XennaExecutor

from nemo_curator.backends.xenna import XennaExecutor

class XennaExecutor(BaseExecutor):
    """Production executor using Cosmos-Xenna for distributed execution.
    Provides:
    - Distributed task orchestration
    - Resource allocation and management
    - Batch processing optimization
    - Performance metrics collection
    """
    def __init__(
        self,
        config: dict[str, Any] | None = None,
        ignore_head_node: bool = False,
    ) -> None:
        """Initialize the executor.
        Args:
            config: Executor configuration dictionary.
            ignore_head_node: Not supported. Raises ValueError if True.
        """

from nemo_curator.pipeline import Pipeline
from nemo_curator.backends.xenna import XennaExecutor
pipeline = Pipeline(name="my_pipeline", stages=[...])
# Default executor
results = pipeline.run()
# Equivalent to:
executor = XennaExecutor()
results = pipeline.run(executor=executor)

from nemo_curator.stages.base import ProcessingStage
from nemo_curator.stages.resources import Resources
from nemo_curator.tasks import EmptyTask
class PassthroughStage(ProcessingStage[EmptyTask, EmptyTask]):
    name = "passthrough"
    resources = Resources(cpus=1.0)
    def process(self, task: EmptyTask) -> EmptyTask:
        return task
cluster_wide_stage = PassthroughStage().with_(
    num_workers=12,
    xenna_stage_spec={
        "worker_max_lifetime_m": 45,
    },
)
per_node_stage = PassthroughStage().with_(
    num_workers=None,
    xenna_stage_spec={
        "num_workers_per_node": 2,
    },
)

executor = XennaExecutor(config={
    "logging_interval": 30,
    "ignore_failures": True,
    "execution_mode": "batch",
    "cpu_allocation_percentage": 0.9,
})
results = pipeline.run(executor=executor)

def execute(
    self,
    stages: list[ProcessingStage],
    initial_tasks: list[Task] | None = None,
) -> list[Task]:
    """Execute the pipeline stages.
    Args:
        stages: List of processing stages to execute.
        initial_tasks: Initial tasks (defaults to a fresh `EmptyTask()` instance).
    Returns:
        List of output tasks from the final stage.
    """

executor = XennaExecutor(config={
    "ignore_failures": True,  # Continue despite errors
})
try:
    results = pipeline.run(executor=executor)
except Exception as e:
    # Handle pipeline-level failures
    print(f"Pipeline failed: {e}")

results = pipeline.run(executor=executor)
# Each task contains performance data
for task in results:
    for perf in task._stage_perf:
        print(f"Stage: {perf.stage_name}")
        print(f"  Duration: {perf.process_time}s")
        print(f"  Items processed: {perf.num_items_processed}")