GitLab

* Standalone can run

* fix

* Add save

* Fix

* Fix

* Fix

* Fix

* debug

* test

* test

* Fix

* Fix

* log

* Fix

* fix

* Profile

* auto sync grad

* update

* add test for unsupervised dist training

* upd

* Fix lr

* Fix update

* sync

* fix

* Revert "fix"

This reverts commit d5caa7398b36125f6d6e2c742a95c6ff4298c9e9.

* Fix

* unsupervised

* Fix

* remove debug

* Add test case for dist_graph find_edges()

* Fix

* skip tensorflow test for find_edges

* Update readme

* remove some test

* upd

* Update partition_graph.py
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Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* fix bugs.

* eval on both vaidation and testing.

* add script.

* update.

* update launch.

* make train_dist.py independent.

* update readme.

* update readme.

* update readme.

* update readme.

* generate undirected graph.

* rename conf_file to part_config

* use rsync

* make train_dist independent.
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Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* Update cluster GCN README

We do not need to build metis right now.
We can use builtin metis.

* Fix gcmc mxnet

* Fix graphwriter
Co-authored-by: Ubuntu <ubuntu@ip-172-31-68-185.ec2.internal>

* Merge

* [Graph][CUDA] Graph on GPU and many refactoring (#1791)

* change edge_ids behavior and C++ impl

* fix unittests; remove utils.Index in edge_id

* pass mx and th tests

* pass tf test

* add aten::Scatter_

* Add nonzero; impl CSRGetDataAndIndices/CSRSliceMatrix

* CSRGetData and CSRGetDataAndIndices passed tests

* CSRSliceMatrix basic tests

* fix bug in empty slice

* CUDA CSRHasDuplicate

* has_node; has_edge_between

* predecessors, successors

* deprecate send/recv; fix send_and_recv

* deprecate send/recv; fix send_and_recv

* in_edges; out_edges; all_edges; apply_edges

* in deg/out deg

* subgraph/edge_subgraph

* adj

* in_subgraph/out_subgraph

* sample neighbors

* set/get_n/e_repr

* wip: working on refactoring all idtypes

* pass ndata/edata tests on gpu

* fix

* stash

* workaround nonzero issue

* stash

* nx conversion

* test_hetero_basics except update routines

* test_update_routines

* test_hetero_basics for pytorch

* more fixes

* WIP: flatten graph

* wip: flatten

* test_flatten

* test_to_device

* fix bug in to_homo

* fix bug in CSRSliceMatrix

* pass subgraph test

* fix send_and_recv

* fix filter

* test_heterograph

* passed all pytorch tests

* fix mx unittest

* fix pytorch test_nn

* fix all unittests for PyTorch

* passed all mxnet tests

* lint

* fix tf nn test

* pass all tf tests

* lint

* lint

* change deprecation

* try fix compile

* lint

* update METIDS

* fix utest

* fix

* fix utests

* try debug

* revert

* small fix

* fix utests

* upd

* upd

* upd

* fix

* upd

* upd

* upd

* upd

* upd

* trigger

* +1s

* [kernel] Use heterograph index instead of unitgraph index (#1813)

* upd

* upd

* upd

* fix

* upd

* upd

* upd

* upd

* upd

* trigger

* +1s

* [Graph] Mutation for Heterograph (#1818)

* mutation add_nodes and add_edges

* Add support for remove_edges, remove_nodes, add_selfloop, remove_selfloop

* Fix
Co-authored-by: Ubuntu <ubuntu@ip-172-31-51-214.ec2.internal>

* upd

* upd

* upd

* fix

* [Transfom] Mutable transform (#1833)

* add nodesy

* All three

* Fix

* lint

* Add some test case

* Fix

* Fix

* Fix

* Fix

* Fix

* Fix

* fix

* triger

* Fix

* fix
Co-authored-by: Ubuntu <ubuntu@ip-172-31-51-214.ec2.internal>

* [Graph] Migrate Batch & Readout module to heterograph (#1836)

