@Override
public InputData readInput(Scanner scanner, int testCase) {
InputData in = new InputData(testCase);
in.N = scanner.nextInt();
return in;
}
@Override
public InputData readInput(Scanner scanner, int testCase) {
InputData in = new InputData(testCase);
in.N = scanner.nextInt();
in.highest = new int[in.N - 1];
for (int n = 0; n < in.N - 1; ++n) {
in.highest[n] = scanner.nextInt();
}
return in;
}
@Override
public void execute() throws IOException, RecommenderBuildException {
LenskitConfiguration dataConfig = input.getConfiguration();
LenskitRecommenderEngineBuilder builder = LenskitRecommenderEngine.newBuilder();
for (LenskitConfiguration config : environment.loadConfigurations(getConfigFiles())) {
builder.addConfiguration(config);
}
builder.addConfiguration(dataConfig, ModelDisposition.EXCLUDED);
Stopwatch timer = Stopwatch.createStarted();
LenskitRecommenderEngine engine = builder.build();
timer.stop();
logger.info("built model in {}", timer);
File output = getOutputFile();
CompressionMode comp = CompressionMode.autodetect(output);
logger.info("writing model to {}", output);
Closer closer = Closer.create();
try {
OutputStream stream = closer.register(new FileOutputStream(output));
stream = closer.register(comp.wrapOutput(stream));
engine.write(stream);
} catch (Throwable th) { // NOSONAR using a closer
throw closer.rethrow(th);
} finally {
closer.close();
}
}
@Override
public InputData readInput(Scanner scanner, int testCase) {
InputData in = new InputData(testCase);
in.N = scanner.nextInt();
in.levels = Lists.newArrayList();
/** Number of points(stars) prereq to play level 1 ; Number to play level 2 */
for (int i = 0; i < in.N; ++i) {
in.levels.add(new Level(scanner.nextInt(), scanner.nextInt()));
}
// log.info("TestCase {} Grid {}", testCase, in.grid);
return in;
}
private LenskitRecommenderEngine loadEngine() throws RecommenderBuildException, IOException {
File modelFile = options.get("model_file");
if (modelFile == null) {
logger.info("creating fresh recommender");
LenskitRecommenderEngineBuilder builder = LenskitRecommenderEngine.newBuilder();
for (LenskitConfiguration config : environment.loadConfigurations(getConfigFiles())) {
builder.addConfiguration(config);
}
builder.addConfiguration(input.getConfiguration());
Stopwatch timer = Stopwatch.createStarted();
LenskitRecommenderEngine engine = builder.build();
timer.stop();
logger.info("built recommender in {}", timer);
return engine;
} else {
logger.info("loading recommender from {}", modelFile);
LenskitRecommenderEngineLoader loader = LenskitRecommenderEngine.newLoader();
for (LenskitConfiguration config : environment.loadConfigurations(getConfigFiles())) {
loader.addConfiguration(config);
}
loader.addConfiguration(input.getConfiguration());
Stopwatch timer = Stopwatch.createStarted();
LenskitRecommenderEngine engine;
CompressionMode comp = CompressionMode.autodetect(modelFile);
InputStream input = new FileInputStream(modelFile);
try {
input = comp.wrapInput(input);
engine = loader.load(input);
} finally {
input.close();
}
timer.stop();
logger.info("loaded recommender in {}", timer);
return engine;
}
}
@Test
public void setCalculateSunrisesSunsets() {
String[] coordinates = {InputData.LATITUDE_NAME, InputData.LONGITUDE_NAME};
for (String memberName : coordinates) {
assertTrue(
memberName + " should NOT cause error, when sunrise/sunset calculation isn't needed.",
!isError(memberName));
}
inputData.setCalculateSunrisesSunsets(InputData.DEFAULT_TRUE);
for (String memberName : coordinates) {
assertTrue("Null " + memberName + " should cause error.", isError(memberName));
}
}
public static void configureArguments(ArgumentParser parser) {
parser.description("Trains a recommendation model and write it to disk.");
ScriptEnvironment.configureArguments(parser);
InputData.configureArguments(parser);
parser
.addArgument("-o", "--output-file")
.type(File.class)
.metavar("FILE")
.setDefault("model.bin")
.help("write trained model to FILE");
parser
.addArgument("config")
.type(File.class)
.nargs("+")
.metavar("CONFIG")
.help("load algorithm configuration from CONFIG");
}
public static void configureArguments(ArgumentParser parser) {
