GitLab

* add init version.

* fix build.

* fix format.

* fix.

* fix.

* fix format.

* update README.

* avoid running CI on distributed training tutorials.

* Update tutorials/dist/1_node_classification.py
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

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

* add

* fix

* set default

* fix

* try master

* try fix

* try

* fix

* 111

* fix

* fix

* update

* ccc

* try

* fix

* fix

* try new machine

* fix

* fix

* fix

* Revert "fix"

This reverts commit e716d66b046f92fe7ae368947a51a036a7a3188a.

* try

* more parrallel

* use k8s for all

* fix name

* try not specify instance type

* ci

* use one yaml

* Revert "use one yaml"

This reverts commit 717d8d852be39fbf2e2e45f9f224aa97907c372c.

* add timeout

* fix permission

* mount efs

* print

* fix pvc

* fix

* restrict num of gpu instances

* check

* fix

* fix

* make to_heterogeneous and to_homogeneous invertible

* docstring

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

* update

* update

* update

* update

* lint

* lint

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* lint

* update

* clone

* update

* update

* update

* update

* replace idarray with ndarray

* refactor cpp part

* refactor python part

* debug

* refactor interface

* test and doc

* lint and test

* lint

* fix

* fix

* fix

* const

* doc

* fix

* fix

* fix

* fix

* fix & doc

* fix

* fix

* fix

* fix

* fix

* fix

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

* Fix #2808

* fix

* fix

* fix

* fix

* fix

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

* explicitly set the graph format.

* fix.

* fix.

* fix launch script.

* fix readme.
Co-authored-by: Zheng <dzzhen@3c22fba32af5.ant.amazon.com>
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-71-112.ec2.internal>

[Feature][Performance] Implement NCCL wrapper for communicating NodeEmbeddings and sparse gradients. (#2825)

* Split NCCL wrapper from sparse optimizer and sparse embedding

* Add more unit tests for single node nccl

* Fix unit test for tf

* Switch to device histogram

* Fix histgram issues

* Finish migration to histogram

* Handle cases with zero send/recieve data

* Start on partition object

* Get compiling

* Updates

* Add unit tests

* Switch to partition object

* Fix linting issues

* Rename partition file

* Add python doc

* Fix python assert and finish doxygen comments

* Remove stubs for range based partition to satisfy pylint

* Wrap unit test in GPU only

* Wrap explicit cuda call in ifdef

* Merge with partition.py

* update docstrings

* Cleanup partition_op

* Add Workspace object

* Switch to using workspace object

* Move last remainder based function out of nccl_api

* Add error messages

* Update docs with examples

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

* add bruteforce impl

* add support for bruteforce-sharemem

* modify python API

* add tests

* change file path

* change python API

* fix lint

* fix test

* also check worst_dist in the last few dim

* use heap and early-stop on CPU

* fix lint

* fix lint

* add device check

* use cuda function to determine max shared mem

* use cuda to determine block info

* add memory free for tmp var

* update doc-string and add dist option

* fix lint

* add more tests
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* add distributed in-degree and out-degree.

* update comments.

* fix a bug.

* add tests.

* add tests.

* fix a bug.

* fix docstring.

* update doc.

* fix

* fix.
Co-authored-by: Zheng <dzzhen@3c22fba32af5.ant.amazon.com>
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* add lda model

* tweak latent dirichlet allocation

* Update README.md

* Update README.md

* update example index

* update header

* minor tweak

* add example test

* update doc

* Update README.md

* Update README.md

* add partial_fit for free

* Update examples/pytorch/lda/lda_model.py
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>

* Update examples/pytorch/lda/example_20newsgroups.py
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>

* Update lda_model.py

* bugfix torch Gamma uses rate parameter
Co-authored-by: Yifei Ma <yifeim@amazon.com>
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>

* test commit

* fixes

* oops

* add docs

* lint

* why does it say I have a trailing whitespace

* oh ok

* fixes

* why there's an invalid argument error

* address comments

* fix

* address comments

* Update heterograph.py

* remove unit tests

* replace tutorial

* Make loader items iterator

* Update test_dataloader.py

* Update __init__.py

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

* 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
Co-authored-by: Ubuntu <ubuntu@ip-172-31-57-25.ec2.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-24-210.ec2.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-2-66.ec2.internal>

* init cuda support

* cuSPARSE err

* passed unittest for csr_mm/SpGEMM. int64 not supported

* Debugging cuSPARSE error 3

* csrgeam only supports int32?

* disabling int64 for cuda

* refactor and add CSRMask

* lint

* oops

* remove todo

* rewrite CSRMask with CSRGetData

* lint

* fix test

* address comments

* lint

* fix

* addresses comments and rename BUG_ON
Co-authored-by: Israt Nisa <nisisrat@amazon.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-30-71.ec2.internal>
Co-authored-by: Quan Gan <coin2028@hotmail.com>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* Update

* update
Co-authored-by: Ubuntu <ubuntu@ip-172-31-59-108.us-west-2.compute.internal>

* update distributed training doc.

* explain data split.

* fix message passing.

* id mapping.

* fix.

* test data reshuffling.

* fix a bug.

* fix test.

* Revert "fix."

This reverts commit 2d025e9e1a5c05c3da9b803a035a788ced59bd77.

* Revert "id mapping."

This reverts commit 2a6a93ceb81fbdff86e6e9e5a58e1ace1e9d9882.

