class_docstr: Fitted RecursivePipeline.
  
  Behaves the same as a Spark PipelineModel does. Not intended to be
  initialized by itself. To create a RecursivePipelineModel please fit data to
  a :class:`.RecursivePipeline`.
class_docstr_tok: ["Fitted","RecursivePipeline",".","Behaves","the","same","as","a","Spark","PipelineModel","does",".","Not","intended","to","be","initialized","by","itself",".","To","create","a","RecursivePipelineModel","please","fit","data","to","a",":","class",":","`",".RecursivePipeline","`","."]
code: def __init__(self, pipeline_model):
      super(PipelineModel, self).__init__()
      self.stages = pipeline_model.stages
  
file_path: spark-nlp/python/sparknlp/base/recursive_pipeline.py
imports: from pyspark import keyword_only
  from pyspark.ml import PipelineModel, Estimator, Pipeline, Transformer
  from pyspark.ml.wrapper import JavaEstimator
  from sparknlp.common import AnnotatorProperties
  from sparknlp.internal import RecursiveEstimator
  from sparknlp.base import HasRecursiveTransform
label_desc: Use image node_id 1 to create a new RecursivePipelineModel object from inherited base classes: PipelineModel with example: obj = RecursivePipelineModel(pipeline_model)