* Move func outside loop

* fix name inconsistency

* DGMG with batch size 1

* Fix

* Adjustment

* Fix

* Fix

* Fix

* Fix

* Fix has_node and __contains__

* Batched implementation for DGMG

* Remove redundant dependency

* Adjustment

* Fix

* Add comments

* [Model]SBM hotfix

* [Model] remove backend in data

* DGMG with batch size 1

* Fix

* Adjustment

* Fix

* Fix

* Fix

* Fix

* add a test.

* move file.

* debug

* add degree normalization.

* it can converge now.

* remove hidden_data.

* use readonly graph index.

* use subgraph loader.

* refactor code and remove intermediate data.

* split inference.

* mix cpu and gpu training.

* fix mxnet sparse_matrix constructor.

* convert tensor context.

* set up the prediction model.

* load mxnet csr directly.

* add timing.

* move test_sse.py to sse_batch.py

* fix the tensor version of SSE.

* update README.

* update tree lstm

* tree_lstm (new interface)

* simplify pop

* merge qipeng(root)

* upd tree-lstm & tutorial

* upd model

* new capsule tutorial

* capsule for new API

* fix deprecated API

* New tutorial and example

* investigate gc problem

* add viz code

* new capsule tutorial

* remove ipynb

* move u_hat

* add link

* add requirements.txt

* remove ani.save

* update ci to install requirements

* utf-8

* change seed

* graphviz requirement

* accelerate

* little format

* update some markup

* add neighbor sampler.

* fix sampler.

* handle non-existing nodes differently in MapParentIdToSubgraphId.

* fix sampling tests.

* parallelize sampling.

* add more tests.

* fix a bug in subgraph loader.

* get number of sampled nodes directly.

* load mxnet CSR to DGLGraph directly.

* create graph from mxnet csr array directly.

* use subgraph loader in SSE.

* fix a bug in sampling.

* output framework tensor.

* fix.

* remove unnecessary code.

* fix tests.

* add SSE README.

* move to contrib.

* address comments.

* add tests.

[DOC][Model] Tree-LSTM example and tutorial

* new capsule tutorial

* capsule for new API

* fix deprecated API

* New tutorial and example

* investigate gc problem

* add viz code

* new capsule tutorial

* remove ipynb

* move u_hat

* add link

* add requirements.txt

* remove ani.save

* update ci to install requirements

* add graphviz

* 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

* move gat to the new api.

* fix gcn.

* update sse.

* fix dgl core.

* update sse.

* fix small bugs in dgl core.

* fix mxnet tests.

* retrigger

* address comments and fix more bugs.

* fix

* fix tests.

* tree_lstm (new interface)

* simplify pop

* bfs, dfs and topological traversal

* dfs and test cases

* Conflicts:
	python/dgl/graph.py
	src/graph/graph.cc
	src/graph/graph_op.cc

* documentation

* requested changes

* Conflicts:
	Jenkinsfile
	examples/pytorch/gcn/gcn.py
	examples/pytorch/gcn/gcn_spmv.py
	python/dgl/graph.py
	python/dgl/graph_index.py
	src/graph/graph.cc
	src/graph/graph_op.cc

* Conflicts:
	Jenkinsfile
	python/dgl/graph_index.py

* fix lint errors

* fix lint errors

* fix lint errors

* fix test cases

* requested changes

* traversal interface

* [Bug] fixed a typo that caused syntax error (#120)

* WIP

* bfs nodes generator works

* topological traversal

* WIP: dfs_edges

* dfs edges

* dfs labeled edges

* utest for traversal

* fix lint

* fix utest

* code clean

* changes 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

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.