Add SubgraphType with bidirectional sampling support (2/2)
#7200
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## master #7200 +/- ##
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Coverage 91.68% 91.68%
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rusty1s
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May 24, 2023
Simple addition to enable bidirectional neighbor loader benchmarking. Results show a relative drop in performance moving from directional to bidirectional (example below) maybe due to the fact that, currently, bidirectional sampling is implemented as a post-processing of regular sampling [#7200](https://github.com/pyg-team/pytorch_geometric/pull/7200/files#) With directional sampling: Dataset: products Training sampling with [10, 5] neighbors 100%|█████████████████████████████████193/193 [00:03<00:00, 48.96it/s] 100%|█████████████████████████████████ 193/193 [00:03<00:00, 49.59it/s] 100%|█████████████████████████████████ 193/193 [00:03<00:00, 49.01it/s] batch size=1024, iterations=579, runtimes=[3.943, 3.892, 3.939], average runtime=3.925 while with bidirectional sampling: Dataset: products Training sampling with [10, 5] neighbors 100%|██████████████████████████████████ 193/193 [00:04<00:00, 42.22it/s] 100%|██████████████████████████████████193/193 [00:04<00:00, 43.18it/s] 100%|██████████████████████████████████193/193 [00:04<00:00, 42.56it/s] batch size=1024, iterations=579, runtimes=[4.572, 4.47, 4.535], average runtime=4.526 --------- Co-authored-by: rusty1s <matthias.fey@tu-dortmund.de>
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