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/*
 * Copyright 2017-2022 John Snow Labs
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.johnsnowlabs.nlp

import org.apache.spark.ml.{Model, PipelineModel}
import org.apache.spark.sql.expressions.UserDefinedFunction
import org.apache.spark.sql.functions.udf
import org.apache.spark.sql.{DataFrame, Dataset}

trait HasRecursiveTransform[M <: Model[M]] {

  this: AnnotatorModel[M] =>

  def annotate(annotations: Seq[Annotation], recursivePipeline: PipelineModel): Seq[Annotation]

  def dfRecAnnotate(recursivePipeline: PipelineModel): UserDefinedFunction = udf {
    annotationProperties: Seq[AnnotationContent] =>
      annotate(annotationProperties.flatMap(_.map(Annotation(_))), recursivePipeline)
  }

  def recursiveTransform(dataset: Dataset[_], recursivePipeline: PipelineModel): DataFrame = {
    _transform(dataset, Some(recursivePipeline))
  }

}




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