sparknlp_jsl.common.annotator_properties_internal#

Contains the base classes for Annotator properties.

Module Contents#

Classes#

AnnotatorPropertiesInternal

Components that take parameters. This also provides an internal

class AnnotatorPropertiesInternal#

Bases: sparknlp_jsl.common.AnnotatorProperties

Components that take parameters. This also provides an internal param map to store parameter values attached to the instance.

New in version 1.3.0.

inputAnnotatorTypes = []#
inputCols#
lazyAnnotator#
optionalInputAnnotatorTypes = []#
outputAnnotatorType = None#
outputCol#
uid = ''#
clear(param: Param) None#

Clears a param from the param map if it has been explicitly set.

copy(extra: pyspark.ml._typing.ParamMap | None = None) P#

Creates a copy of this instance with the same uid and some extra params. The default implementation creates a shallow copy using copy.copy(), and then copies the embedded and extra parameters over and returns the copy. Subclasses should override this method if the default approach is not sufficient.

Parameters:

extra (dict, optional) – Extra parameters to copy to the new instance

Returns:

Copy of this instance

Return type:

Params

explainParam(param: str | Param) str#

Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.

explainParams() str#

Returns the documentation of all params with their optionally default values and user-supplied values.

extractParamMap(extra: pyspark.ml._typing.ParamMap | None = None) pyspark.ml._typing.ParamMap#

Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra.

Parameters:

extra (dict, optional) – extra param values

Returns:

merged param map

Return type:

dict

getInputCols()#

Gets current column names of input annotations.

getLazyAnnotator()#

Gets whether Annotator should be evaluated lazily in a RecursivePipeline.

getOrDefault(param: str) Any#
getOrDefault(param: Param[T]) T

Gets the value of a param in the user-supplied param map or its default value. Raises an error if neither is set.

getOutputCol()#

Gets output column name of annotations.

getParam(paramName: str) Param#

Gets a param by its name.

hasDefault(param: str | Param[Any]) bool#

Checks whether a param has a default value.

hasParam(paramName: str) bool#

Tests whether this instance contains a param with a given (string) name.

inputColsValidation(value)#
isDefined(param: str | Param[Any]) bool#

Checks whether a param is explicitly set by user or has a default value.

isSet(param: str | Param[Any]) bool#

Checks whether a param is explicitly set by user.

set(param: Param, value: Any) None#

Sets a parameter in the embedded param map.

setForceInputTypeValidation(etfm)#
setInputCols(*value)#

Sets column names of input annotations.

Parameters:

*value (List[str]) – Input columns for the annotator

setLazyAnnotator(value)#

Sets whether Annotator should be evaluated lazily in a RecursivePipeline.

Parameters:

value (bool) – Whether Annotator should be evaluated lazily in a RecursivePipeline

setOutputCol(value)#

Sets output column name of annotations.

Parameters:

value (str) – Name of output column