snorkel.labeling.apply.dask.DaskLFApplier

class snorkel.labeling.apply.dask.DaskLFApplier(lfs)[source]

Bases: snorkel.labeling.apply.core.BaseLFApplier

LF applier for a Dask DataFrame.

Dask DataFrames consist of partitions, each being a Pandas DataFrame. This allows for efficient parallel computation over DataFrame rows. For more information, see https://docs.dask.org/en/stable/dataframe.html

__init__(lfs)[source]

Initialize self. See help(type(self)) for accurate signature.

Return type

None

Methods

__init__(lfs)

Initialize self.

apply(df[, scheduler, fault_tolerant])

Label Dask DataFrame of data points with LFs.
apply(df, scheduler='processes', fault_tolerant=False)[source]

Label Dask DataFrame of data points with LFs.

Parameters

  • df (dask.dataframe.DataFrame) – Dask DataFrame containing data points to be labeled by LFs

  • scheduler (Union[str, dask.distributed.Client]) – A Dask scheduling configuration: either a string option or a Client. For more information, see https://docs.dask.org/en/stable/scheduling.html#

  • fault_tolerant (bool) – Output -1 if LF execution fails?

Returns

Matrix of labels emitted by LFs

Return type

np.ndarray