GitLab

* [Model] Simplifying Graph Convolutional Networks.

* - improve code stype (use nn.Linear)
- use `bias` option
- update hyperparameter and corresponding performance

* sample layer subgraphs.

* fix.

* fix.

* add layered subgraph.

* fix lint.

* fix.

* fix tutorial.

* fix.

* remove copy_to_parent.

* add num_layers

* move sampling code to sampler.cc

* fix.

* move subgraph construction out.

* Revert "move subgraph construction out."

This reverts commit 24b3d13b0d8ed5f91847ea75a7674ee8f7d45cff.

* change to NodeFlow.

* use NodeFlow in Python.

* use NodeFlowIndex.

* add node_mapping and edge_mapping.

* remove unnecessary code in SSE tutorial.

* Revert "remove unnecessary code in SSE tutorial."

This reverts commit 093f0413d5fa2e63ca5f80c46c80a126a9fb720c.

* fix tutorial.

* move to node_flow.

* update gcn cv updater.

* import NodeFlow.

* update.

* add demo code for vanilla control variate sampler.

* update.

* update.

* add neighbor sampling.

* return flow offsets.

* update node_flow.

* add test.

* fix sampler.

* fix graph index.

* fix a bug in sampler.

* fix map_to_layer_nid and map_to_flow_eid.

* fix apply_flow.

* remove model code.

* implement flow_compute.

* fix a bug.

* reverse the csr physically.

* add mini-batch test.

* add mini batch test.

* update flow_compute.

* add prop_flows

* run on specific nodes.

* test copy

* fix a bug in creating frame in NodeFlow.

* add init gcn_cv_updater.

* fix a minor bug.

* fix gcn_cv_updater.

* fix a bug.

* fix a bug in NodeFlow.

* use new h in gcn_cv_updater.

* add layer_in_degree and layer_out_degree.

* fix gcn_cv_updater for gpu.

* temp fix in NodeFlow for diff context.

* allow enabling/disabling copy back.

* add with-updater option.

* fix a bug in computing degree.

* add with-cv option.

* rename and add comments.

* fix lint complain.

* fix lint.

* avoid assert.

* remove assert.

* fix.

* fix.

* fix.

* fix.

* fix the methods in NodeFlow.

* fix lint.

* update SSE.

* remove gcn_cv_updater.

* correct comments for the schedulers.

* update comment.

* add map_to_nodeflow_nid

* address comment.

* remove duplicated test.

* fix int.

* fix comments.

* fix lint

* fix.

* replace subgraph with NodeFlow.

* move view.

* address comments.

* fix lint.

* fix lint.

* remove static_cast.

* fix docstring.

* fix comments.

* break SampleSubgraph.

* move neighbor sampling to sampler.cc

* fix comments.

* rename.

* split neighbor_list.

* address comments.

* fix.

* remove TODO.

* Create ppi.py

* Create train_ppi.py

* Update train_ppi.py

* Update train_ppi.py

* Create gat.py

* Update train.py

* Update train_ppi.py

* Update ppi.py

* Update train_ppi.py

* Update ppi.py

* Update train_ppi.py

* Update train_ppi.py

* Update ppi.py

* Update train_ppi.py

* update docs and readme

* fix rgcn tutorial

* small fix

* upd

* update gat: add minus max for softmax

* small fix

* Update prerequisites of README

* dependencies for pytorch models

* dependencies for mxnet models

* minor

* multi-process version of transformer

* lots of fix

* fix bugs and accum gradients for multiple batches

* many fixes

* minor

* upd

* set torch device

* fix bugs

* fix and minor

* comments and clean up

* uncomment viz code

* update readme.

* Revert "update readme."

This reverts commit cd5ea512059adadfcb22a615a2c42bba12f334a8.

* update.

* fix gat residual bug

* fix the residual addition; output heads; add some shape notations;

* minor

* fix the output head average

* add requests package in requirement

* two better GAT implementations

* update numbers

* use version switch for spmm

* add missing dropout and output heads

* minor spelling tweaks

* Update CONTRIBUTORS.md

* TreeLSTM MXNet example

* hybridize

* add glove download

* usability

* Update README.md

* mxgat

* pygat

* Update gat_batch.py

* add train

* Update gat_batch.py

* Update gat.py

* Update gat_batch.py

* readme

* Update and rename README to README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* fix gat.

* fix context.

* fix SSE.

* fix.

* fix.

* add cache to adj and incmat

* Fix bug in cached adj/inc

* mx gcn spmv runnable; acc debugging...

* fix bug in mx gcn that loss is not correctly calculated

* fix mx utest

* fix as requested

* use raw parameter tensors rather than dense layer

* fix dropout

* Add numbers in readme

* mxnet gcn spmv

* update readme

* fix gcn

* pytorch gcn

* update readme

* change the signature of node/edge filter

* upd filter

* Support multi-dimension node feature in SPMV

* push transformer

* remove some experimental settings

* stable version

* hotfix

* upd tutorial

* upd README

* merge

* remove redundency

* remove tqdm

* several changes

* Refactor

* Refactor

* tutorial train

* fixed a bug

* fixed perf issue

* upd

* change dir

* move un-related to contrib

* tutuorial code

* remove redundency

* upd

* upd

* upd

* upd

* improve viz

* universal done

* halt norm

* fixed a bug

* add draw graph

* fixed several bugs

* remove dependency on core

* upd format of README

* trigger

* trigger

* upd viz

* trigger

* add transformer tutorial

* fix tutorial

* fix readme

* small fix on tutorials

* url fix in readme

* fixed func link

* upd

* fix bug after moving batcher out of dgl.data

* disable mx utest

* 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