* list to {@link com.google.common.collect.ImmutableList#copyOf(Collection) ImmutableList.copyOf}
   * and use that list instead.
   */
  public List<Long> asList() {
    /*
     * Typically we cache this kind of thing, but much repeated use of this view is a performance
     * anti-pattern anyway. If we cache, then everyone pays a price in memory footprint even if

   * returned list to {@link com.google.common.collect.ImmutableList#copyOf(Collection)
   * ImmutableList.copyOf} and use that list instead.
   */
  public List<Integer> asList() {
    /*
     * Typically we cache this kind of thing, but much repeated use of this view is a performance
     * anti-pattern anyway. If we cache, then everyone pays a price in memory footprint even if

// This builder is used in the eager API to build a NodeDef.
struct TF_AttrBuilder : public tensorflow::AttrBuilder {
  using tensorflow::AttrBuilder::AttrBuilder;
  // The string buffers to make sure that any `attr_name` we pass into
  // `builder->Set()` will outlive the subsequent
  // `TF_AttrBuilderCheckCanRunOnDevice()` call(s) on the same `builder`.
  std::set<std::string> attr_names;
};

func (b *Reader) Reset(r io.Reader) {
	// If a Reader r is passed to NewReader, NewReader will return r.
	// Different layers of code may do that, and then later pass r
	// to Reset. Avoid infinite recursion in that case.
	if b == r {
		return
	}
	if b.buf == nil {
		b.buf = make([]byte, defaultBufSize)
	}
	b.reset(b.buf, r)
}

// You must use TF_AddInput() for the first input (since it takes a
// single tensor), and TF_AddInputList() for the second input (since
// it takes a list, even if you were to pass a list with a single
// tensor), as in:
//   TF_OperationDescription* desc = TF_NewOperation(graph, "Concat", "c");
//   TF_Output concat_dim_input = {...};
//   TF_AddInput(desc, concat_dim_input);

    server.enqueue(MockResponse().setSocketPolicy(SocketPolicy.DISCONNECT_DURING_REQUEST_BODY))
    // Limit the size of the request body that the server holds in memory to an arbitrary
    // 3.5 MBytes so this test can pass on devices with little memory.
    server.bodyLimit = 7 * 512 * 1024
    val connection = server.url("/").toUrl().openConnection() as HttpURLConnection
    connection.setRequestMethod("POST")
    connection.setDoOutput(true)

        if (!hasNext()) {
          throw new NoSuchElementException();
        }
        /*
         * requireNonNull is safe because our callers always pass non-null arguments. Each element
         * of the array becomes null only when we iterate past it and then clear it.
         */
        I result = requireNonNull(elements[index]);
        elements[index] = null;
        index++;
        return result;
      }

 *
 * <ol>
 *   <li>Expose a public method, known as the <i>event subscriber</i>, which accepts a single
 *       argument of the type of event desired;
 *   <li>Mark it with a {@link Subscribe} annotation;
 *   <li>Pass itself to an EventBus instance's {@link #register(Object)} method.
 * </ol>
 *
 * <h2>Posting Events</h2>
 *
 * <p>To post an event, simply provide the event object to the {@link #post(Object)} method. The

///

## Password hashing { #password-hashing }

"Hashing" means converting some content (a password in this case) into a sequence of bytes (just a string) that looks like gibberish.

Whenever you pass exactly the same content (exactly the same password) you get exactly the same gibberish.

But you cannot convert from the gibberish back to the password.

### Why use password hashing { #why-use-password-hashing }

   * Returns the identity function.
   *
   * <p><b>Discouraged:</b> Prefer using a lambda like {@code v -> v}, which is shorter and often
   * more readable.
   */
  // implementation is "fully variant"; E has become a "pass-through" type
  @SuppressWarnings("unchecked")
  public static <E extends @Nullable Object> Function<E, E> identity() {
    return (Function<E, E>) IdentityFunction.INSTANCE;
  }

  // enum singleton pattern