class_docstr: Instantiated Model of the Normalizer.
  
  This is the instantiated model of the :class:`.Normalizer`.
  For training your own model, please see the documentation of that class.
  
  ====================== ======================
  Input Annotation types Output Annotation type
  ====================== ======================
  ``TOKEN``              ``TOKEN``
  ====================== ======================
  
  Parameters
  ----------
  cleanupPatterns
      normalization regex patterns which match will be removed from token
  lowercase
      whether to convert strings to lowercase
class_docstr_tok: ["Instantiated","Model","of","the","Normalizer",".","This","is","the","instantiated","model","of","the",":","class",":","`",".Normalizer","`",".","For","training","your","own","model",",","please","see","the","documentation","of","that","class",".","======================","======================","Input","Annotation","types","Output","Annotation","type","======================","======================","``","TOKEN","``","``","TOKEN","``","======================","======================","Parameters","--","--","--","--","--","cleanupPatterns","normalization","regex","patterns","which","match","will","be","removed","from","token","lowercase","whether","to","convert","strings","to","lowercase"]
code: def __init__(
      self,
      classname="com.johnsnowlabs.nlp.annotators.NormalizerModel",
      java_model=None,
  ):
      super(NormalizerModel, self).__init__(
          classname=classname, java_model=java_model
      )
  
file_path: spark-nlp/python/sparknlp/annotator/normalizer.py
imports: from sparknlp.common import *
label_desc: Use image node_id 1 to create a new NormalizerModel object from inherited base classes: AnnotatorModel with example: obj = NormalizerModel(classname, java_model)