launcher: wire TensorBoard fields into VertexAiJobConfig#621
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kmontemayor2-sc wants to merge 2 commits intomainfrom
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launcher: wire TensorBoard fields into VertexAiJobConfig#621kmontemayor2-sc wants to merge 2 commits intomainfrom
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Adds two optional fields on ``VertexAiResourceConfig`` for opting into Vertex AI TensorBoard. ``tensorboard_resource_name`` points at an existing ``Tensorboard`` resource; ``tensorboard_experiment_name`` is the user-chosen ``TensorboardExperiment`` ID under that resource — multiple jobs sharing this name surface as comparable runs on the same TB page. The fields must be set together (or both unset). The validation rule is not enforced yet (lands in a follow-up PR); this commit only adds the proto fields and regenerates Python + Scala stubs. Also expands the docstring on ``TrainedModelMetadata.tensorboard_logs_uri`` to document its mapping to ``AIP_TENSORBOARD_LOG_DIR`` via ``CustomJobSpec.baseOutputDirectory``. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds the launcher-side TensorBoard plumbing. After this PR, callers that pass ``tensorboard_logs_uri`` get ``baseOutputDirectory`` set on the CustomJob, and resource configs that set ``tensorboard_experiment_name`` get three env vars injected into the worker container so the trainer's chief-rank uploader can find the named experiment. - ``_build_job_config`` accepts ``tensorboard_logs_uri: Optional[Uri]`` and derives ``base_output_dir`` from it. - When the resource config sets ``tensorboard_experiment_name``, inject ``GIGL_TENSORBOARD_RESOURCE_NAME``, ``GIGL_TENSORBOARD_EXPERIMENT_NAME``, and ``GIGL_TENSORBOARD_RUN_NAME`` (sanitized + UTC-suffixed for per-launch uniqueness). - ``_maybe_log_tensorboard_url`` prints the cross-job TB experiment URL at submit time so the link is visible in the launcher's local stdout. - ``VertexAiJobConfig`` gains a ``base_output_dir`` field, threaded through to ``aiplatform.CustomJob``. - ``get_tensorboard_logs_gcs_path`` now returns ``<asset_dir>/logs/`` (was ``<asset_dir>/tensorboard_logs/``), aligning with Vertex AI's ``<base_output_dir>/logs/`` convention so writer events land where ``AIP_TENSORBOARD_LOG_DIR`` points. Updates the ConfigPopulator unit test that asserts on the path suffix. Reading the new fields off the resource config and the ``tensorboard_logs_uri`` off the GbmlConfig is deferred to the next PR (trainer/inferencer dispatch) — production trainers don't pass ``tensorboard_logs_uri`` yet, so this change is invisible to existing production runs. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Adds the launcher-side TensorBoard plumbing. After this PR, callers
that pass
tensorboard_logs_urigetbaseOutputDirectoryset onthe CustomJob, and resource configs that set
tensorboard_experiment_nameget three env vars injected into theworker container so the trainer's chief-rank uploader can find the
named experiment.
_build_job_configacceptstensorboard_logs_uri: Optional[Uri]and derives
base_output_dirfrom it.tensorboard_experiment_name, injectGIGL_TENSORBOARD_RESOURCE_NAME,GIGL_TENSORBOARD_EXPERIMENT_NAME,and
GIGL_TENSORBOARD_RUN_NAME(sanitized + UTC-suffixed forper-launch uniqueness).
_maybe_log_tensorboard_urlprints the cross-job TB experiment URLat submit time so the link is visible in the launcher's local stdout.
VertexAiJobConfiggains abase_output_dirfield, threadedthrough to
aiplatform.CustomJob.get_tensorboard_logs_gcs_pathnow returns<asset_dir>/logs/(was
<asset_dir>/tensorboard_logs/), aligning with Vertex AI's<base_output_dir>/logs/convention so writer events land whereAIP_TENSORBOARD_LOG_DIRpoints. Updates the ConfigPopulator unittest that asserts on the path suffix.
Reading the new fields off the resource config and the
tensorboard_logs_urioff the GbmlConfig is deferred to the next PR(trainer/inferencer dispatch) — production trainers don't pass
tensorboard_logs_uriyet, so this change is invisible to existingproduction runs.
Co-Authored-By: Claude Opus 4.7 (1M context) noreply@anthropic.com