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Make graph-store ABLP supervision-edge direction edge_dir-aware#692

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Make graph-store ABLP supervision-edge direction edge_dir-aware#692
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Callers specify supervision edge types in outward form (anchor -> supervision), matching taskMetadata. The colocated ABLP path already reverses these internally for edge_dir="in" to match how label edges are stored; the graph-store path did not, so the DBLP example compensated with a pre-reversed config and query = dst_node_type. That double reversal canceled out but trained the mirror of the declared task (author anchors -> paper candidates instead of paper -> author).

Make the graph-store path edge_dir-aware to match colocated mode:

  • DistServer.get_ablp_input reverses the supervision edge for edge_dir="in" before resolving stored label edge types.
  • DistABLPLoader._setup_for_graph_store asserts the outward convention and applies the same reversal, consistently across label-type derivation and the per-server loop.
  • Correct the GS DBLP config to outward ("paper","to","author").
  • Switch the GS training example to query = src / labeled = dst.
  • Add an edge_dir="in" regression test for get_ablp_input.

Behavior note: GS DBLP training now anchors on papers (the declared task), so e2e loss curves will shift.

Scope of work done

Where is the documentation for this feature?: N/A

Did you add automated tests or write a test plan?

Updated Changelog.md? NO

Ready for code review?: NO

Callers specify supervision edge types in outward form
(anchor -> supervision), matching taskMetadata. The colocated ABLP path
already reverses these internally for edge_dir="in" to match how label
edges are stored; the graph-store path did not, so the DBLP example
compensated with a pre-reversed config and query = dst_node_type. That
double reversal canceled out but trained the mirror of the declared
task (author anchors -> paper candidates instead of paper -> author).

Make the graph-store path edge_dir-aware to match colocated mode:
- DistServer.get_ablp_input reverses the supervision edge for
  edge_dir="in" before resolving stored label edge types.
- DistABLPLoader._setup_for_graph_store asserts the outward convention
  and applies the same reversal, consistently across label-type
  derivation and the per-server loop.
- Correct the GS DBLP config to outward ("paper","to","author").
- Switch the GS training example to query = src / labeled = dst.
- Add an edge_dir="in" regression test for get_ablp_input.

Behavior note: GS DBLP training now anchors on papers (the declared
task), so e2e loss curves will shift.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
@kmontemayor2-sc

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/all_test

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GiGL Automation

@ 21:44:13UTC : 🔄 E2E Test started.

@ 23:26:41UTC : ❌ Workflow failed.
Please check the logs for more details.

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GiGL Automation

@ 21:44:13UTC : 🔄 C++ Unit Test started.

@ 21:46:03UTC : ✅ Workflow completed successfully.

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GiGL Automation

@ 21:44:14UTC : 🔄 Python Unit Test started.

@ 23:01:39UTC : ✅ Workflow completed successfully.

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GiGL Automation

@ 21:44:14UTC : 🔄 Scala Unit Test started.

@ 21:54:46UTC : ✅ Workflow completed successfully.

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GiGL Automation

@ 21:44:16UTC : 🔄 Lint Test started.

@ 21:51:07UTC : ✅ Workflow completed successfully.

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@ 21:44:16UTC : 🔄 Integration Test started.

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