constraints.NotEmpty.message                = {item} may not be empty.
constraints.ParametersScriptAssert.message  = script expression "{script}" didn't evaluate to true.
constraints.Range.message                   = {item} must be between {min} and {max}.
constraints.SafeHtml.message                = {item} may have unsafe html content.

   * guaranteed to be exactly +/-1 even when the data are perfectly (anti-)correlated, due to
   * numerical errors. However, it is guaranteed to be in the inclusive range [-1, +1].
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link

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;

  /**
   * Translates a specified portion of our currently stored permits which we want to spend/acquire,
   * into a throttling time. Conceptually, this evaluates the integral of the underlying function we
   * use, for the range of [(storedPermits - permitsToTake), storedPermits].
   *
   * <p>This always holds: {@code 0 <= permitsToTake <= storedPermits}
   */
  abstract long storedPermitsToWaitTime(double storedPermits, double permitsToTake);

		config.KV{
			Key:   config.Enable,
			Value: config.EnableOn,
		},
		config.KV{
			Key: target.KafkaBrokers,
			Value: func() string {
				var brokers []string
				for _, broker := range cfg.Brokers {
					brokers = append(brokers, broker.String())
				}
				return strings.Join(brokers, config.ValueSeparator)
			}(),
		},
		config.KV{
			Key:   target.KafkaTopic,
			Value: cfg.Topic,
		},

// POSIX specifies a sum of the unsigned byte values, but the Sun tar used
// signed byte values.
// We compute and return both.
func (b *block) computeChecksum() (unsigned, signed int64) {
	for i, c := range b {
		if 148 <= i && i < 156 {
			c = ' ' // Treat the checksum field itself as all spaces.
		}
		unsigned += int64(c)
		signed += int64(int8(c))
	}
	return unsigned, signed
}

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;

  if (!status->status.ok()) return nullptr;

  if (input_index >= op_def->input_arg_size() || input_index < 0) {
    status->status = tensorflow::errors::InvalidArgument(
        input_index, " out of range for ", op_name);
    return nullptr;
  }

  const tensorflow::OpDef_ArgDef& input_arg = op_def->input_arg()[input_index];

  if (input_arg.number_attr().empty()) {

   * guaranteed to be exactly +/-1 even when the data are perfectly (anti-)correlated, due to
   * numerical errors. However, it is guaranteed to be in the inclusive range [-1, +1].
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link

	full, frag, n, err := b.collectFragments(delim)
	// Allocate new buffer to hold the full pieces and the fragment.
	buf := make([]byte, n)
	n = 0
	// Copy full pieces and fragment in.
	for i := range full {
		n += copy(buf[n:], full[i])
	}
	copy(buf[n:], frag)
	return buf, err
}

// ReadString reads until the first occurrence of delim in the input,