GitLab

* First update to fix two examples

* Update to fix RGCN/graphsage example and dataloader

* Update

* rename

* Update node_classification.py

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

* enable UVA sampling with CPU indices

* add docs

* add more docs

* lint

* fix

* fix

* better error message

* use mp.Barrier instead of queues

* revert

* revert

* oops

* revert dgl.multiprocessing.spawn

* Update pytorch.py

* fix multi-gpu rgcn example

* remove dgl.multiprocessing in turorials

* add a comment
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

* huuuuge update

* remove

* lint

* lint

* fix

* what happened to nccl

* update multi-gpu unsupervised graphsage example

* replace most of the dgl.mp.process with torch.mp.spawn

* update if condition for use_uva case

* update user guide

* address comments

* incorporating suggestions from @jermainewang

* oops

* fix tutorial to pass CI

* oops

* fix again
Co-authored-by: Xin Yao <xiny@nvidia.com>

* WIP: TypedLinear and new RelGraphConv

* wip

* further simplify RGCN

* a bunch of tweak for performance; add basic cpu support

* update on segmm

* wip: segment.cu

* new backward kernel works

* fix a bunch of bugs in kernel; leave idx_a for future

* add nn test for typed_linear

* rgcn nn test

* bugfix in corner case; update RGCN README

* doc

* fix cpp lint

* fix lint

* fix ut

* wip: hgtconv; presorted flag for rgcn

* hgt code and ut; WIP: some fix on reorder graph

* better typed linear init

* fix ut

* fix lint; add docstring

* Update (#5)

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* FIx

* Try

* Update

* Update

* Update

* Fix

* Update

* Fix

* Fix

* Fix

* Fix

* Update

* Fix

* Update

* Update

* Update

* Fix

* Fix

* Update

* Update

* Update

* Update

* Fix

* Fix

* Fix

* Update

* Update

* Update

* Update

* Update

* Update README.md

* Update

* Fix

* Update

* Update

* Fix

* Fix

* Fix

* Update

* Update

* Update
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* Update

* Update

* Fix

* Update

* Update

* Update

* Fix

* Update

* Update

* Update

* Update

* Update

* Update

* CI
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Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>

* initial update

* more

* more

* multi-gpu example

* cluster gcn, finalize homogeneous

* more explanation

* fix

* bunch of fixes

* fix

* RGAT example and more fixes

* shadow-gnn sampler and some changes in unit test

* fix

* wth

* more fixes

* remove shadow+node/edge dataloader tests for possible ux changes

* lints

* add legacy dataloading import just in case

* fix

* update pylint for f-strings

* fix

* lint

* lint

* lint again

* cherry-picking commit fa9f494

* oops

* fix

* add sample_neighbors in dist_graph

* fix

* lint

* fix

* fix

* fix

* fix tutorial

* fix

* fix

* fix

* fix warning

* remove debug

* add get_foo_storage apis

* lint

Co-authored-by: Ubuntu <ubuntu@ip-172-31-30-164.us-west-2.compute.internal>

Remove self-loops and duplicate edges before ParMETIS and restore when converting to DGLGraph (#3472)

* save self-loops and duplicated edges separately.

* [BugFix] sort graph by dgl.ETYPE

* fix bugs in verify script

* fix verify logic

* refine README
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-2-66.ec2.internal>

* Added code for Rectifying (TypeError: unhashable type: 'slice') when copying file

* 1) added distributed preprocessing code to create ParMetis Input from CSV files
2) add code to run pm_dglpart on multiple machines
3) added support for recreating heteregenous graph from homo geneous graph based on dropped edges, as ParMetis currently only supports homogeneous graphs

* move to pandas

* Added comments and remove drop_duplicates as it was redundant

* Addressed Pr Comments

* Rename variable

* Added comment

* Added comment

* updated ReadMe
Co-authored-by: Ankit Garg <gaank@amazon.com>
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* fix.

* fix.

* fix.

* fix.

* Fix test

* Deprecate old DistEmbedding impl, use synchronized embedding impl

* Basic imple of heterogeneous on homogenenous sampling

* make pass

* Pass C++ test

* Add python test code

* lint

* lint

* Add MultiLayerEtypeNeighborSampler

* Add unitest for single machine dataloader

* Add dist dataloader test for edge type sampler

* Fix lint

* fix

* support for per etype sample

* Fix some bug and enable distributed training with per edge sample

* fix

* Now distributed training works

* turn off some mxnet

* turn off mxnet for some dist test

* fix

* upd

* upd according to the comments

* Fix

* Fix test and now distributed works.

* upd

* upd

* Fix

* Fix bug

* remove dead code.

* upd

* Fix

* upd

* Fix
Co-authored-by: Ubuntu <ubuntu@ip-172-31-71-112.ec2.internal>
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Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* support hetero RGCN.

* fix.

* simplify code.

* sample_neighbors return heterograph directly.

* avoid using to_heterogeneous.

* compute canonical etypes in advance.

* fix tests.

* fix.