* dgl.batch

* unbatch

* fix to device

* reduce readout; segment reduce

* change batch_num_nodes|edges to function

* reduce readout/ softmax

* broadcast

* topk

* fix

* fix tf and mx

* fix some ci

* fix batch but unbatch differently

* new checkk

* upd

* upd

* upd

* idtype behavior; code reorg

* idtype behavior; code reorg

* wip: test_basics

* pass test_basics

* WIP: from nx/ to nx

* missing files

* upd

* pass test_basics:test_nx_conversion

* Fix test

* Fix inplace update

* WIP: fixing tests

* upd

* pass test_transform cpu

* pass gpu test_transform

* pass test_batched_graph

* GPU graph auto cast to int32

* missing file

* stash

* WIP: rgcn-hetero

* Fix two datasety

* upd

* weird

* Fix capsuley

* fuck you

* fuck matthias

* Fix dgmg

* fix bug in block degrees; pass rgcn-hetero

* rgcn

* gat and diffpool fix
also fix ppi and tu dataset

* Tree LSTM

* pointcloud

* rrn; wip: sgc

* resolve conflicts

* upd

* sgc and reddit dataset

* upd

* Fix deepwalk, gindt and gcn

* fix datasets and sign

* optimization

* optimization

* upd

* upd

* Fix GIN

* fix bug in add_nodes add_edges; tagcn

* adaptive sampling and gcmc

* upd

* upd

* fix geometric

* fix

* metapath2vec

* fix agnn

* fix pickling problem of block

* fix utests

* miss file

* linegraph

* upd

* upd

* upd

* graphsage

* stgcn_wave

* fix hgt

* on unittests

* Fix transformer

* Fix HAN

* passed pytorch unittests

* lint

* fix

* Fix cluster gcn

* cluster-gcn is ready

* on fixing block related codes

* 2nd order derivative

* Revert "2nd order derivative"

This reverts commit 523bf6c249bee61b51b1ad1babf42aad4167f206.

* passed torch utests again

* fix all mxnet unittests

* delete some useless tests

* pass all tf cpu tests

* disable

* disable distributed unittest

* fix

* fix

* lint

* fix

* fix

* fix script

* fix tutorial

* fix apply edges bug

* fix 2 basics

* fix tutorial
Co-authored-by: yzh119 <expye@outlook.com>
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
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Co-authored-by: Ubuntu <ubuntu@ip-172-31-68-185.ec2.internal>

* update

* update

* update

* update

* slice dstdata from srcdata within nn module

* a bunch of fixes

* add comment

* fix gcmc layer

* repr for blocks

* fix

* fix context

* fix

* do not copy internal columns

* docstring

* add eval.

* extend DistTensor.

* fix.

* add barrier.

* add more print.

* add more checks in kvstore.

* fix lint.

* get all neighbors for eval.

* reorganize.

* fix.

* fix.

* fix.

* fix test.

* add reuse_if_exist.

* add test for reuse_if_exist.

* fix lint.

* fix bugs.

* fix.

* print errors of tcp socket.

* support delete tensors.

* fix lint.

* fix

* fix example
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* exit client

* update

* update

* update

* update

* update

* update

* update

* update test

* update

* update

* update

* update

* update

* update

* update

* update

* update

* fix partition and print timing.

* fix lint.
Co-authored-by: Ubuntu <ubuntu@ip-172-31-19-1.us-west-2.compute.internal>

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* fix launch script.
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* add standalone mode

* add comments.

* add tests for sampling.

* fix.

* make the code to run the standalone mode

* fix

* fix

* fix readme.

* fix.

* fix test
Co-authored-by: Chao Ma <mctt90@gmail.com>

* run dist server in dgl.

* fix bugs.

* fix example.

* check environment variables and fix lint.

