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nexuml.execution.ray

nexuml.execution.ray

Thin Ray Train execution for the canonical NexuML Lightning session.

RayExecutionError

Bases: RuntimeError

Raised when a Ray execution request cannot be represented cleanly.

train_loop_per_worker

train_loop_per_worker(config: dict[str, Any]) -> None

Run one Ray worker through the normal NexuML session lifecycle.

Raises:

Type Description
RayExecutionError

If Ray Train is unavailable in the worker environment.

run_ray

run_ray(scenario: ScenarioSpec) -> Any

Execute one resolved scenario with Ray Train and return Ray's native Result.

Returns:

Type Description
Any

The ray.train.Result returned by TorchTrainer.fit.

Raises:

Type Description
RayExecutionError

If the scenario cannot be executed safely with Ray or Ray dependencies are unavailable.