/*
* 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.
*/
module.exports = function(kernelP) {
return (function() {
var Utils = require('../utils.js');
var gKernelP = kernelP;
/**
* @classdesc
* A simple pipeline, which acts as an estimator. A Pipeline consists of a sequence of stages, each
* of which is either an {@link module:eclairjs/ml.Estimator} or a {@link module:eclairjs/ml.Transformer}.
* When {@link module:eclairjs/ml.Pipeline#fit} is called, the
* stages are executed in order. If a stage is an {@link module:eclairjs/ml.Estimator}, its {@link module:eclairjs/ml.Estimator#fit} method will
* be called on the input dataset to fit a model. Then the model, which is a transformer, will be
* used to transform the dataset as the input to the next stage. If a stage is a {@link Transformer},
* its {@link module:eclairjs/ml.Transformer#transform} method will be called to produce the dataset for the next stage.
* The fitted model from a {@link Pipeline} is an {@link module:eclairjs/ml.PipelineModel}, which consists of fitted models and
* transformers, corresponding to the pipeline stages. If there are no stages, the pipeline acts as
* an identity transformer.
* @class
* @memberof module:eclairjs/ml
* @param {string} [uid]
*/
function Pipeline() {
Utils.handleConstructor(this, arguments, gKernelP);
}
/**
* @param {module:eclairjs/ml.PipelineStage[]} value
* @returns {module:eclairjs/ml.Pipeline}
*/
Pipeline.prototype.setStages = function(value) {
var args = {
target: this,
method: 'setStages',
args: Utils.wrapArguments(arguments),
returnType: Pipeline
};
return Utils.generate(args);
};
/**
* @returns {Promise.<PipelineStage[]>}
*/
Pipeline.prototype.getStages = function() {
var PipelineStage = require('./PipelineStage')();
var args = {
target: this,
method: 'setStages',
args: Utils.wrapArguments(arguments),
returnType: [PipelineStage]
};
return Utils.generate(args);
};
/**
* Fits the pipeline to the input dataset with additional parameters. If a stage is an
* {@link Estimator}, its [[Estimator#fit]] method will be called on the input dataset to fit a model.
* Then the model, which is a transformer, will be used to transform the dataset as the input to
* the next stage. If a stage is a {@link Transformer}, its [[Transformer#transform]] method will be
* called to produce the dataset for the next stage. The fitted model from a {@link Pipeline} is an
* {@link PipelineModel}, which consists of fitted models and transformers, corresponding to the
* pipeline stages. If there are no stages, the output model acts as an identity transformer.
*
* @param {module:eclairjs/sql.Dataset} dataset input dataset
* @returns {module:eclairjs/ml.PipelineModel} fitted pipeline
*/
Pipeline.prototype.fit = function(dataset) {
var PipelineModel = require('./PipelineModel')();
var args = {
target: this,
method: 'fit',
args: Utils.wrapArguments(arguments),
returnType: PipelineModel
};
return Utils.generate(args);
};
/**
* @param {module:eclairjs/ml/param.ParamMap} extra
* @returns {module:eclairjs/ml.Pipeline}
*/
Pipeline.prototype.copy = function(extra) {
var args = {
target: this,
method: 'copy',
args: Utils.wrapArguments(arguments),
returnType: Pipeline
};
return Utils.generate(args);
};
/**
* Derives the output schema from the input schema.
* @param {module:eclairjs/sql/types.StructType} schema
* @returns {module:eclairjs/sql/types.StructType}
*/
Pipeline
Pipeline.prototype.transformSchema = function(schema) {
var StructType = require('../sql/types/StructType')();
var args = {
target: this,
method: 'transformSchema',
args: Utils.wrapArguments(arguments),
returnType: StructType
};
return Utils.generate(args);
};
/**
* @returns {MLWriter}
*/
Pipeline.prototype.write = function() {
throw "not implemented by ElairJS";
// var args ={
// target: this,
// method: 'write',
// returnType: MLWriter
//
// };
//
// return Utils.generate(args);
};
//
// static methods
//
/**
* @returns {MLReader}
*/
Pipeline.read = function() {
throw "not implemented by ElairJS";
// var args ={
// target: Pipeline,
// method: 'read',
// returnType: MLReader
//
// };
//
// return Utils.generate(args);
};
/**
* @param {string} path
* @returns {module:eclairjs/ml.Pipeline}
*/
Pipeline.load = function(path) {
var args = {
target: Pipeline,
method: 'load',
kernelP: gKernelP,
static: true,
args: Utils.wrapArguments(arguments),
returnType: Pipeline
};
return Utils.generate(args);
};
Pipeline.moduleLocation = '/ml/Pipeline';
return Pipeline;
})();
};