data_juicer.ops.selector.range_specified_field_selector module#

class data_juicer.ops.selector.range_specified_field_selector.RangeSpecifiedFieldSelector(field_key: str = '', lower_percentile: Annotated[float, FieldInfo(annotation=NoneType, required=True, metadata=[Ge(ge=0), Le(le=1)])] | None = None, upper_percentile: Annotated[float, FieldInfo(annotation=NoneType, required=True, metadata=[Ge(ge=0), Le(le=1)])] | None = None, lower_rank: Annotated[int, Gt(gt=0)] | None = None, upper_rank: Annotated[int, Gt(gt=0)] | None = None, *args, **kwargs)[source]#

Bases: Selector

Selector to select a range of samples based on the sorted specified field value from smallest to largest.

__init__(field_key: str = '', lower_percentile: Annotated[float, FieldInfo(annotation=NoneType, required=True, metadata=[Ge(ge=0), Le(le=1)])] | None = None, upper_percentile: Annotated[float, FieldInfo(annotation=NoneType, required=True, metadata=[Ge(ge=0), Le(le=1)])] | None = None, lower_rank: Annotated[int, Gt(gt=0)] | None = None, upper_rank: Annotated[int, Gt(gt=0)] | None = None, *args, **kwargs)[source]#

Initialization method.

Parameters:

  • field_key – Selector based on the specified value corresponding to the target key. The target key corresponding to multi-level field information need to be separated by ‘.’.

  • lower_percentile – The lower bound of the percentile to be sample, samples will be selected if their specified field values are greater than this lower bound. When both lower_percentile and lower_rank are set, the value corresponding to the larger number of samples will be applied.

  • upper_percentile – The upper bound of the percentile to be sample, samples will be selected if their specified field values are less or equal to the upper bound. When both upper_percentile and upper_rank are set, the value corresponding to the smaller number of samples will be applied.

  • lower_rank – The lower bound of the rank to be sample, samples will be selected if their specified field values are greater than this lower bound. When both lower_percentile and lower_rank are set, the value corresponding to the larger number of samples will be applied.

  • upper_rank – The upper bound of the rank to be sample, samples will be selected if their specified field values are less or equal to the upper bound. When both upper_percentile and upper_rank are set, the value corresponding to the smaller number of samples will be applied.

  • args – extra args

  • kwargs – extra args

process(dataset)[source]#

Dataset –> dataset.

Parameters:

dataset – input dataset

Returns:

selected dataset.