GitLab

* Other

* revert

---------
Co-authored-by: Ubuntu <ubuntu@ip-172-31-28-63.ap-northeast-1.compute.internal>

* [Doc] update doc page for distributed partition pipeline

* update

* Update from master (#4584)

* [Example][Refactor] Refactor graphsage multigpu and full-graph example (#4430)

* Add refactors for multi-gpu and full-graph example

* Fix format

* Update

* Update

* Update

* [Cleanup] Remove async_transferer (#4505)

* Remove async_transferer

* remove test

* Remove AsyncTransferer
Co-authored-by: Xin Yao <xiny@nvidia.com>
Co-authored-by: Xin Yao <yaox12@outlook.com>

* [Cleanup] Remove duplicate entries of CUB submodule   (issue# 4395) (#4499)

* remove third_part/cub

* remove from third_party
Co-authored-by: Israt Nisa <nisisrat@amazon.com>
Co-authored-by: Xin Yao <xiny@nvidia.com>

* [Bug] Enable turn on/off libxsmm at runtime (#4455)

* enable turn on/off libxsmm at runtime by adding a global config and related API
Co-authored-by: Ubuntu <ubuntu@ip-172-31-19-194.ap-northeast-1.compute.internal>

* [Feature] Unify the cuda stream used in core library (#4480)

* Use an internal cuda stream for CopyDataFromTo

* small fix white space

* Fix to compile

* Make stream optional in copydata for compile

* fix lint issue

* Update cub functions to use internal stream

* Lint check

* Update CopyTo/CopyFrom/CopyFromTo to use internal stream

* Address comments

* Fix backward CUDA stream

* Avoid overloading CopyFromTo()

* Minor comment update

* Overload copydatafromto in cuda device api
Co-authored-by: xiny <xiny@nvidia.com>

* [Feature] Added exclude_self and output_batch to knn graph construction (Issues #4323 #4316) (#4389)

* * Added "exclude_self" and "output_batch" options to knn_graph and segmented_knn_graph
* Updated out-of-date comments on remove_edges and remove_self_loop, since they now preserve batch information

* * Changed defaults on new knn_graph and segmented_knn_graph function parameters, for compatibility; pytorch/test_geometry.py was failing

* * Added test to ensure dgl.remove_self_loop function correctly updates batch information

* * Added new knn_graph and segmented_knn_graph parameters to dgl.nn.KNNGraph and dgl.nn.SegmentedKNNGraph

* * Formatting

* * Oops, I missed the one in segmented_knn_graph when I fixed the similar thing in knn_graph

* * Fixed edge case handling when invalid k specified, since it still needs to be handled consistently for tests to pass
* Fixed context of batch info, since it must match the context of the input position data for remove_self_loop to succeed

* * Fixed batch info resulting from knn_graph when output_batch is true, for case of 3D input tensor, representing multiple segments

* * Added testing of new exclude_self and output_batch parameters on knn_graph and segmented_knn_graph, and their wrappers, KNNGraph and SegmentedKNNGraph, into the test_knn_cuda test

* * Added doc comments for new parameters

* * Added correct handling for uncommon case of k or more coincident points when excluding self edges in knn_graph and segmented_knn_graph
* Added test cases for more than k coincident points

* * Updated doc comments for output_batch parameters for clarity

* * Linter formatting fixes

* * Extracted out common function for test_knn_cpu and test_knn_cuda, to add the new test cases to test_knn_cpu

* * Rewording in doc comments

* * Removed output_batch parameter from knn_graph and segmented_knn_graph, in favour of always setting the batch information, except in knn_graph if x is a 2D tensor
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* [CI] only known devs are authorized to trigger CI (#4518)

* [CI] only known devs are authorized to trigger CI

* fix if author is null

* add comments

* [Readability] Auto fix setup.py and update-version.py (#4446)

* Auto fix update-version

* Auto fix setup.py

* Auto fix update-version

* Auto fix setup.py

* [Doc] Change random.py to random_partition.py in guide on distributed partition pipeline (#4438)

* Update distributed-preprocessing.rst

* Update
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>

* fix unpinning when tensoradaptor is not available (#4450)

* [Doc] fix print issue in tutorial (#4459)

* [Example][Refactor] Refactor RGCN example (#4327)

* Refactor full graph entity classification

* Refactor rgcn with sampling

* README update

* Update

* Results update

* Respect default setting of self_loop=false in entity.py

* Update

* Update README

* Update for multi-gpu

* Update

* [doc] fix invalid link in user guide (#4468)

* [Example] directional_GSN for ogbg-molpcba (#4405)

