GitLab

* upgrade CI pytorch version

* update

* revert tensorflow image

* old image (220816) backup

* Update Dockerfile.ci_gpu

Recently we find dist test often fails due to timeout. Root cause is not found yet.

* [Sparse] Add sparse matrix C++ implementation

* Add documentation

* Update

* Minor fix

* Move Python code to dgl/mock_sparse2

* Move headers to include

* lint

* Update

* Add dgl_sparse directory

* Move src code to dgl_sparse

* Add __init__.py in tests to avoid naming conflict

* Add dgl sparse so in Jenkinsfile

* Complete docstring & SparseMatrix basic op

* lint

* Disable win tests

* [CI] Enable DGL cugaph nightly CI

* fix build issue

* remove runtime

* [CI] refine stage logic

* refine

* refine

This reverts commit ec171c64.

* 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>

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

* fix if author is null

* add comments

* [CI] upgrade python version to 3.7.0

* do not upgrade for mxnet cpu due to seg fault

* fix test failure for mxnet

* [CI] upgrade python version to 3.7.0

* do not upgrade for mxnet cpu due to seg fault

* fix test failure for mxnet

* [CI] separate distributed tests from torch cpu tests

* remove TF related env

* [CI] add new stage specific forcuda related features based on nvidia+pytorch

* build and test for gpu_nv

* fix build failure

* fix unit tests

* make -j

* install cython beforehand

* copy cython lib

* test cugraph tests only

* fix typo

* separate test script for cugraph

* refactor build dgl shell

* try optimize CI

* fix go test; adjust timing report

* disable certain tests for mx/tf backends

* fix ut

* add pydantic

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

* Update

* Update

* Fix

* Update

* CI

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* [BugFix] fix job status in master CI

* finalize

* [CI] fix job status

* fetch from master

refactor CI report and log

* try fix

* try fix

* try fix

* try fix

* Revert "try fix"

This reverts commit a3fa0b1e9c0ab892cc3a22acf3770903db8b14a7.

* try fix shared memory

* try fix shared memory

* try fix image version

* fix

* fix

* fix bench

* fix

* Update bench_rgcn.py

* try fix

* fix wrong fix

* Update bench_rgcn.py

* fix

* try mount

* what's happening

* fix

* ci

* doesn't know whether works

* add change

* fix

* fix

* fix

* remove

* revert

* lint

* lint

* fix

* revert

* lint

* fix

* only build rpc on linux

* lint

* lint

* fix build on windows

* fix windows

* remove old test

* fix cmake

* Revert "remove old test"

This reverts commit f1ea75c777c34cdc1f08c0589676ba6aee1feb29.

* fix windows

* fix

* fix

* fix indent

* fix indent

* address comment

* fix

* fix

* fix

* fix

* fix

* lint

* fix indent

* fix lint

* add introduction

* fix

* lint

* lint

* add more logs

* fix

* update xbyak for C++14 with gcc5

* Remove channels

* fix

* add test script

* fix

* remove unused file

* fix lint

* add timeout

* try enable kvstore test

* fix

* fix

* seperate out kvstore test

* add comment

* 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

* fix regression ram info

* fix

* Enable C++ tests on GPU

* Add missing '--runtime nvidia'

* fix

* fix

* debug

* fix

* fix

* fix

* fix

* ci

* fix

* fix

* first commit

* some thoughts

* move around

* more commit

* more fixes

* now it uses torch allocator

* fix symbol export error

* fix

* fixes

* test fix

* add script

* building separate library per version

* fix for vs2019

* more fixes

* fix on windows build

* update jenkinsfile

* auto copy built dlls for windows

* lint and installation guide update

* fix

* specify conda environment

* set environment for ci

* fix

* fix

* fix

* fix again

* revert

* fix cmake

* fix

* switch to using python interpreter path

* remove scripts

* debug

* oops sorry

* Update index.rst

* Update index.rst

* copies automatically, no need for this

* do not print message if library not found

* tiny fixes

* debug on nightly

* replace add_compile_definitions to make CMake 3.5 happy

* fix linking to wrong lib for multiple pytorch envs

* changed building strategy

* fix nightly

* fix windows

* fix windows again

* setup bugfix

* address comments

* change README