InputData.configureArguments(parser);
ScriptEnvironment.configureArguments(parser);
parser
.addArgument("-c", "--config-file")
.type(File.class)
.action(Arguments.append())
.metavar("FILE")
.help("use configuration from FILE");
parser
.addArgument("-m", "--model-file")
.type(File.class)
.metavar("FILE")
.help("load model from FILE");
parser.addArgument("--print-channel").metavar("CHAN").help("also print value from CHAN");
parser.addArgument("user").type(Long.class).metavar("USER").help("predict for USER");
parser
.addArgument("items")
.type(Long.class)
.metavar("ITEM")
.nargs("+")
.help("predict for ITEMs");
}
@Test
public void setLatitudeLongitude() {
java.lang.reflect.Method method;
String[] coordinates = {InputData.LATITUDE_NAME, InputData.LONGITUDE_NAME};
try {
for (String memberName : coordinates) {
String methodName = "set" + memberName;
method = inputData.getClass().getMethod(methodName, String.class);
inputData.initialize();
inputData.setCalculateSunrisesSunsets(null);
assertTrue(
methodName
+ ": At the beginning, there should be no errors:\n\n"
+ inputData.toString(),
!isError(memberName));
method.invoke(inputData, "-961");
assertTrue(
methodName
+ ": Dont test range when sunrise/sunset calculation isn't needed:\n\n"
+ inputData.toString(),
!isError(memberName));
inputData.setCalculateSunrisesSunsets(InputData.DEFAULT_TRUE);
double extreme = (memberName.equals(InputData.LATITUDE_NAME)) ? 90 : 180;
double value = -(extreme + 0.1);
method.invoke(inputData, "" + value);
assertTrue(
methodName + " @ " + value + ": should fail:\n\n" + inputData.toString(),
isError(memberName));
value = -extreme;
method.invoke(inputData, "" + value);
assertTrue(
methodName + " @ " + value + ": should NOT fail:\n\n" + inputData.toString(),
!isError(memberName));
value = 0;
method.invoke(inputData, "" + value);
assertTrue(
methodName + " @ " + value + ": should NOT fail:\n\n" + inputData.toString(),
!isError(memberName));
value = extreme;
method.invoke(inputData, "" + value);
assertTrue(
methodName + " @ " + value + ": should NOT fail:\n\n" + inputData.toString(),
!isError(memberName));
value = extreme + 1.2;
method.invoke(inputData, "" + value);
assertTrue(
methodName + " @ " + value + ": should fail:\n\n" + inputData.toString(),
isError(memberName));
}
} catch (Exception e) {
fail("Exception : " + e.getMessage());
}
}
public OutputData learn(InputData id, Target tg, int k, String task) {
this.k = k;
OutputData ret;
this.col = id.getCol();
this.row = id.getRow();
this.groupNum = id.getGroup();
this.task = task;
this.groupRangeUpperLimit = id.getGroupRangeUpperLimit();
init();
int t = 0;
for (int iter = 0; iter < 100; iter++) { // tmp
System.out.println(iter); // ***********************
double diff = 0;
for (int p = 0; p < id.getRow(); p++, t++) {
// double tmpEta = eater / (t0 + t*0.1);
// double tmpEta = eater / Math.pow((t + 1), power_t);
double eta = 0.005;
Map<Integer, Double> record = id.getOneRecord(p); // pick up one record
double y = tg.getOneTarget(p); // pickup the target for the chosen record
w0 = w0 - eta * (calcGrad(0, record, y, "w0") + 2 * lambda0 * w0);
// System.out.println("w0:" + w0);//**************
for (int i : record.keySet()) {
double gradWi = calcGrad(i, record, y, "w"); // dloss(predict("w", i), y);
int pi = pi(i);
double nextWi = w[i] - eta * (gradWi + 2 * lambdaW.get(pi) * w[i]);
w[i] = nextWi;
for (int f = 0; f < k; f++) {
double gradVij =
dloss(
predict(y, record),
y,
i,
f,
"v",
record); // calcGradV(i, f, pi, y, "v"); // dloss(predict("v", i, f), y)
// System.out.println("key:" + key + ", f:" + f + ", groupOfKey:" + groupOfKey);
// //******************
V[i][f] -= eta * (gradVij + 2 * lambdaV[f][pi] * V[i][f]);
// System.out.println("V[key][f]:" + V[key][f]); //***************
}
}
if (task.equals("regression")) {
double pred = predict(y, record);
double d = y - pred;
diff += d * d;
} else if (task.equals("classification")) {
if (y != predict(y, record)) {
// System.out.println("tg:" + this.tg + ", predict:" + predict()); //****
diff++;
}
}
}
// effect evaluation
results.add(diff);
}
System.out.println(results); // ****
ret = new OutputData(w0, w, V);
return ret;
}