* version-1

* version-2

* version-3

* update examples/README

* Update .gitignore

* update performance in README, delete scripts

* 1st approving review

* 2nd approving review
Co-authored-by: Mufei Li <mufeili1996@gmail.com>

* Clarify the message name, which is 'm'. (#4462)
Co-authored-by: Ubuntu <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>
Co-authored-by: Rhett Ying <85214957+Rhett-Ying@users.noreply.github.com>

* [Refactor] Auto fix view.py. (#4461)
Co-authored-by: Ubuntu <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* [Example] SEAL for OGBL (#4291)

* [Example] SEAL for OGBL

* update index

* update

* fix readme typo

* add seal sampler

* modify set ops

* prefetch

* efficiency test

* update

* optimize

* fix ScatterAdd dtype issue

* update sampler style

* update
Co-authored-by: Quan Gan <coin2028@hotmail.com>

* [CI] use https instead of http (#4488)

* [BugFix] fix crash due to incorrect dtype in dgl.to_block() (#4487)

* [BugFix] fix crash due to incorrect dtype in dgl.to_block()

* fix test failure in TF

* [Feature] Make TensorAdapter Stream Aware (#4472)

* Allocate tensors in DGL's current stream

* make tensoradaptor stream-aware

* replace TAemtpy with cpu allocator

* fix typo

* try fix cpu allocation

* clean header

* redirect AllocDataSpace as well

* resolve comments

* [Build][Doc] Specify the sphinx version (#4465)
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* reformat

* reformat

* Auto fix update-version

* Auto fix setup.py

* reformat

* reformat
Co-authored-by: Ubuntu <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>
Co-authored-by: Rhett Ying <85214957+Rhett-Ying@users.noreply.github.com>
Co-authored-by: Mufei Li <mufeili1996@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>
Co-authored-by: Xin Yao <xiny@nvidia.com>
Co-authored-by: Chang Liu <chang.liu@utexas.edu>
Co-authored-by: Zhiteng Li <55398076+ZHITENGLI@users.noreply.github.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: rudongyu <ru_dongyu@outlook.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>

* Move mock version of dgl_sparse library to DGL main repo (#4524)

* init

* Add api doc for sparse library

* support op btwn matrices with differnt sparsity

* Fixed docstring

* addresses comments

* lint check

* change keyword format to fmt
Co-authored-by: Israt Nisa <nisisrat@amazon.com>

* [DistPart] expose timeout config for process group (#4532)

* [DistPart] expose timeout config for process group

* refine code

* Update tools/distpartitioning/data_proc_pipeline.py
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* [Feature] Import PyTorch's CUDA stream management (#4503)

* add set_stream

* add .record_stream for NDArray and HeteroGraph

* refactor dgl stream Python APIs

* test record_stream

* add unit test for record stream

* use pytorch's stream

* fix lint

* fix cpu build

* address comments

* address comments

* add record stream tests for dgl.graph

* record frames and update dataloder

* add docstring

* update frame

* add backend check for record_stream

* remove CUDAThreadEntry::stream

* record stream for newly created formats

* fix bug

* fix cpp test

* fix None c_void_p to c_handle

* [examples]educe memory consumption (#4558)

* [examples]educe memory consumption

* reffine help message

* refine

* [Feature][REVIEW] Enable DGL cugaph nightly CI  (#4525)

* Added cugraph nightly scripts

* Removed nvcr.io//nvidia/pytorch:22.04-py3 reference
Co-authored-by: Rhett Ying <85214957+Rhett-Ying@users.noreply.github.com>

* Revert "[Feature][REVIEW] Enable DGL cugaph nightly CI  (#4525)" (#4563)

This reverts commit ec171c64

.

* [Misc] Add flake8 lint workflow. (#4566)

* Add pyproject.toml for autopep8.

* Add pyproject.toml for autopep8.

* Add flake8 annotation in workflow.

* remove

* add

* clean up
Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* [Misc] Try use official pylint workflow. (#4568)

* polish update_version

* update pylint workflow.

* add

* revert.
Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* [CI] refine stage logic (#4565)

* [CI] refine stage logic

* refine

* refine

* remove (#4570)
Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* Add Pylint workflow for flake8. (#4571)

* remove

* Add pylint.
Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* [Misc] Update the python version in Pylint workflow for flake8. (#4572)

* remove

* Add pylint.

* Change the python version for pylint.
Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* Update pylint. (#4574)
Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* [Misc] Use another workflow. (#4575)

* Update pylint.

