},
	}

	for idx, r := range results {
		if result := logger.ExplainSQL(r.SQL, r.NumericRegexp, `"`, r.Vars...); result != r.Result {
			t.Errorf("Explain SQL #%v expects %v, but got %v", idx, r.Result, result)
		}
	}

import org.opensearch.search.aggregations.bucket.missing.MissingAggregationBuilder;
import org.opensearch.search.aggregations.bucket.range.IpRangeAggregationBuilder;
import org.opensearch.search.aggregations.bucket.range.RangeAggregationBuilder;
import org.opensearch.search.aggregations.bucket.sampler.SamplerAggregationBuilder;

        int pathConsumed = dr.getPathConsumed();
        if ( pathConsumed < 0 ) {
            log.warn("Path consumed out of range " + pathConsumed);
            pathConsumed = 0;
        }
        else if ( pathConsumed > this.unc.length() ) {
            log.warn("Path consumed out of range " + pathConsumed);
            pathConsumed = oldUncPath.length();
        }

        if ( log.isDebugEnabled() ) {

// https://github.com/containers/podman/blob/master/libpod/runtime.go
//
//	"/.dockerenv":        "file",
//	"/run/.containerenv": "file",
func IsDocker() bool {
	var err error
	for _, envfile := range []string{
		"/.dockerenv",
		"/run/.containerenv",
	} {
		_, err = os.Stat(envfile)
		if err == nil {
			return true
		}
	}
	if osIsNotExist(err) {

}

var errorRune = []byte(string(utf8.RuneError))

// ScanRunes is a split function for a [Scanner] that returns each
// UTF-8-encoded rune as a token. The sequence of runes returned is
// equivalent to that from a range loop over the input as a string, which
// means that erroneous UTF-8 encodings translate to U+FFFD = "\xef\xbf\xbd".
// Because of the Scan interface, this makes it impossible for the client to

    assertFailsWith<IllegalArgumentException> {
      clientWriter.writeClose(98724976, "Hello".encodeUtf8())
    }.also { expected ->
      assertThat(expected.message).isEqualTo("Code must be in range [1000,5000): 98724976")
    }
  }

  @Test fun closeReservedThrows() {
    assertFailsWith<IllegalArgumentException> {
      clientWriter.writeClose(1005, "Hello".encodeUtf8())
    }.also { expected ->

import org.opensearch.search.aggregations.bucket.missing.MissingAggregationBuilder;
import org.opensearch.search.aggregations.bucket.range.IpRangeAggregationBuilder;
import org.opensearch.search.aggregations.bucket.range.RangeAggregationBuilder;
import org.opensearch.search.aggregations.bucket.sampler.SamplerAggregationBuilder;

  /**
   * Returns {@code table[index]}, where {@code table} is actually a {@code byte[]}, {@code
   * short[]}, or {@code int[]}. When it is a {@code byte[]} or {@code short[]}, the returned value
   * is unsigned, so the range of possible returned values is 0–255 or 0–65535, respectively.
   */
  static int tableGet(Object table, int index) {
    if (table instanceof byte[]) {
      return ((byte[]) table)[index] & BYTE_MASK; // unsigned read

constraints.NotEmpty.message                = {item} darf nicht leer sein.
constraints.ParametersScriptAssert.message  = Der Skript-Ausdruck "{script}" hat kein wahres Ergebnis geliefert.
constraints.Range.message                   = {item} muss zwischen {min} und {max} liegen.
constraints.SafeHtml.message                = {item} darf unsicheres HTML enthalten.

to the network can execute arbitrary code with the privileges of the user
running the `tf.train.Server`.

## Untrusted inputs during training and prediction

TensorFlow supports a wide range of input data formats. For example it can
process images, audio, videos, and text. There are several modules specialized
in taking those formats, modifying them, and/or converting them to intermediate