com.johnsnowlabs.nlp.HasBatchedAnnotateImage.scala Maven / Gradle / Ivy

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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
import org.apache.spark.ml.param.IntParam
import org.apache.spark.sql.Row

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

  this: RawAnnotator[M] =>

  /** Size of every batch (Default depends on model).
    *
    * @group param
    */
  val batchSize = new IntParam(this, "batchSize", "Size of every batch.")

  /** Size of every batch.
    *
    * @group setParam
    */
  def setBatchSize(size: Int): this.type = {
    val recommended = size
    require(recommended > 0, "batchSize must be greater than 0")
    set(this.batchSize, recommended)
  }

  /** Size of every batch.
    *
    * @group getParam
    */
  def getBatchSize: Int = $(batchSize)

  def batchProcess(rows: Iterator[_]): Iterator[Row] = {
    // TODO remove the @unchecked annotation and create a type to handle different subtypes
    // TODO make sure getAs(6) is compatible as supposed to getSeq[Byte].toArray
    rows
      .grouped(getBatchSize)
      .flatMap { case batchedRows: Seq[Row @unchecked] =>
        val inputAnnotations = batchedRows.map(row => {
          getInputCols.flatMap(inputCol => {
            row
              .getAs[Seq[Row]](inputCol)
              .map(r =>
                AnnotationImage(
                  r.getString(0),
                  r.getString(1),
                  r.getInt(2),
                  r.getInt(3),
                  r.getInt(4),
                  r.getInt(5),
                  r.getAs(6),
                  r.getMap[String, String](7)))
          })
        })
        val outputAnnotations = batchAnnotate(inputAnnotations)
        batchedRows.zip(outputAnnotations).map { case (row, annotations) =>
          row.toSeq ++ Array(annotations.map(a => Row(a.productIterator.toSeq: _*)))
        }
      }
      .map(Row.fromSeq)
  }

  /** takes a document and annotations and produces new annotations of this annotator's annotation
    * type
    *
    * @param batchedAnnotations
    *   Annotations in batches that correspond to inputAnnotationCols generated by previous
    *   annotators if any
    * @return
    *   any number of annotations processed for every batch of input annotations. Not necessary
    *   one to one relationship
    */
  def batchAnnotate(batchedAnnotations: Seq[Array[AnnotationImage]]): Seq[Seq[Annotation]]

}