Kmonte/tb examples v2#632
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…_metrics Introduces ``gigl.utils.tensorboard_writer.TensorBoardWriter``, the trainer/inferencer-side abstraction that writes scalar metrics to a Vertex AI ``ExperimentRun`` synchronously via ``aiplatform.log_time_series_metrics``. Key design points: - ``TensorBoardWriter.create(resource_name=..., experiment_name=..., experiment_run_name=..., enabled=is_chief_process)`` is the only constructor entry point. No env-var contract, no proto fields on ``GiglResourceConfig`` — configuration is plumbed through the trainer/inferencer's argparse (typically populated from ``GbmlConfig.trainerConfig.trainerArgs`` / ``inferencerConfig.inferencerArgs``). - ``enabled=False`` (non-chief ranks) returns a no-op writer. Chief ranks must supply all three string args; missing any of them raises ``RuntimeError`` so misconfiguration surfaces fast rather than producing a silent no-op. - Logs the cross-job experiment URL on ``start_run`` success so engineers can find the comparison TB page from trainer stdout. - Each ``log()`` is a single synchronous ``WriteTensorboardRunData`` RPC. Failures propagate to the caller (no background uploader thread). This PR introduces the writer with full test coverage but no callers; example trainer/inferencer entrypoints get wired up in a follow-up PR. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds chief-rank TensorBoard logging to all 8 example link_prediction entrypoints (4 trainers + 4 inferencers, single-pool and graph-store). Each entrypoint: - Adds ``--tensorboard_resource_name`` / ``--tensorboard_experiment_name`` argparse flags (populated from ``trainerConfig.trainerArgs`` / ``inferencerConfig.inferencerArgs`` in the task config). - Plumbs both args plus ``--job_name`` through the per-process dataclass (``TrainingProcessArgs`` / ``InferenceProcessArgs``). - Constructs the writer once at the top of the per-process function with ``enabled=is_chief_process`` (or the graph-store equivalent ``args.cluster_info.compute_node_rank == 0 and local_rank == 0``). Misconfiguration on the chief rank fails fast inside ``create()``. - Trainers log ``Loss/train`` / ``Loss/val`` / ``Loss/test`` inside the existing ``log_every_n_batch`` gates; inferencers log ``Inference/throughput_batches_per_sec``. - Closes the writer at the end of the per-process function (paired ``aiplatform.end_run``). Updates the four OSS example task configs (CORA and DBLP, single-pool and graph-store) to set the GiGL OSS Tensorboard resource + ``gigl-oss-examples`` experiment, so the examples emit comparable runs out of the box. The single-line ruff reformat of ``tensorboard_writer_test.py`` is a trivial cleanup that rides along. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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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