GitLab

* Fix

* Update

* Fix model save and load problem.

Add offline inference example

* Fix test

* Fix randomness problem between test runs

* Make rdf loader deterministic

* First commit

* Update

* Update splitters

* Update

* Update

* Update

* Update

* Update

* Update

* Migrate ACNN

* Fix

* Fix

* Update

* Update

* Update

* Update

* Update

* Update

* Finish classification

* Update

* Fix

* Update

* Update

* Update

* Fix

* Fix

* Fix

* Update

* Update

* Update

* trigger CI

* Fix CI

* Update

* Update

* Update

* Add default values

* Rename

* Update deprecation message

* trying to refactor IndexSelect

* partial implementation

* add index select and assign for floats as well

* move to random choice source

* more updates

* fixes

* fixes

* more fixes

* adding python impl

* fixes

* unit test

* lint

* lint x2

* lint x3

* update metapath2vec

* debugging performance

* still debugging for performance

* tuning

* switching to succvec

* redo

* revert non-uniform sampler to use vector

* still not fast

* why does this crash with OpenMP???

* because there was a data race!!!

* add documentations and remove assign op

* lint

* lint x2

* lol what have i done

* lint x3

* fix and disable gpu testing

* bugfix

* generic random walk

* reorg the random walk source code

* Update randomwalks.h

* Update randomwalks_cpu.cc

* rename file

* move internal function to anonymous ns

* reorg & docstrings

* constant restart probability

* docstring fix

* more commit

* random walk with restart, tested

* some fixes

* switch to using NDArray for choice

* massive fix & docstring

* lint x?

* lint x??

* fix

* export symbols

* skip gpu test

* addresses comments

* replaces another VecToIdArray

* add randomwalks.h to include

* replace void * with template

* several nn example

* appnp

* fix lint

* lint

* add dgi

* fix

* fix

* fix

* fff

* docs

* 111

* fix

* change init

* change result

* tiaocan+1

* fix

* fix lint

* fix

* fix

Fixes #1182 .

This is embarrassing.

* API change of kvstore

* add demo for kvstore

* update

* remove duplicated log

* change queue size

* update

* update

* update

* update

* update

* update

* update

* update

* update

* fix lint

* change name

* update

* fix lint

* update

* update

* update

* update

* change message queue size to a python argument

* change default queue size to 2GB

* OMP_NUM_THREADS=1

* add multiple NICs support for kvstore

* test

* fix lint

* update

* update

* update

* update

* update

* update

* update

* fix lint

* fix lint

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* fix lint

* API change of kvstore

* add demo for kvstore

* update

* remove duplicated log

* change queue size

* update

* update

* update

* update

* update

* update

* update

* update

* update

* fix lint

* change name

* update

* fix lint

* update

* update

* update

* update

* change message queue size to a python argument

* change default queue size to 2GB

* OMP_NUM_THREADS=1

* add multiple NICs support for kvstore

* test

* fix lint

* update

* update

* update

* update

* update

* update

* update

* fix lint

* fix lint

* update

* update

* update

* update

* API change of kvstore

* add demo for kvstore

* update

* remove duplicated log

* change queue size

* update

* update

* update

* update

* update

* update

* update

* update

* update

* fix lint

* change name

* update

* fix lint

* update

* update

* update

* update

* change message queue size to a python argument

* change default queue size to 2GB

* OMP_NUM_THREADS=1

* API change of kvstore

* add demo for kvstore

* update

* remove duplicated log

* change queue size

* update

* update

* update

* update

* update

* update

* update

* update

* update

* fix lint

* change name

* update

* fix lint

* update

* update

* update

* update

* change message queue size to a python argument

* Add several splitting methods

* Update

* Update

* Update

* Update

* Update

* Fix

* Update

* Update

* Update

* Update

* Fix

* Fix

* Fix

* Fix

* Fix

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Finally

* CI

* upd

* fix

* upd

* upd

* upd

* fix

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* Fix outdated example

* Hot fix

* upd

* fig edgebatch edges

* add test

* trigger

* add graphwriter pytorch example

* fix line break in graphwriter README

* upd

* fix

* upd

* rm redundancy:

* upd

fix minor error: GCNLayerSAGE->GraphSAGELayer

* [Example] Finish adaptive sampling

* refactor code and use argparse for command-line usage

* Update README.md

* add node_per_layer command-line argument

* Small change for kvstore api

* fix ci

* fix ci

* Performance improvment for distributed kvstore

* update

* update

* upd

* damn it

* fuck

* fuck pylint

* fudge

* remove some comments about MXNet

* upd

* upd

* damn it

* damn it

* fuck

* fuck

* upd

* upd

* pylint bastard

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* fig edgebatch edges

* add test

* trigger

* Update README.md for pytorch PinSage example.

Add noting that the PinSage model example under
example/pytorch/recommendation only work with Python 3.6+
as its dataset loader depends on stanfordnlp package
which work only with Python 3.6+.

* Provid a frame agnostic API to test nn modules on both CPU and CUDA side.

1. make dgl.nn.xxx frame agnostic
2. make test.backend include dgl.nn modules
3. modify test_edge_softmax of test/mxnet/test_nn.py and
    test/pytorch/test_nn.py work on both CPU and GPU

* Fix style

* Delete unused code

* Make agnostic test only related to tests/backend

1. clear all agnostic related code in dgl.nn
2. make test_graph_conv agnostic to cpu/gpu

* Fix code style

* fix

* doc

* Make all test code under tests.mxnet/pytorch.test_nn.py
work on both CPU and GPU.

* Fix syntex

* Remove rand

* Add TAGCN nn.module and example

* Now tagcn can run on CPU.

* Add unitest for TGConv

* Fix style

* For pubmed dataset, using --lr=0.005 can achieve better acc

* Fix style

* Fix some descriptions

* trigger

* Fix doc

* Add nn.TGConv and example

* Fix bug

* Update data in mxnet.tagcn test acc.

* Fix some comments and code

* delete useless code

* Fix namming

* Fix bug

* Fix bug

* Add test for mxnet TAGCov

* Add test code for mxnet TAGCov

* Update some docs

* Fix some code

* Update docs dgl.nn.mxnet

* Update weight init

* Fix

* reproduce the bug

* Fix concurrency bug reported at #755.
Also make test_shared_mem_store.py more deterministic.

* Update test_shared_mem_store.py

* Update dmlc/core

* networkx >= 2.4 will break our examples

* Update tutorials/requirements

* fix selfloop edges

* upd version

* Change Byte to Bool for training masks

* Check if module has Bool, otherwise use Byte

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Fix

* Fix

* Update

* Fix style

* Update

* Update

* Fix

* Update

* Update

* Refactor

* Add note

* Update

* CI

* Update

* Update

* rrn model and sudoku

* add README

* refine the code, add doc strings

* add sudoku solver

* add example for sudoku_solver

* ggnn example

* Rewrite README file

* fix typos

* convert np.ndarray to backend tensor

* add datasets

* add qm7

* add dataset

* add dataset

* fix

* change ppi

* tu dataset

* add datasets

* fix

* fix

* fix

* fix

* add docstring

* docs

* doc

* new hetero RGCN

* bgs running

* fix gpu

* am dataset

* fix bug in label preparation

* Fix AM training; add result

* rm sym link

* new embed layer; mutag

* mutag matched; other fix

* minor fix

* dataset refactor

* new data loading

* rm old files

* refactor

* docstring

* include literal nodes in AIFB dataset

* address comments

* docstring

* initial commit of cluster GCN

* update readme

* fix small bugs running ppi

* nearly sota ppi training script&update readme

* rm unused imports&add shebang line to scripts

* minor comments&readme appended

* add rnd seed control&update readme

* Add HAN

* Fix

* WIP; load raw ACM dataset

* DGL's own preprocessing with metapath coalescer

* various fixes

* comparison against simple logistic regression

* rename

* fix test