* fix distributed data loader for heterograph.

* use NodeDataLoader.

* fix bugs in partitioning on heterogeneous graphs.

* fix lint.

* fix tests.

* fix.

* fix.

* fix bugs.

* fix tests.

* fix.

* enable coo for distributed.

* fix.

* fix.

* fix.

* fix.

* fix.
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Co-authored-by: Zheng <dzzhen@3c22fba32af5.ant.amazon.com>

* fix.

* fix.

* fix.

* fix.

* Fix test

* Deprecate old DistEmbedding impl, use synchronized embedding impl

* update doc
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Co-authored-by: Da Zheng <zhengda1936@gmail.com>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

* fix bugs in partitioning on heterogeneous graphs.

* fix.

* fix.

* fix example.

* fix.

* fix test.

* fix.

* fix.

* fix.

* fix tests.
Co-authored-by: Ubuntu <ubuntu@ip-172-31-71-112.ec2.internal>
Co-authored-by: Zheng <dzzhen@3c22fba32af5.ant.amazon.com>

* Fix example datasplitting

* Remove left-over split parameter

* Remove unused parameter

* Set epoch when using multiple GPUs
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

[Performance] Perform to_block on the GPU when the dataloader is created with a GPU `device`. (#3016)

* add output device for dataloading

* Update dataloader

* Get sampler device from dataloader

* Fix line length

* Update examples

* Fix to_block GPU for empty relation types

* Handle the case where the DistGraph has None for the underlying graph
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* Split from NCCL PR

* Fix type in comment

* Expand documentation for sparse_all_to_all_push

* Restore previous behavior in example

* Re-work optimizer to use NCCL based on gradient location

* Allow for running with embedding on CPU but using NCCL for gradient exchange

* Optimize single partition case

* Fix pylint errors

* Add missing include

* fix gradient indexing

* Fix line continuation

* Migrate 'first_step'

* Skip tests without enough GPUs to run NCCL

* Improve empty tensor handling for pytorch 1.5

* Fix indentation

* Allow multiple NCCL communicator to coexist

* Improve handling of empty message

* Update python/dgl/nn/pytorch/sparse_emb.py
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* Update python/dgl/nn/pytorch/sparse_emb.py
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* Keepy empty tensor dimensionaless

* th.empty -> th.tensor

* Preserve shape for empty non-zero dimension tensors

* Use shared state, when embedding is shared

* Add support for gathering an embedding

* Fix typo

* Fix more typos

* Fix backend call

* Use NodeDataLoader to take advantage of ddp

* Update training script to share memory

* Only squeeze last dimension

* Better handle empty message

* Keep embedding on the target device GPU if dgl_sparse if false in RGCN example

* Fix typo in comment

* Add asserts

* Improve documentation in example
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

corrected docstring, the model uses two R-GCN layers
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* standardizing thread_wrapped_func

* lints

* Update __init__.py

* Draft for sparse emb

* add some notes

* Fix

* Add sparse optim for dist pytorch

* Update test

* Fix

* upd

* upd

* Fix

* Fix

* Fix bug

* add transductive exmpale

* Fix example

* Some fix

* Upd

* Fix lint

* lint

* lint

* lint

* upd

* Fix lint

* lint

* upd

* remove dead import

* update

* lint

* update unitest

* update example

* Add adam optimizer

* Add unitest and update data

* upd

* upd

* upd

* Fix docstring and fix some bug in example code

* Update rgcn readme
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Co-authored-by: Ubuntu <ubuntu@ip-172-31-73-81.ec2.internal>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

* remove num_workers.

* remove num_workers.

* remove num_workers.

* remove num-servers.

* update error message.

* update docstring.

* fix docs.

* fix tests.

* fix test.

* fix.

* print messages in test.

* fix.

* fix test.

* fix.
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-132.us-west-1.compute.internal>

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

* Address bug where epochs exceed specified limit

* fix spacing

* support gpu training.

* remove unnecessary arguments.

* update README.

* update time measurement.

* add zero_grad.
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-132.us-west-1.compute.internal>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

* Update README to use NFS, rather than copying files

* Update README.md

* Update README.md

* Update README.md

* Add ParMetis

* Update README.md

* fix directory.

* fix

* redo.

* fix.

* update.

* add more descriptions
Co-authored-by: Da Zheng <zhengda1936@gmail.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-132.us-west-1.compute.internal>

* add convert.

* fix.

* add write_mag.

* fix convert_partition.py

* write data.

* use pyarrow to read.

* update write_mag.py

* fix convert_partition.py.

* load node/edge features when necessary.

* reshuffle nodes.

* write mag correctly.

* fix a bug: inner nodes in a partition might be empty.

* fix bugs.

* add verify code.

* insert reverse edges.

* fix a bug.

* add get node/edge data.

* add instructions.

* remove unnecessary argument.

* update distributed preprocessing.

* fix readme.

* fix.

* fix.

* fix.

* fix readme.

* fix doc.

* fix.

* update readme

* update doc.

