[ML] Train - added a test method for trained model

[ML] Train - added a test method for trained model

[ACR] https://code.sec.samsung.net/jira/browse/TWDAPI-285

[Verification] Code compiles without errors.
Verification method is available in JS console.

var trainsetFile = "documents/trainingSet.dat";
var validsetFile = "documents/valSet.dat";
// TODO should support virtual roots
var outputFile = "/home/owner/media/Documents/webapi_tizen_model.bin"
var m = tizen.ml.trainer.createModel()

var l1 = tizen.ml.trainer.createLayer("LAYER_IN")
l1.setProperty("input_shape", "1:1:62720")
l1.setProperty("normalization", "true")
l1.setProperty("name", "inputlayer")
m.addLayer(l1)

var l2 = tizen.ml.trainer.createLayer("LAYER_FC")
l2.setProperty("unit", "10")
l2.setProperty("activation", "softmax")
l2.setProperty("bias_initializer", "zeros")
l2.setProperty("weight_regularizer", "l2norm")
l2.setProperty("weight_regularizer_constant", "0.005")
l2.setProperty("weight_initializer", "xavier_uniform")
l2.setProperty("name", "fc1")
l2.setProperty("input_layers", "inputlayer")
m.addLayer(l2)

var opt = tizen.ml.trainer.createOptimizer("OPTIMIZER_ADAM")
opt.setProperty("learning_rate", "0.0001")
opt.setProperty("decay_rate", "0.96")
opt.setProperty("decay_steps", "1000")
opt.setProperty("beta1", "0.002")
opt.setProperty("beta2", "0.001")
opt.setProperty("epsilon", "1e-7")
m.setOptimizer(opt);

var dataset = tizen.ml.trainer.createFileDataset(trainsetFile, validsetFile, /*no test file*/);
dataset.setProperty("buffer_size", "100", "MODE_TRAIN");
dataset.setProperty("buffer_size", "100", "MODE_VALID");
m.setDataset(dataset);

var compileOpts = {
    loss: "cross", batch_size: "16"
}
m.compile(compileOpts);

var runOpts = {
    epochs: "2", save_path: outputFile
}
m.run(runOpts, (s) => {
    console.log("success");
    console.log("Test result: " + m._checkMetrics(2.163000, 2.267410, 16.666700));
}, (e) => console.log("error " + JSON.stringify(e)));

Change-Id: I4760fe341f58f84c985c6e4e4b609bafe36fb4be