* fix lint

* graphsage inductive example

* fix

* neighbor sampler data loader first commit

* more commit

* nodedataloader

* fix

* update RGCN example

* update OGB

* fixes

* fix minibatch RGCN crashing with self loop

* reverting gatconv test code

* fix

* change to new solution that doesn't require tf dataloader

* fix

* lint

* fix

* fixes

* change doc

* fix docstring

* docstring fixes

* return seeds and input nodes from data loader

* fixes

* fix test

* fix windows build problem

* add pytorch wrapper

* fixes

* add pytorch wrapper

* add unit test

* add -1 support to sample_neighbors & fix docstrings

* docstring fix

* lint

* add minibatch rgcn evaluations
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
Co-authored-by: Tong He <hetong007@gmail.com>

* fix.

* fix tests.

* fix

* add tests.

* fix.

* have default rank.

* add comment.

* fix test.

* remove check

* simplify code.

* add test.

* split data evenly.

* simplify the distributed training code.

* add comments.

* add comments.

* add train_dist.

* Fix sampling example.

* use distributed sampler.

* fix a bug in DistTensor.

* fix distributed training example.

* add graph partition.

* add command

* disable pytorch parallel.

* shutdown correctly.

* load diff graphs.

* add ip_config.txt.

* record timing for each step.

* use ogb

* add profiler.

* fix a bug.

* add train_dist.

* Fix sampling example.

* use distributed sampler.

* fix a bug in DistTensor.

* fix distributed training example.

* add graph partition.

* add command

* disable pytorch parallel.

* shutdown correctly.

* load diff graphs.

* add ip_config.txt.

* record timing for each step.

* use ogb

* add profiler.

* add Ips of the cluster.

* fix exit.

* support multiple clients.

* balance node types and edges.

* move code.

* remove run.sh

* Revert "support multiple clients."

* fix.

* update train_sampling.

* fix.

* fix

* remove run.sh

* update readme.

* update readme.

* use pytorch distributed.

* ensure all trainers run the same number of steps.

* Update README.md
Co-authored-by: Ubuntu <ubuntu@ip-172-31-16-250.us-west-2.compute.internal>

* test

* profile

* opt

* Some fix

* upd

* upd

* Add multigpu training support for graphsage unsupervised

* Add share neg

* Fix

* Add profile

* turn on eval

* upd

* Fix

* performance opt
Co-authored-by: Ubuntu <ubuntu@ip-172-31-12-103.ec2.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-14-53.ec2.internal>
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* initial version from distributed training.

This is copied from multiprocessing training.

* modify for distributed training.

* it's runnable now.

* measure time in neighbor sampling.

* simplify neighbor sampling.

* fix a bug in distributed neighbor sampling.

* allow single-machine training.

* fix a bug.

* fix a bug.

* fix openmp.

* make some improvement.

* fix.

* add prepare in the sampler.

* prepare nodeflow async.

* fix a bug.

* get id.

* simplify the code.

* improve.

* fix partition.py

* fix the example.

* add more features.

* fix the example.

* allow one partition

* use distributed kvstore.

* do g2l map manually.

* fix commandline.

* a temp script to save reddit.

* fix pull_handler.

* add pytorch version.

* estimate the time for copying data.

* delete unused code.

* fix a bug.

* print id.

* fix a bug

* fix a bug

* fix a bug.

* remove redundent code.

* revert modify in sampler.

* fix temp script.

* remove pytorch version.

* fix.

* distributed training with pytorch.

* add distributed graph store.

* fix.

* add metis_partition_assignment.

* fix a few bugs in distributed graph store.

* fix test.

* fix bugs in distributed graph store.

* fix tests.

* remove code of defining DistGraphStore.

* fix partition.

* fix example.

* update run.sh.

* only read necessary node data.

* batching data fetch of multiple NodeFlows.

* simplify gcn.

* remove unnecessary code.

* use the new copy_from_kvstore.

* update training script.

* print time in graphsage.

* make distributed training runnable.

* use val_nid.

* fix train_sampling.

* add distributed training.

* add run.sh

* add more timing.

* fix a bug.

* save graph metadata when partition.

* create ndata and edata in distributed graph store.

* add timing in minibatch training of GraphSage.