* update readme.
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* Fix pytorch TCP kvstore bug

* lint

* Fix

* upd

* Fix lint

* Fix

* trigger

* fix
Co-authored-by: Ubuntu <ubuntu@ip-172-31-56-220.ec2.internal>

* Add sparse embedding for dgl and update rgcn example

* upd

* Fix

* Revert "Fix"

This reverts commit 4da87cdfb8b8c3506b7fc7376cd2385ba8045c2a.

* Fix

* upd

* upd

* Fix

* Add unitest and update impl

* fix

* Clean up rgcn example code

* upd

* upd

* update

* Fix

* update score

* sparse for sage

* remove model sparse

* upd

* upd

* remove global norm

* revert delete model_sparse.py

* update according to comments

* Fix doc

* upd

* Fix test

* upd

* lint

* lint

* lint

* upd

* upd

* clean up
Co-authored-by: Ubuntu <ubuntu@ip-172-31-56-220.ec2.internal>

* Distributed heterograph (#3)

* heterogeneous graph partition.

* fix graph partition book for heterograph.

* load heterograph partitions.

* update DistGraphServer to support heterograph.

* make DistGraph runnable for heterograph.

* partition a graph and store parts with homogeneous graph structure.

* update DistGraph server&client to use homogeneous graph.

* shuffle node Ids based on node types.

* load mag in heterograph.

* fix per-node-type mapping.

* balance node types.

* fix for homogeneous graph

* store etype for now.

* fix data name.

* fix a bug in example.

* add profiler in rgcn.

* heterogeneous RGCN.

* map homogeneous node ids to hetero node ids.

* fix graph partition book.

* fix DistGraph.

* shuffle eids.

* verify eids and their mappings when loading a partition.

* Id map from homogneous Ids to per-type Ids.

* verify partitioned results.

* add test for distributed sampler.

* add mapping from per-type Ids to homogeneous Ids.

* update example.

* fix DistGraph.

* Revert "add profiler in rgcn."

This reverts commit 36daaed8b660933dac8f61a39faec3da2467d676.

* add tests for homogeneous graphs.

* fix a bug.

* fix test.

* fix for one partition.

* fix for standalone training and evaluation.

* small fix.

* fix two bugs.

* initialize projection matrix.

* small fix on RGCN.

* Fix rgcn performance (#17)
Co-authored-by: Ubuntu <ubuntu@ip-172-31-62-171.ec2.internal>

* fix lint.

* fix lint.

* fix lint.

* fix lint.

* fix lint.

* fix lint.

* fix.

* fix test.

* fix lint.

* test partitions.

* remove redundant test for partitioning.

* remove commented code.

* fix partition.

* fix tests.

* fix RGCN.

* fix test.

* fix test.

* fix test.

* fix.

* fix a bug.

* update dmlc-core.

* fix.

* fix rgcn.

* update readme.

* add comments.
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Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-62-171.ec2.internal>

* fix.

* fix.

* add div_int.

* fix.

* fix.

* fix lint.

* fix.

* fix.

* fix.

* adjust.

* move code.

* handle heterograph.

* return pytorch tensor in GPB.

* remove some tests in example.

* add to_block for distributed training.

* use distributed to_block.

* remove unnecessary function in DistGraph.

* remove distributed to_block.

* use pytorch tensor.

* fix a bug in ntypes and etypes.

* enable norm.

* make the data loader compatible with the old format.

* fix.

* add comments.

* fix a bug.

* add test for heterograph.

* support partition without reshuffle.

* add test.

* support partition without reshuffle.

* fix.

* add test.

* fix bugs.

* fix lint.

* fix dataset.

* fix for mxnet.

* update docstring.

* rename to floor_div

* avoid exposing NodePartitionPolicy and EdgePartitionPolicy.

* fix docstring.

* fix error.

* fixes.

* fix comments.

* rename.

* rename.

* explain IdMap.

* fix docstring.

* fix docstring.

* update docstring.

* remove the code of returning heterograph.

* remove argument.

* fix example.

* make GraphPartitionBook an abstract class.

* fix.

* fix.

* fix a bug.

* fix a bug in example

* fix a bug

* reverse heterograph sampling.

* temp fix.

* fix lint.

* Revert "temp fix."

This reverts commit c450717b9f578b8c48769c675f2a19d6c1e64381.

* compute norm.

* Revert "reverse heterograph sampling."

This reverts commit bd6deb7f52998de76508f800441ff518e2fadcb9.

* fix.

* move id_map.py

* remove check

* add more comments.

* update docstring.
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Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-62-171.ec2.internal>

* Update gatedgraphconv.py

* Update entity_classify.py

* Update data-process.rst

* Update reading_data.py

* Update data-process.rst

* Update utils.py

* Update knowledge_graph.py

* Update entity_classify.py

* Update rdf.py

* Update entity_classify_mb.py

* Update test_classify.py

* Update tensor.py

* Update sparse.py

* Update entity_classify_mp.py

* Update 6_line_graph.py