* size of the input (in bytes). This is only important for non-streaming hash functions (hash
   * functions that need to buffer their whole input before processing any of it).
   */
  Hasher newHasher(int expectedInputSize);

  /**
   * Shortcut for {@code newHasher().putInt(input).hash()}; returns the hash code for the given

"}.fa-deviantart:before{content:"\f1bd"}.fa-dharmachakra:before{content:"\f655"}.fa-dhl:before{content:"\f790"}.fa-diagnoses:before{content:"\f470"}.fa-diaspora:before{content:"\f791"}.fa-dice:before{content:"\f522"}.fa-dice-d20:before{content:"\f6cf"}.fa-dice-d6:before{content:"\f6d1"}.fa-dice-five:before{content:"\f523"}.fa-dice-four:before{content:"\f524"}.fa-dice-one:before{content:"\f525"}.fa-dice-six:before{content:"\f526"}.fa-dice-three:before{content:"\f527"}.fa-dice-two:before{content:"...

 * those classes explore numerous corner cases. The intent here is to confirm that everything is
 * wired up properly.
 *
 * @author Craig Berry
 */
public final class HostSpecifierTest extends TestCase {

  private static final ImmutableList<String> GOOD_IPS =
      ImmutableList.of("1.2.3.4", "2001:db8::1", "[2001:db8::1]");

 * those classes explore numerous corner cases. The intent here is to confirm that everything is
 * wired up properly.
 *
 * @author Craig Berry
 */
public final class HostSpecifierTest extends TestCase {

  private static final ImmutableList<String> GOOD_IPS =
      ImmutableList.of("1.2.3.4", "2001:db8::1", "[2001:db8::1]");

```Python hl_lines="2  7"
{!../../docs_src/custom_response/tutorial001b.py!}
```

/// info

    /**
     * Indicates whether the model building should happen in two phases. If enabled, the initial invocation of the model
     * builder will only produce an interim result which may be used to analyze inter-model dependencies before the
     * final invocation of the model builder is performed.
     *
     * @return {@code true} if two-phase building is enabled, {@code false} if the model should be build in a single
     *         step.
     */

   * example during quiescent points between multithreaded computations. If there are updates
   * concurrent with this method, the returned value is not guaranteed to be the final
   * value occurring before the reset.
   *
   * @return the sum
   */
  public long sumThenReset() {
    long sum = base;
    Cell[] as = cells;
    base = 0L;
    if (as != null) {
      int n = as.length;

 * views are modifiable.
 *
 * <p>This class is not threadsafe when any concurrent operations update the multimap. Concurrent
 * read operations will work correctly if the last write <i>happens-before</i> any reads. To allow
 * concurrent update operations, wrap your multimap with a call to {@link
 * Multimaps#synchronizedSetMultimap}.
 *

  int num_dims = TF_NumDims(t);
  for (int i = 0; i < num_dims; i++) {
    out_dims[i] = TF_Dim(t, i);
  }
}

// Runs model as is if output is a scalar,
// else sums the output tensor before returning.
absl::Status RunAndMaybeSum(AbstractContext* ctx, Model forward,
                            absl::Span<AbstractTensorHandle* const> inputs,
                            absl::Span<AbstractTensorHandle*> outputs,

	if w != nil {
		return w.Flush()
	}
	return nil
}

func (s *XdsStatusWriter) setupStatusPrint(drs map[string]*discovery.DiscoveryResponse) (*tabwriter.Writer, []*xdsWriterStatus, error) {
	// Gather the statuses before printing so they may be sorted
	var fullStatus []*xdsWriterStatus
	mappedResp := map[string]string{}
	w := new(tabwriter.Writer).Init(s.Writer, 0, 8, 5, ' ', 0)