* Revert "fix message passing."

This reverts commit ed8a86bf2b015e5e4f64ba160e81b207ad2a1d65.

* Revert "explain data split."

This reverts commit 4338ddf8a336014cf92d4cb9a1db02b9badc0e55.

* Revert "update distributed training doc."

This reverts commit dda1c35c44536934c19715534f01f832afda6ad2.

* add more tests.

* fix.

* fix.

* fix.
Co-authored-by: Zheng <dzzhen@3c22fba32af5.ant.amazon.com>
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* Fix #2856

* upd

* Fix unitest

* upd

* upd

* upd

* Fix
Co-authored-by: Ubuntu <ubuntu@ip-172-31-57-25.ec2.internal>

* return mapping.

* support heterogeneous graph.

* more test.

* fix lint.

* fix for diff backends.

* fix.

* fix.
Co-authored-by: Zheng <dzzhen@3c22fba32af5.ant.amazon.com>
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* update

* update

* update

* update

* update

* update

* update

* fix

* fix

* update

* doc

* doc

* fix

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

* Add row/col sorted flags

* improve sorting paths

* Remove print statement

* Keep track of sorted matrices

* Remove sort check in to_block

* Improve CPU sorted COO->CSR

* Handle the zero edge case

* Remove omp default clause to work with MSVC

* Update comments on sorted COO->CSR cpu implementatoin

* Expose sorted to python interface

* Make check_sorted default to false for dgl.graph()

* remove check sorted; add utests

* remove check_sorted flag
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* Start on uniform GPU sampling

* Save more work

* Get cu file compiling

* Update sampling

* More changes

* Get GPU sampling for uniform probabilities solved

* Fix batch tensor migration

* Fix

* update kernels

* expand blocking

* Undo testing change

* Cut down on sampling overhead

* Fix replacement

* Update unit tests

* Add option to gpu sample in graphsage

* Copy only csc to gpu

* Add ogbn support

* Fix linting

* Remove nvtx from sample

* Improve documentation and error checking

* Expand documentation

* Update assert checking

* delete extra space

* Use standard dataloader when dataset is a dictionary

* ogb -> ogbn

* Fix edge selection determinism

* Fix typos

* Remove nvtx

* Add comment for self.fanout_arrays and assert

* Fix linting

* Migrate to scalarbatcher

* Fix indentation

* Fix batcher

* Fix indexing

* Only use databatcher for GPU

* Convert to DGL NDArray to PyTorch Tensor

* Add optimization for PyTorch's F.tensor() for list of GPU tensors
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* fix.

* test distributed graph without node/edge data.

* remove some tests.

* fix lint

* add submodule nanoflann

* finish python API for knn

* finish ndarray adaptor

* finish cpu-kdtree version of knn

* use openmp

* add endline

* upt

* upt

* fix format and code style

* upt

* add warning for gpu-cpu copy

* avoid contiguous copy
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Tong He <hetong007@gmail.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>

* tf nn for edgeConv

* Auto stash before merge of "tf_working" and "origin/tf_working"

* clean up

* added test for edge_conv

* fix

* fix

* fix
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>

* test

* more stuff

* add test

* fixes

* optimize algo

* replace unordered_map with arrays

* lint

* lint x2

* oops

* disable gpu csrmm tests

* remove gpu invocation

* optimize with openmp

* remove python functions

* add back with docstrings

* lint

* lint

* update python interface

* functionize

* functionize

* lint

* lint

* upd

* lint

* upd

* upd

* compatibility

* upd

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

* fix pickle problem

* lint

* add pickle tests

* fix

* fix

* fix

* fix

* fix for windows

* finish graph matching gpu version

* use C++ shuffle

* finish graph matching

* fix bug

* fix bug

* change name and use swap

* upt

* fix format problem

* fix format problem

* stronger test

* upt

* upt

* change python api

* upt

* upt

* format check

* upt

* upt

* fix bug
Co-authored-by: Tong He <hetong007@gmail.com>

* Update

* update

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

* upd

* fix

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* fix

* refactor

* upd test

* large feat_len or n in segment reduce

* lint

* reorg

* change titles

* rm some stale API doc; minor fix

* fix docs

* add warning

* rm new-tutorial run in ci

* lint

* fix inconsistencies and GPu

* bug fixes

* fix

* trigger new tutorials

* Add start of to_block gpu implementation

* Pull in more changes from 0.4.2 cuda_to_block

* Move more code to IdArray

* Refactor DeviceNodeMapMaker

* Updates

* get compiling

* Integrate to_block

* Fix ID allocation

* Minor fixes

* Cleanup cuda calls to use cuda_common

* Reduce kernel calls

* Lint cleanup

* Expand documentation

* Remove unused function

* Rename variables for consistency

* Add doxygen comments

* Fix file extension

* Remove raw asynccopy for deviceapi

* Remove unused function

* Fix block/tile configuration

* Add cuda_device_common.cuh

* Add basic hashtable

* Migrate part of hashtable

* Refactor to use external hashtable

* Make functions members

* Format hash table functions

* Migrate duplicate filling

* Move last function over

* Refactor with cu file

* lint c++ code

* Move context check to C++ code

* Use macro switch

* Add missing files

* Update docstring

* update docs

* Move atomic functions

* Refactor hashtable

* Fix linting

* Expand docs

* Fix mismatched argument names

* Switch doxygen comments from using @param to \param
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>