Sampler Methods & Properties

Full reference for sampler instance methods and shared properties.

Methods

Name	Description
__call__	Return an iterator over sampled Batch objects from a dataset.
iter_series	Iterate sampled Batch objects per series.
write_batches	Write sampled batches to disk (local directory or cloud storage).

Properties

Name	Description
data_schema	Data schema for the sampler output (available after sampling a dataset).
targets_schema	Target schema if a target_spec is configured.

__call__

__call__(
    dataset: Dataset,
    num_batches: int | None = None,
    *,
    reset: bool = False
) -> Iterator[Batch]

Return an iterator over sampled Batch objects from a dataset.

Parameter Name	Description
dataset	Dataset to sample from.
num_batches	Optional maximum batches to yield, or None for all available.
reset	If True, reset the sampler's internal state before sampling.

iter_series

iter_series(
    dataset: Dataset
) -> Iterator[Iterator[Batch]]

Iterate sampled Batch objects per series.

Parameter Name	Description
dataset	Dataset to sample from.

write_batches

write_batches(
    dataset: Dataset,
    num_batches: int,
    path: str | Path,
    *,
    prefix: str = 'batch_',
    offset: int = 0,
    filesystem: fs.FileSystem | None = None,
    fs_config: dict[str, Any] | None = None,
    overwrite: bool = False,
    reset: bool = False
) -> None

Write sampled batches to disk (local directory or cloud storage).

Parameter Name	Description
dataset	Dataset to sample from.
num_batches	Number of batches to write.
path	Output directory path.
prefix	Filename prefix for each batch.
offset	Starting index for batch numbering.
filesystem	Optional PyArrow filesystem instance to write to.
fs_config	Optional filesystem configuration if filesystem is not provided.
overwrite	Overwrite existing files if True.
reset	If True, reset the sampler's internal state before sampling.