if s.ipos > s.ifill { // internal buffer is exhausted
		s.ifill = <-s.fillReady

		s.buf[0] = s.buf[len(s.buf)-1] // copy current last item to guarantee lookback
		copy(s.buf[1:], s.nbuf[:])     // copy contents of pre-filled next buffer
		s.ipos = 1                     // move to beginning of internal buffer

		// request next fill to be prepared
		if s.end == maxInt {
			s.fillReq <- struct{}{}
		}
	}

	s.pos++

 */
@CacheableTask
abstract class GenerateAutoTestedSamplesTestTask @Inject constructor(@Internal val fileOperations: FileOperations) : DefaultTask() {
    private
    val sampleStart = Pattern.compile("""<pre class=['"]autoTested(.*?)['"].*?>""")

    @get:InputFiles
    @get:PathSensitive(PathSensitivity.RELATIVE)
    abstract val mainSources: ConfigurableFileCollection

    @get:Input

			References: []Reference{{"ID", "User", "UserID", "Account", "", true}},
		},
		{
			Name: "Pets", Type: schema.HasMany, Schema: "User", FieldSchema: "Pet",
			References: []Reference{{"ID", "User", "UserID", "Pet", "", true}},
		},
		{
			Name: "Toys", Type: schema.HasMany, Schema: "User", FieldSchema: "Toy",
			Polymorphic: Polymorphic{ID: "OwnerID", Type: "OwnerType", Value: "users"},

 * It can identify areas where string deduplication could provide significant memory savings.</p>
 *
 * <p>Usage example:</p>
 * <pre>
 * PomMemoryAnalyzer analyzer = new PomMemoryAnalyzer();
 * Model model = reader.read(Files.newInputStream(pomPath));
 * analyzer.analyzePom(model);
 * analyzer.printAnalysis();
 * </pre>
 *
 * <p>The analysis output includes:</p>
 * <ul>
 *   <li>Total memory usage per POM path</li>

	}
	return &SMA{
		buf:    make([]float64, ln),
		window: ln,
		idx:    0,
	}
}

func (s *SMA) addSample(next float64) {
	prev := s.buf[s.idx]
	s.buf[s.idx] = next

	if s.filledBuf {
		s.prevSMA += (next - prev) / float64(s.window)
		s.CAvg += (next - s.CAvg) / float64(s.window)
	} else {
		s.CAvg = s.simpleMovingAvg()
		s.prevSMA = s.CAvg
	}
	if s.idx == s.window-1 {

                try {
                    if (securityDispatcher.isLegacyEncryptedString(password)) {
                        problems.add(new DefaultSettingsProblem(
                                "Pre-Maven 4 legacy encrypted password detected for server " + server.getId()
                                        + " - configure password encryption with the help of mvnenc to be compatible with Maven 4.",

   
      * Try Google Colab to use TensorFlow.
         * The easiest way to use TF will be to switch to [google colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb#recent=true). You get pre-installed latest stable TF version. Also you can use ```pip install```  to install any other preferred TF version.

	} else if debug == "false" {
		db.Logger = db.Logger.LogMode(logger.Silent)
	}

	return
}

func RunMigrations() {
	var err error
	allModels := []interface{}{&User{}, &Account{}, &Pet{}, &Company{}, &Toy{}, &Language{}, &Coupon{}, &CouponProduct{}, &Order{}, &Parent{}, &Child{}, &Tools{}}
	rand.Seed(time.Now().UnixNano())

    private final Set<String> blockContent = new HashSet<String>();

    public HtmlToXmlJavadocLexer(JavadocLexer lexer) {
        this.lexer = lexer;
        blockElements.add("p");
        blockElements.add("pre");
        blockElements.add("ul");
        blockElements.add("ol");
        blockElements.add("li");
        blockElements.add("h1");
        blockElements.add("h2");
        blockElements.add("h3");

 * the maximum depth of crawling, and URL filters.
 *
 * <p>Example usage:
 * <pre>
 *   Crawler crawler = new Crawler();
 *   crawler.addUrl("http://example.com/");
 *   crawler.execute();
 *   crawler.close();
 * </pre>
 */
public class Crawler implements Runnable, AutoCloseable {

    private static final Logger logger = LogManager.getLogger(Crawler.class);