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[GraphBolt][Dataset] Contribute IGBH dataset to hetero examples. #7708

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@BowenYao18 BowenYao18 commented Aug 15, 2024

Description

I added IGB-dataset to the RGCN folder. Currently the three smaller version (tiny[~2GB], small[~20GB], medium[~100GB]) are supported. The two larger versions (large[~800GB], full[~2.2TB]) are still under test.

Usage:

  1. Run the "download.py --size {choose the size}", the dataset will be downloaded and processed under the default ""dataset/"" folder
  2. Run the ""hetero_rgcn.py"" with the corresponding dataset you just processed

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.

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dgl-bot commented Aug 15, 2024

To trigger regression tests:

  • @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

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BowenYao18 and others added 4 commits August 15, 2024 15:01
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We don't need this file. The same functionality can be implemented in a few lines.

"igb-het-medium",
"igb-het-large",
"igb-het",
"igb-het-MLPerf",
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Can we make it all lower case?

The igb-hom-[tiny|small|medium] dataset is a heterogeneous citation network,
which is designed for developers to train and evaluate GNN models with
high fidelity. See more details in `igb-het-[tiny|small|medium]
high fidelity. See more details in `igb-het-[tiny|small|medium|large]
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also here as well. igb-het-[tiny|small|medium|large|mlperf] and igb-het.

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mfbalin commented Oct 19, 2024

LGTM except for the overly complicated evaluator.py file.

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Let's use pure pytorch operations to compute the evaluation score.

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