nemo_curator.core.utils

Module Contents

Functions

Name	Description
`_logger_custom_deserializer`	-
`_logger_custom_serializer`	-
`check_ray_responsive`	-
`get_free_port`	Checks if start_port is free.
`ignore_ray_head_node`	Return True if `CURATOR_IGNORE_RAY_HEAD_NODE` is set to a truthy value.
`init_cluster`	Initialize a new local Ray cluster or connects to an existing one.
`split_table_by_group_max_bytes`	Split an Arrow table by approximate byte size without splitting group rows.

API

nemo_curator.core.utils._logger_custom_deserializer(
    _: None
) -> loguru.Logger

nemo_curator.core.utils._logger_custom_serializer(
    _: loguru.Logger
) -> None

nemo_curator.core.utils.check_ray_responsive(
    timeout_s: int = RAY_CLUSTER_START_VERIFICAT...
) -> bool

nemo_curator.core.utils.get_free_port(
    start_port: int,
    get_next_free_port: bool = True
) -> int

Checks if start_port is free. If not, it will get the next free port starting from start_port if get_next_free_port is True. Else, it will raise an error if the free port is not equal to start_port.

nemo_curator.core.utils.ignore_ray_head_node() -> bool

Return True if CURATOR_IGNORE_RAY_HEAD_NODE is set to a truthy value.

Used by both the pipeline executors (to skip the head node when scheduling stage actors) and the inference-server backends (to emit a worker-only bundle-label selector on placement groups).

nemo_curator.core.utils.init_cluster(
    ray_port: int,
    ray_temp_dir: str,
    ray_dashboard_port: int,
    ray_metrics_port: int,
    ray_client_server_port: int,
    ray_dashboard_host: str,
    num_gpus: int | None = None,
    num_cpus: int | None = None,
    object_store_memory: int | None = None,
    enable_object_spilling: bool = False,
    block: bool = True,
    ip_address: str | None = None,
    stdouterr_capture_file: str | None = None
) -> subprocess.Popen

Initialize a new local Ray cluster or connects to an existing one.

nemo_curator.core.utils.split_table_by_group_max_bytes(
    table: pyarrow.Table,
    group_column: str,
    max_batch_bytes: int | None
) -> list[pyarrow.Table]

Split an Arrow table by approximate byte size without splitting group rows.

Each unique value in group_column is kept in a single output table. If a single group exceeds max_batch_bytes, it is still emitted as one chunk.

Note: null values in group_column are grouped together (consecutive nulls are not split). Callers should ensure the column is non-nullable or handle nulls upstream.