GitLab

* random walk traces generation

* remove outdated comments

* oops put in the wrong place

* explicit inline

* moving rand_r to util

* pinsage-like model on movielens

* the code runs now

* support cuda

* using readonly graph

* moving random walk to public function

* per-thread seed and openmp support

* pinsage-like model on movielens

* the code runs now

* support cuda

* using readonly graph

* using C random walk

* removing profile decorators

* param initialization

* no grad

* leaky relu fixes everything

* train and save

* WIP

* WIP

* WIP

* seems to work

* evaluation output

* swapping order of val/test and train

* debug

* hyperparam tuning

* prior/training dataset split changes

* random walk reorg

* random walk with restart

* signed comparison fix

* migrating random walk to nodeflow

* Revert "migrating random walk to nodeflow"

This reverts commit f2565347cced7c912a58a529b257c033d9f375b7.

* add README and remove dataset

* new endpoint

* lint

* lint x2

* oops forgot test

* including bpr - better for baseline

* addressing fixes

* throwing random walks out from SamplerOp class

* forgot to move RandomWalk; why did this even work?

* removing legacy garbage

* add todo

* address comments

* stupid bug fix

* call ndarrayvector converter to handle traces

* use index_select instead of __getitem__

* fix bug in dataset processing

* fix edge_type shape bug

* comments

* refactor graph conv

* docs & tests

* fix lint

* fix lint

* fix lint

* fix lint script

* fix lint

* Update

* Style fix

* Fix style

* Fix style

* Fix gpu case

* Fix for gpu case

* Hotfix edgesoftmax docs

* Handle repeated features

* Add docstring

* Set default arguments

* Remove dropout from nn.conv

* Fix

* add util fn for renaming

* revert gcn_spmv.py

* mx folder

* fix wierd bug

* fix mx

* fix lint

* simple implemention of GraphSAGE

* update the abstract method and `torch.nn` modules are more utilized

* [Model] Simplifying Graph Convolutional Networks.

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

* 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

* 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

* 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

* 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

* update readme.

* update readme

* 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

* 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

* 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