sparknlp_jsl.common.annotator_properties_internal
#
Contains the base classes for Annotator properties.
Module Contents#
Classes#
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