With these, the multiGPU example works and accuracy seems to be good.
Future PRs will add more tests, examples, refactoring and potential optimizations.
Checklist
Please feel free to remove inapplicable items for your PR.
[ ] The PR title starts with [$CATEGORY] (such as [NN], [Model], [Doc], [Feature]])
[ ] I've leverage the tools to beautify the python and c++ code.
[ ] The PR is complete and small, read the Google eng practice (CL equals to PR) to understand more about small PR. In DGL, we consider PRs with less than 200 lines of core code change are small (example, test and documentation could be exempted).
[ ] All changes have test coverage
[ ] Code is well-documented
[ ] To the best of my knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change
[ ] Related issue is referred in this PR
[ ] If the PR is for a new model/paper, I've updated the example index here.
@dgl-bot run [instance-type] [which tests] [compare-with-branch];
For example: @dgl-bot run g4dn.4xlarge all dmlc/master or @dgl-bot run c5.9xlarge kernel,api dmlc/master
Description
Towards #7273.
With these, the multiGPU example works and accuracy seems to be good.
Future PRs will add more tests, examples, refactoring and potential optimizations.
Checklist
Please feel free to remove inapplicable items for your PR.
Changes