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/** Copyright 2015 TappingStone, Inc.
*
* 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 io.prediction.controller
import org.apache.spark.SparkContext
/** Mix in and implement this trait if your model cannot be persisted by
* PredictionIO automatically. A companion object extending
* IPersistentModelLoader is required for PredictionIO to load the persisted
* model automatically during deployment.
*
* Notice that models generated by [[PAlgorithm]] cannot be persisted
* automatically by nature and must implement these traits if model persistence
* is desired.
*
* {{{
* class MyModel extends PersistentModel[MyParams] {
* def save(id: String, params: MyParams, sc: SparkContext): Boolean = {
* ...
* }
* }
*
* object MyModel extends PersistentModelLoader[MyParams, MyModel] {
* def apply(id: String, params: MyParams, sc: Option[SparkContext]): MyModel = {
* ...
* }
* }
* }}}
*
* In Java, all you need to do is to implement this interface, and add a static
* method with 3 arguments of type String, [[Params]], and SparkContext.
*
* {{{
* public class MyModel implements PersistentModel<MyParams>, Serializable {
* ...
* public boolean save(String id, MyParams params, SparkContext sc) {
* ...
* }
*
* public static MyModel load(String id, Params params, SparkContext sc) {
* ...
* }
* ...
* }
* }}}
*
* @tparam AP Algorithm parameters class.
* @see [[PersistentModelLoader]]
* @group Algorithm
*/
trait PersistentModel[AP <: Params] {
/** Save the model to some persistent storage.
*
* This method should return true if the model has been saved successfully so
* that PredictionIO knows that it can be restored later during deployment.
* This method should return false if the model cannot be saved (or should
* not be saved due to configuration) so that PredictionIO will re-train the
* model during deployment. All arguments of this method are provided by
* automatically by PredictionIO.
*
* @param id ID of the run that trained this model.
* @param params Algorithm parameters that were used to train this model.
* @param sc An Apache Spark context.
*/
def save(id: String, params: AP, sc: SparkContext): Boolean
}
/** Implement an object that extends this trait for PredictionIO to support
* loading a persisted model during serving deployment.
*
* @tparam AP Algorithm parameters class.
* @tparam M Model class.
* @see [[PersistentModel]]
* @group Algorithm
*/
trait PersistentModelLoader[AP <: Params, M] {
/** Implement this method to restore a persisted model that extends the
* [[PersistentModel]] trait. All arguments of this method are provided
* automatically by PredictionIO.
*
* @param id ID of the run that trained this model.
* @param params Algorithm parameters that were used to train this model.
* @param sc An optional Apache Spark context. This will be injected if the
* model was generated by a [[PAlgorithm]].
*/
def apply(id: String, params: AP, sc: Option[SparkContext]): M
}
/** DEPRECATED. Use [[PersistentModel]] instead.
*
* @group Algorithm */
@deprecated("Use PersistentModel instead.", "0.9.2")
trait IPersistentModel[AP <: Params] extends PersistentModel[AP]
/** DEPRECATED. Use [[PersistentModelLoader]] instead.
*
* @group Algorithm */
@deprecated("Use PersistentModelLoader instead.", "0.9.2")
trait IPersistentModelLoader[AP <: Params, M] extends PersistentModelLoader[AP, M]