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

* to simple

* WIP: multigraph flag

* graph index refactor; pass basic testing

* graph index refactor; pass basic testing

* fix bug in to_simple; pass torch test

* fix mx utest

* fix example

* fix lint

* fix ci

* poke ci

* poke ci

* WIP

* poke ci

* poke ci

* poke ci

* change ci workspace

* poke ci

* poke ci

* poke ci

* poke ci

* delete ci

* use enum for multigraph flag

* Update README.md for the demo of distributed sampler

* Update README.MD of demo for distributed sampler

* update

* update

* update demo

* load mxnet csr.

* enable load large csr.

* fix

* fix.

* fix int overflow.

* fix test.

* update

* update

* update

* add sender

* update

* remove duplicate cpde

* fix.

* use inplace.

* move to shared memory graph store.

* fix.

* add more unit tests.

* fix.

* fix test.

* fix test.

* disable test.

* fix.

* 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

* update

* update

* update

* update num_hops

* fix bug

* update

* report numbers of distributed training in AMLC giant graph paper

* add init_ndata and init_edata in DGLGraph.

* adjust SharedMemoryGraph API.

* print warning.

* fix comment.

* update example

* fix.

* fix examples.

* add unit tests.

* add comments.

* fix.

* add comment.

* remove.

* temp fix.

* initialize for shared memory.

* fix graphsage.

* fix gcn.

* add more unit tests.

* add more tests.

* avoid creating shared-memory exclusively.

* redefine remote initializer.

* improve initializer.

* fix unit test.

* fix lint.

* fix lint.

* initialize data in the graph store server properly.

* fix test.

* fix test.

* fix test.

* small fix.

* add comments.

* cleanup server.

* test graph store with a random port.

* print.

* print to stderr.

* test1

* test2

* remove comment.

* adjust the initializer signature.

* reorganize sampling code.

* add multi-process training.

* speed up gcn_cv

* fix graphsage_cv.

* add new API in graph store.

* update barrier impl.

* support both local and distributed training.

* fix multiprocess train.

* fix.

* fix barrier.

* add script for loading data.

* multiprocessing sampling.

* accel training.

* replace pull with spmv for speedup.

* nodeflow copy from parent with context.

* enable GPU.

* fix a bug in graph store.

* enable multi-GPU training.

* fix lint.

* add comments.

* rename to run_store_server.py

* fix gcn_cv.

* fix a minor bug in sampler.

* handle error better in graph store.

* improve graphsage_cv for distributed mode.

* update README.

* fix.

* update.

* Change Distributed Sampler API

* fix lint

* fix lint

* update demo

* update

* update

* update

* update demo

* update demo

* [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

* reorganize sampling code.

* speedup gcn_ns.

* speed up gcn_cv

* fix graphsage_cv.

* undo the modification.

* accel training.

* update readme.

* 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

* Refactoring network API

* update demo

* update

* update demo

* update demo

* add num_sender

* update

* fix lint

* fix lint

* fix lint

* update

* 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

* add C++ rpc infrastructure and distributed sampler

* update

* update lint

* update lint

* update lint

* update

* update

* update

* updare

* update

* update

* update

* update serialize and unittest

* update serialize

* lint

* update

* update

* update

* update

* update

* update

* update unittest

* put Finalize() to __del__

* update unittest

* update

* delete buffer in Finalize

* update unittest

* update unittest

* update unittest

* update unittest

* update

* update

* fix small bug

* windows socket impl

* update API

* fix bug in serialize

* fix bug in serialzie

* set parent graph

* update

* update

* update

* update

* update

* update

* fix lint

* fix lint

* fix

* fix windows compilation error

* fix windows error

* change API to lower-case

* update test

* fix typo

* update

* add SamplerPool

* add SamplerPool

* update

* update test

* update

* update

* update

* update

* add example

* update

* update

* add distributed sampler demo

* add index

* update demo of distributed sampler

* fix lower-case

* print subg index

* update README.md

* update

* remove --gpu args

* 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

* enable cython

* add helper function and data structure for void_p vector return

* move sampler from graph index to contrib.sampling

* WIP

* WIP

* refactor layer sampling

* pass tests

* fix lint

* fix graphsage

* remove comments

* pickle test

* fix comments

* update dev guide for cython build

* use index_select instead of __getitem__

* fix bug in dataset processing

* fix edge_type shape bug

* comments

* don't return aux_info.

* fix sampler test.

* fix sse.

* fix.

* add comment.

* neighbor sampling draft

* val/test acc

* control variate draft

* control variate

* update

* fix new_history

* maintain aggregated history while updating new history

* preprocess the first layer, change push to pull

* update

* fix subg_degree

* nodeflow

* clear

* readme

* doc and unittest for self loop

* address comments

* rename

* update

* fix

* Update node_flow.py

* Update node_flow.py

* 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