* use pytorch distributed.

* add checks.

* fix a bug in global vs. local ids.

* remove fast pull

* fix a compile error.

* update and add new APIs.

* implement more methods in DistGraphStore.

* update more APIs.

* rename it to DistGraph.

* rename to DistTensor

* remove some unnecessary API.

* remove unnecessary files.

* revert changes in sampler.

* Revert "simplify gcn."

This reverts commit 0ed3a34ca714203a5b45240af71555d4227ce452.

* Revert "simplify neighbor sampling."

This reverts commit 551c72d20f05a029360ba97f312c7a7a578aacec.

* Revert "measure time in neighbor sampling."

This reverts commit 63ae80c7b402bb626e24acbbc8fdfe9fffd0bc64.

* Revert "add timing in minibatch training of GraphSage."

This reverts commit e59dc8957a414c7df5c316f51d78bce822bdef5e.

* Revert "fix train_sampling."

This reverts commit ea6aea9a4aabb8ba0ff63070aa51e7ca81536ad9.

* fix lint.

* add comments and small update.

* add more comments.

* add more unit tests and fix bugs.

* check the existence of shared-mem graph index.

* use new partitioned graph storage.

* fix bugs.

* print error in fast pull.

* fix lint

* fix a compile error.

* save absolute path after partitioning.

* small fixes in the example

* Revert "[kvstore] support any data type for init_data() (#1465)"

This reverts commit 87b6997b

.

* fix a bug.

* disable evaluation.

* Revert "Revert "[kvstore] support any data type for init_data() (#1465)""

This reverts commit f5b8039c6326eb73bad8287db3d30d93175e5bee.

* support set and init data.

* support set and init data.

* Revert "Revert "[kvstore] support any data type for init_data() (#1465)""

This reverts commit f5b8039c6326eb73bad8287db3d30d93175e5bee.

* fix bugs.

* fix unit test.

* move to dgl.distributed.

* fix lint.

* fix lint.

* remove local_nids.

* fix lint.

* fix test.

* remove train_dist.

* revert train_sampling.

* rename funcs.

* address comments.

* address comments.

Use NodeDataView/EdgeDataView to keep track of data.

* address comments.

* address comments.

* revert.

* save data with DGL serializer.

* use the right way of getting shape.

* fix lint.

* address comments.

* address comments.

* fix an error in mxnet.

* address comments.

* add edge_map.

* add more test and fix bugs.
Co-authored-by: Zheng <dzzhen@186590dc80ff.ant.amazon.com>
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* shared memory history for multi-gpu training

* reorg
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* unsupervised graphsage first commit

* fix

* disable remove_edges and still got 0.90 performance

* optimize edgeids with multimap

* change hyperparams

* update README
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* control variate first commit

* bug fixes

* split to single and multi GPU

* update readme

* bugfix

* bugfix

* remove push

* bugfix on multi gpu

* update README
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* fix for new ntype API for blocks

* adding two new interfaces

* improve speed

* fix bugs

* upd reg test

Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* remove edge and to bipartite and graphsage with sampling

* fixes

* fixes

* fixes

* reenable multigpu training

* fixes

* compatibility in DGLGraph

* rename to compact_as_bipartite

* bugfix

* lint

* add offline inference

* skip GPU tests

* fix

* addresses comments

* fix

* fix

* fix

* more tests

* more docs and unit tests

* workaround for empty slice on empty data

* 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

* refactor

* upd mpnn

* gat

* upd

* upd sage

* upd

* upd

* upd

* upd

* upd

* add gmmconv

* upd ggnn

* upd

* upd

* upd

* upd

* add citation examples

* add README

* fix cheb

* improve doc

* formula

* upd

* trigger

* lint

* lint

* upd

* add test for transform

* add test

* check

* upd

* improve doc

* shape check

* upd

* densechebconv, currently not correct (?)

* fix cheb

* fix

* upd

* upd sgc-reddit

* upd

* trigger

* simple implemention of GraphSAGE

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