GitLab

* all pytorch examples

* scan through mxnet examples

* change reddit data

* tweak numerical range for unittest

* fix ci

* fix ci

* fix

* add seed to workaround

* fix gat code to use latest edge softmax module

* avoid transpose

* update README

* use edge_softmax op

* mxnet edge softmax op

* mxnet gat

* update README

* fix unittest

* fix ci

* fix mxnet nn test; relax criteria for prod reducer

* Update README.md for the demo of distributed sampler

* Update README.MD of demo for distributed sampler

* update

* update

* update demo

* update

* update

* update

* add sender

* update

* remove duplicate cpde

* update

* update

* re-use single-machine code

* update

* use relative path

* update

* update

* update

* add __init__.py

* add __init__.py

* import sys, os

* fix typo

* update

* [Model] Add edge dropout to APPNP

[Model] Add edge dropout to APPNP

* [Model] Refactor the sampling examples (#498)

* reorganize sampling code.

* speedup gcn_ns.

* speed up gcn_cv

* fix graphsage_cv.

* undo the modification.

* accel training.

* update readme.

* [Model] Add edge dropout to APPNP

[Model] Add edge dropout to APPNP

update

* add gin model

* convert dataset.py to data_ont_the_fly way and put it into dgl.data module

* convert dataset.py to data_ont_the_fly way and put it into dgl.data module
python code checked

* modified document and reference TUDataset; checked python part and bypass cpp part due to error

* change tensor to numpy in dataset and transform in collate@Dataloader

* Change minor format issue

Change minor format issue

* moved logging; adjusted tqdm etc

* Update gcn_mp.py

* Update train.py

* Update train.py

* Update train.py

* Update gat_batch.py

* Update gat_batch.py

* Update gcn_mp.py

* [Model] Add APPNP model

* update

* Revert "update"

This reverts commit a8e42d19c8b421fb382305a8f04d7426e78ea53c.

* update

* Update appnp.py

* 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* remove outdated comments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