/*
* Copyright 2016 IBM Corp.
*
* 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.
*/
(function () {
var JavaWrapper = require(EclairJS_Globals.NAMESPACE + '/JavaWrapper');
var Logger = require(EclairJS_Globals.NAMESPACE + '/Logger');
var Utils = require(EclairJS_Globals.NAMESPACE + '/Utils');
/**
* Class used to compute the gradient for a loss function, given a single data point.
* @class
* @memberof module:eclairjs/mllib/optimization
* @constructor
*/
var Gradient = function () {
this.logger = Logger.getLogger("Gradient_js");
var jvmObject;
if (arguments[0] instanceof org.apache.spark.mllib.optimization.Gradient) {
jvmObject = arguments[0];
} else {
jvmObject = new org.apache.spark.mllib.optimization.Gradient();
}
JavaWrapper.call(this, jvmObject);
};
Gradient.prototype = Object.create(JavaWrapper.prototype);
Gradient.prototype.constructor = Gradient;
/**
* Compute the gradient and loss given the features of a single data point.
* @param {module:eclairjs/mllib/linalg.Vector} data
* @param {float} label
* @param {module:eclairjs/mllib/linalg.Vector} weights
* @returns {module:eclairjs.Tuple2}
*/
Gradient.prototype.compute = function (data,label,weights) {
var data_uw = Utils.unwrapObject(data);
var weights_uw = Utils.unwrapObject(weights);
var javaObject = this.getJavaObject().compute(data_uw,label,weights_uw);
Tuple2 = require('eclairjs/Tuple2');
return new Tuple2(javaObject);
};
module.exports = Gradient;
})();