GitLab

* add lint workflow

* add line number

* address comments

* update package versions

* remove autopep8 config

Co-authored-by: Xiang Song <xiangsx@amazon.com>

* Add GraphTransformerLayer (dense)

* beautify the python code with black

* refine according to mufei's comments

* fix AttributeError in unit test

* rename module as GraphormerLayer

* fix name issue
Co-authored-by: Mufei Li <mufeili1996@gmail.com>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-36-188.ap-northeast-1.compute.internal>

* turn off use_alternate_stream when tensoradaptor is not enabled

* add docstring

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

* update agg function with new bindings

* handle optional import in __init__

* raise error in RelGraphConvAgg when pylibcugraphops not imported

* Update tests/cugraph/cugraph-ops/test_cugraph_relgraphconv.py
Co-authored-by: Mufei Li <mufeili1996@gmail.com>

* Update tests/cugraph/cugraph-ops/test_cugraph_relgraphconv.py
Co-authored-by: Mufei Li <mufeili1996@gmail.com>

* use keyword args for readability

* add missing docstring to pass CI

* catch ImportError rather than ModuleNotFoundError
Co-authored-by: Mufei Li <mufeili1996@gmail.com>

* Add support for next cusparse release

* Fix lint

* Add switch and tune the performance

* Fix lint issue

* Fine tune the heuristics

* Fix lint issue

* Address comments

* Minor fix

* Address comments

* Update

* update
Co-authored-by: Ubuntu <ubuntu@ip-172-31-36-188.ap-northeast-1.compute.internal>

* [Dist] remove dependency on deprecated _dataloading

* fix lint

* refine comment

* add twirls

* update attention part

* update; add val_like to mock_sparse

* black

* Add PathEncoder to transformer.py

* add blank line at the and

* rename variabl sp to shortest_path

* Fixed corresponding problems

* Fixed certain bugs when running on CUDA

* changed clamp min from 0 to 1
Co-authored-by: Ubuntu <ubuntu@ip-172-31-14-146.ap-northeast-1.compute.internal>
Co-authored-by: Mufei Li <mufeili1996@gmail.com>

Correction like mentioned in #4969 

I noticed that there is a normalisation step on line 97 while the normalised values are not used downstream. Even if this was meant to show the normalisation step, it would not be calculating the normalisation step described in the CGN paper. The paper considers both in and out degrees while the normalisation in the code only describes normalisation using the in degrees.
In the end, the normalised values are assigned to g.ndata["norm"] but these values are not used afterwards.

Having a normalisation step here is also unnecessary since the GraphConv layer that is used already takes care of the normalisation. https://docs.dgl.ai/en/0.9.x/_modules/dgl/nn/pytorch/conv/graphconv.html#GraphConv

It confused me for a second thinking that I had to do the normalisation myself but this is already handled by the GraphConf.

* add entity_sample example

* update message

* address review, update api call

* Update examples/pytorch/rgcn/entity_sample_cugraph_relgraphconv.py
Co-authored-by: Mufei Li <mufeili1996@gmail.com>

* Update examples/pytorch/rgcn/entity_sample_cugraph_relgraphconv.py
Co-authored-by: Mufei Li <mufeili1996@gmail.com>

* Update examples/pytorch/rgcn/entity_sample_cugraph_relgraphconv.py
Co-authored-by: Mufei Li <mufeili1996@gmail.com>

* address review

* move example and add description
Co-authored-by: Mufei Li <mufeili1996@gmail.com>

* Update

* Update

* Update

* Update
Co-authored-by: Ubuntu <ubuntu@ip-172-31-36-188.ap-northeast-1.compute.internal>

* Update

* Update
Co-authored-by: Ubuntu <ubuntu@ip-172-31-36-188.ap-northeast-1.compute.internal>

* replace dgl PRNG with pcg32

* remove pcg submodule, add a simple implementation

* replace pcg32 with std::mt19937_64

* fix include order

* change RandomEngine to pcg32

* Remove custom pcg32 implementation, use the submodule provided by the original author.

* minor bug

* move include for linting

* include pcg for tests too
Co-authored-by: Hongzhi (Steve), Chen <chenhongzhi.nkcs@gmail.com>

* Make preprocess compatible with openmpi

* update docstr
Co-authored-by: Xiang Song <xiangsx@amazon.com>

* hypergraph attention

* address comments

* Update

* Update

* Update

* CI
Co-authored-by: Ubuntu <ubuntu@ip-172-31-36-188.ap-northeast-1.compute.internal>

* fix unit test

* oops

* [Sparse] Support sparse format conversion

* Update

* Update

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

Signed-off-by: Serge Panev <spanev@nvidia.com>
Signed-off-by: Serge Panev <spanev@nvidia.com>

* black on explain_main

* isort

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

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

* Update

* Update

* Update

* Update
Co-authored-by: Ubuntu <ubuntu@ip-172-31-36-188.ap-northeast-1.compute.internal>

* Update

* Update

* Update

* Update
Co-authored-by: Ubuntu <ubuntu@ip-172-31-36-188.ap-northeast-1.compute.internal>

* Leverage hashmap to accelerate CSRSliceMatrix

* fix lint check

* use `min` in cuda_runtime.ch

* fix hash func

* add some comments and adjust the <grid,block> of the _SegmentMaskColKernel kernel

* set device and stream for thrust::for_each

* use thrust::cuda::par_nosync
Co-authored-by: Xin Yao <xiny@nvidia.com>

* adding LABOR sampling

* add ladies and pladies samplers

* fix compile error after rebase

* add reference for ladies sampler

* Improve ladies implementation.

* weighted labor sampling initial implementation draft
fix indentation and small bug in ladies script

* importance_sampling currently doesn't work with weights

* fix weighted importance sampling

* move labor example into its own folder

* lint fixes

* Improve documentation

* remove examples from the main PR

* fix linting by not using c++17 features

* fix documentation of labor_sampler.py

* update documentation for labor.py

* reformat the labor.py file with black

* fix linting errors

* replace exception use with if

* fix typo in error comment

* fixing win64 build for ci

* fixing weighted implementation, works now.

* fix bug in the weighted case and importance_sampling==0

* address part of the reviews

* remove unused code paths from cuda

* remove unused code path from cpu side

* remove extra features of labor making use of random seed.

* fix exclude_edges bug

* remove pcg and seed logic from cpu implementation, seed logic should still work for cuda.

* minor style change

* refactor CPU implementation, take out the importance_sampling probability computation into a function.

* improve CUDAWorkspaceAllocator

* refactor importance_sampling part out to a function

* minor optimization

* fix linting issue

* Revert "remove pcg and seed logic from cpu implementation, seed logic should still work for cuda."

This reverts commit c250e07ac6d7e13f57e79e8a2c2f098d777378c2.

* Revert "remove extra features of labor making use of random seed."

This reverts commit 7f99034353080308f4783f27d9a08bea343fb796.

* fix the documentation

* disable NIDs

* improve the documentation in the code

* use the stream argument in pcg32 instead of skipping ahead t times, can discard the use of hashmap now since it is faster this way.

* fix linting issue

* address another round of reviews

* further optimize CPU LABOR sampling implementation

* fix linting error

* update the comment

* reformat

* rename and rephrase comment

* fix formatting according to new linting specs

* fix compile error due to renaming, fix linting.

* lint

* rename DGLHeteroGraph to DGLGraph to match master

* replace other occurrences of DGLHeteroGraph to DGLGraph
Co-authored-by: Muhammed Fatih BALIN <m.f.balin@gmail.com>
Co-authored-by: Kaan Sancak <kaansnck@gmail.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>