com.johnsnowlabs.nlp.embeddings.HasEmbeddingsProperties.scala Maven / Gradle / Ivy
/*
* 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.embeddings
import com.johnsnowlabs.nlp.{AnnotatorType, HasProtectedParams}
import org.apache.spark.ml.param.{IntParam, Params}
import org.apache.spark.sql.Column
import org.apache.spark.sql.types.MetadataBuilder
trait HasEmbeddingsProperties extends Params with HasProtectedParams {
/** Number of embedding dimensions (Default depends on model)
*
* @group param
*/
val dimension = new IntParam(this, "dimension", "Number of embedding dimensions").setProtected()
/** @group setParam */
def setDimension(value: Int): this.type = set(this.dimension, value)
/** @group getParam */
def getDimension: Int = $(dimension)
protected def wrapEmbeddingsMetadata(
col: Column,
embeddingsDim: Int,
embeddingsRef: Option[String] = None): Column = {
val metadataBuilder: MetadataBuilder = new MetadataBuilder()
metadataBuilder.putString("annotatorType", AnnotatorType.WORD_EMBEDDINGS)
metadataBuilder.putLong("dimension", embeddingsDim.toLong)
embeddingsRef.foreach(ref => metadataBuilder.putString("ref", ref))
col.as(col.toString, metadataBuilder.build)
}
protected def wrapSentenceEmbeddingsMetadata(
col: Column,
embeddingsDim: Int,
embeddingsRef: Option[String] = None): Column = {
val metadataBuilder: MetadataBuilder = new MetadataBuilder()
metadataBuilder.putString("annotatorType", AnnotatorType.SENTENCE_EMBEDDINGS)
metadataBuilder.putLong("dimension", embeddingsDim.toLong)
embeddingsRef.foreach(ref => metadataBuilder.putString("ref", ref))
col.as(col.toString, metadataBuilder.build)
}
}