com.johnsnowlabs.nlp.HasPretrained.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
import com.johnsnowlabs.nlp.pretrained.ResourceDownloader
import org.apache.spark.ml.PipelineStage
import org.apache.spark.ml.util.{DefaultParamsReadable, MLReader}
trait HasPretrained[M <: PipelineStage] {
/** Only MLReader types can use this interface */
this: { def read: MLReader[M] } =>
val defaultModelName: Option[String]
val defaultLang: String = "en"
lazy val defaultLoc: String = ResourceDownloader.publicLoc
implicit private val companion: DefaultParamsReadable[M] =
this.asInstanceOf[DefaultParamsReadable[M]]
private val errorMsg =
s"${this.getClass.getName} does not have a default pretrained model. Please provide a model name."
/** Java default argument interoperability */
def pretrained(name: String, lang: String, remoteLoc: String): M = {
if (Option(name).isEmpty)
throw new NotImplementedError(errorMsg)
ResourceDownloader.downloadModel(companion, name, Option(lang), remoteLoc)
}
def pretrained(name: String, lang: String): M = pretrained(name, lang, defaultLoc)
def pretrained(name: String): M = pretrained(name, defaultLang, defaultLoc)
def pretrained(): M =
pretrained(defaultModelName.getOrElse(throw new Exception(errorMsg)), defaultLang, defaultLoc)
}