* Use another workflow.
Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* Update pylint. (#4576)
Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* Update pylint.yml

* Update pylint.yml

* Delete pylint.yml

* [Misc]Add pyproject.toml for autopep8 & black. (#4543)

* Add pyproject.toml for autopep8.

* Add pyproject.toml for autopep8.
Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* [Feature] Bump DLPack to v0.7 and decouple DLPack from the core library (#4454)

* rename `DLContext` to `DGLContext`

* rename `kDLGPU` to `kDLCUDA`

* replace DLTensor with DGLArray

* fix linting

* Unify DGLType and DLDataType to DGLDataType

* Fix FFI

* rename DLDeviceType to DGLDeviceType

* decouple dlpack from the core library

* fix bug

* fix lint

* fix merge

* fix build

* address comments

* rename dl_converter to dlpack_convert

* remove redundant comments
Co-authored-by: Chang Liu <chang.liu@utexas.edu>
Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>
Co-authored-by: Xin Yao <xiny@nvidia.com>
Co-authored-by: Xin Yao <yaox12@outlook.com>
Co-authored-by: Israt Nisa <neesha295@gmail.com>
Co-authored-by: Israt Nisa <nisisrat@amazon.com>
Co-authored-by: peizhou001 <110809584+peizhou001@users.noreply.github.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-19-194.ap-northeast-1.compute.internal>
Co-authored-by: ndickson-nvidia <99772994+ndickson-nvidia@users.noreply.github.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: Rhett Ying <85214957+Rhett-Ying@users.noreply.github.com>
Co-authored-by: Hongzhi (Steve), Chen <chenhongzhi.nkcs@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>
Co-authored-by: Zhiteng Li <55398076+ZHITENGLI@users.noreply.github.com>
Co-authored-by: rudongyu <ru_dongyu@outlook.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>
Co-authored-by: Vibhu Jawa <vibhujawa@gmail.com>

* [Deprecation] Dataset Attributes (#4546)

* Update

* CI

* CI

* Update
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>

* [Example] Bug Fix (#4665)

* Update

* CI

* CI

* Update

* Update
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>

* Update

* Update (#4724)
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>

* change DGLHeteroGraph to DGLGraph in DOC

* revert c change
Co-authored-by: Mufei Li <mufeili1996@gmail.com>
Co-authored-by: Chang Liu <chang.liu@utexas.edu>
Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>
Co-authored-by: Xin Yao <xiny@nvidia.com>
Co-authored-by: Xin Yao <yaox12@outlook.com>
Co-authored-by: Israt Nisa <neesha295@gmail.com>
Co-authored-by: Israt Nisa <nisisrat@amazon.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-19-194.ap-northeast-1.compute.internal>
Co-authored-by: ndickson-nvidia <99772994+ndickson-nvidia@users.noreply.github.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: Rhett Ying <85214957+Rhett-Ying@users.noreply.github.com>
Co-authored-by: Hongzhi (Steve), Chen <chenhongzhi.nkcs@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>
Co-authored-by: Zhiteng Li <55398076+ZHITENGLI@users.noreply.github.com>
Co-authored-by: rudongyu <ru_dongyu@outlook.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>
Co-authored-by: Vibhu Jawa <vibhujawa@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-16-19.ap-northeast-1.compute.internal>

* add bf16 specializations

* remove SWITCH_BITS

* enable amp for bf16

* remove SWITCH_BITS for cpu kernels

* enbale bf16 based on CUDART

* fix compiling for sm<80

* fix cpu build

* enable unit tests

* update doc

* disable test for CUDA < 11.0

* address comments

* address comments

* Update distributed-preprocessing.rst

* Another typo for the writes edge type

* [doc] add doc for saving original node/edge IDs in dist part pipeline

* move added docs into advanced topic

* fix ypo

* refine

* Update distributed-preprocessing.rst

* Update
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>

* Update

* rollback for partition_algo/random.py
Co-authored-by: Ubuntu <ubuntu@ip-172-31-20-21.us-west-2.compute.internal>

* dist index chapter

* preproc chapter

* rst

* tools page

* partition chapter

* rst

* hetero chapter

* 7.1 step1

* add parmetis back

* changed based on feedback

* address comments

* add weighted sampling without replacement (A-Chao)

* improve Algorithm A-Chao with block-wise prefix sum

* correctly fill out_idxs

* implement weighted sampling with replacement

* small fix

* merge host-side code of weighted/uniform sampling

* enable unit tests for cuda weighted sampling

* move thrust/cub wrapper to the cmake file

* update docs accordingly

* fix linting

* fix linting

* fix unit test

* Bump external CUB/Thrust versions

* Fix code style and update description of algorithm design

* [Feature] GPU support weighted graph neighbor sampling
commit by pengqirong(OPPO)

