// requireNonNull is safe because of the hasNext check.
      Node<K, V> node = requireNonNull(next);
      next = node.nextInKeyInsertionOrder;
      toRemove = node;
      remaining--;
      return output(node);
    }

    @Override
    public final void remove() {
      if (biMap.modCount != expectedModCount) {
        throw new ConcurrentModificationException();
      }
      if (toRemove == null) {

    /**
     * Wraps exception handling for {@link Properties#store(OutputStream, String)}.
     *
     * <p>
     * The output stream is not closed.
     * </p>
     *
     * @param props
     *            Property set. Must not be {@literal null}.
     * @param out
     *            Output stream. Must not be {@literal null}.
     * @param comments
     *            Comments.
     */

   *
   * <p>This escaper does not escape non-ASCII characters to their numeric character references
   * (NCR). Any non-ASCII characters appearing in the input will be preserved in the output.
   * Specifically "\r" (carriage return) is preserved in the output, which may result in it being
   * silently converted to "\n" when the XML is parsed.
   *
   * <p>This escaper does not treat surrogate pairs specially and does not perform Unicode

     */
    protected OutputStreamUtil() {
    }

    /**
     * Creates a {@link FileOutputStream}.
     *
     * @param file the file (must not be {@literal null})
     * @return a {@link FileOutputStream} to output to the file
     * @see FileOutputStream#FileOutputStream(File)
     */
    public static FileOutputStream create(final File file) {
        assertArgumentNotNull("file", file);

        try {

Ви також можете використовувати поля `bytes` з `ser_json_bytes` у конфігурації моделі для вихідних даних, і Pydantic серіалізує байти як base64 під час формування відповіді JSON.

{* ../../docs_src/json_base64_bytes/tutorial001_py310.py ln[1:2,12:16,29,38:41] hl[16] *}

## Pydantic `bytes` для вхідних і вихідних даних { #pydantic-bytes-for-input-and-output-data }

 */
@J2ktIncompatible
@GwtIncompatible
public final class CountingOutputStream extends FilterOutputStream {

  private long count;

  /**
   * Wraps another output stream, counting the number of bytes written.
   *
   * @param out the output stream to be wrapped
   */
  public CountingOutputStream(OutputStream out) {
    super(checkNotNull(out));
  }

  /** Returns the number of bytes written. */

    private static LogStream inst;

    /**
     * The current logging level.
     */
    public static int level = 1;

    /**
     * Constructs a LogStream with the specified output stream.
     *
     * @param stream the output stream for logging
     */
    public LogStream(final PrintStream stream) {
        super(stream);
    }

    /**
     * Sets the logging level.
     *

				break
			}
		} else if p.arch.Family == sys.Loong64 {
			if arch.IsLoong64RDTIME(op) {
				// The Loong64 RDTIME family of instructions is a bit special,
				// in that both its register operands are outputs
				prog.To = a[0]
				if a[1].Type != obj.TYPE_REG {
					p.errorf("invalid addressing modes for 2nd operand to %s instruction, must be register", op)
					return
				}
				prog.RegTo2 = a[1].Reg
				break

Você receberá uma response assim:

```json
{
  "description": "Some data",
  "content": "hello"
}
```

## Pydantic `bytes` para dados de saída { #pydantic-bytes-for-output-data }

Você também pode usar campos `bytes` com `ser_json_bytes` na configuração do modelo para dados de saída, e o Pydantic irá *serializar* os bytes como base64 ao gerar a response JSON.

  explicit CSession(TF_Session* session);

  ~CSession();

  void SetInputs(std::vector<std::pair<TF_Operation*, TF_Tensor*>> inputs);
  void SetOutputs(std::initializer_list<TF_Operation*> outputs);
  void SetOutputs(const std::vector<TF_Output>& outputs);
  void SetTargets(std::initializer_list<TF_Operation*> targets);

  void Run(TF_Status* s);

  void CloseAndDelete(TF_Status* s);