* merge pengqirong's implementation

* revert the change to cub and thrust

* fix linting

* use DeviceSegmentedSort for better performance

* add more comments

* add necessary notes

* add necessary notes

* resolve some comments

* define THRUST_CUB_WRAPPED_NAMESPACE

* fix doc
Co-authored-by: 彭齐荣 <657017034@qq.com>

* [Feature] Add CUDA Weighted Randomwalk Sampling

* [Feature] Add CUDA Weighted Randomwalk Sampling

* [Feature] Add CUDA Weighted Randomwalk Sampling

* [Feature] Add CUDA Weighted Randomwalk Sampling

* fix empty prob array && enable non-uniform for restart && enable unit tests

* update doc and guide for randomwalk and pinsage

* update comments
Co-authored-by: zhenliangqiu <ubuntu@ip-172-31-24-245.ap-southeast-1.compute.internal>
Co-authored-by: xiny <xiny@nvidia.com>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-53-142.us-west-2.compute.internal>

Co-authored-by: Mufei Li <mufeili1996@gmail.com>

* Update

* CI

* Update

* Update

* Fix

* Fix

* wip: dataloading doc

* update dataloading package doc and many others

* lint

fix #3812
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* fix distributed multi-GPU example device

* try Join

* update version requirement in README

* use model.join

* fix docs
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

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

* Update

* Update

* Update

* Fix

* Update

* Update

* Update

* Fix

* [Fix] be able to parse ids if numeric and non-numeric values are used together

* add required package info and cache note into docstring

* duplicate node id is not allowed

* enable to launch multiple client groups sequentially

* launch simultaneously is enabled

* refine docstring

* revert unnecessary change

* [DOC] add doc for long live server

* refine

* refine doc

* refine doc

* implement pin_memory/unpin_memory/is_pinned for dgl.graph

* update python docstring

* update c++ docstring

* add test

* fix the broken UnifiedTensor

* XPU_SWITCH for kDLCPUPinned

* a rough version ready for testing

* eliminate extra context parameter for pin/unpin

* update train_sampling

* fix linting

* fix typo

* multi-gpu uva sampling case

* disable new format materialization for pinned graphs

* update python doc for pin_memory_

* fix unit test

* UVA sampling for link prediction

* dispatch most csr ops

* update graphsage example to combine uva sampling and UnifiedTensor

* update graphsage example to combine uva sampling and UnifiedTensor

* update graphsage example to combine uva sampling and UnifiedTensor

* update doc

* update examples

* change unitgraph and heterograph's PinMemory to in-place

* update examples for multi-gpu uva sampling

* update doc

* fix linting

* fix cpu build

* fix is_pinned for DistGraph

* fix is_pinned for DistGraph

* update graphsage unsupervised example

* update doc for gpu sampling

* update some check for sampling device switching

* fix linting

* adapt for new dataloader

* fix linting

* fix

* fix some name issue

* adjust device check

* add unit test for uva sampling & fix some zero_copy bug

* fix linting

* update num_threads in graphsage examples
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.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

Fix #3626

* Fix ref to message-passing guide

* Fix pygments and spacing

* Update build documentation steps in README.md

* Use links

* Adjust parameters in SAGEConv docstring in same order as init

* Fix spelling error

* Change doc link

* Update

* Update

* CI

* Update graph-heterogeneous.rst

`tensor([0, 1, 2, 0, 1, 2])` should be output instead of code

* Update message-api.rst

`updata_all_example()` should be `update_all_example()`

* Update message-efficient.rst

`cat_feat` need to concatenate with `dim=1` for the # edge features to match # edges

* Update nn-construction.rst

all `max_pool` in the aggregator type of `SAGEConv` should be `pool` instead

* Update graph-heterogeneous.rst

`tensor([0, 1, 2, 0, 1, 2])` should be output instead of code

* Update message-api.rst

`updata_all_example()` should be `update_all_example()`

* Update message-efficient.rst

`cat_feat` need to concatenate with `dim=1` for the # edge features to match # edges

* Update nn-construction.rst

all `max_pool` in the aggregator type of `SAGEConv` should be `pool` instead

* Update nn-forward.rst

all `max_pool` in the aggregator type of `SAGEConv` should be `pool` instead

* Update nn-forward.rst

all `max_pool` in the aggregator type of `SAGEConv` should be `pool` instead
Co-authored-by: zhjwy9343 <6593865@qq.com>