* @param executor the executor to run the listener in
   * @throws RejectedExecutionException if we tried to execute the listener immediately but the
   *     executor rejected it.
   */
  void addListener(Runnable listener, Executor executor);

	// create bucket.
	err = obj.MakeBucket(b.Context(), bucket, MakeBucketOptions{})
	if err != nil {
		b.Fatal(err)
	}

	objSize := 128 * humanize.MiByte

	// PutObjectPart returns etag of the object inserted.
	// etag variable is assigned with that value.
	var etag string
	// get text data generated for number of bytes equal to object size.
	textData := generateBytesData(objSize)
	// generate md5sum for the generated data.

## 获取用户 { #get-the-user }

`get_current_user` 使用创建的（伪）工具函数，该函数接收 `str` 类型的令牌，并返回 Pydantic 的 `User` 模型：

{* ../../docs_src/security/tutorial002_an_py310.py hl[19:22,26:27] *}

## 注入当前用户 { #inject-the-current-user }

在*路径操作* 的 `Depends` 中使用 `get_current_user`：

{* ../../docs_src/security/tutorial002_an_py310.py hl[31] *}

注意，此处把 `current_user` 的类型声明为 Pydantic 的 `User` 模型。

这有助于在函数内部使用代码补全和类型检查。

  }

  private static <N, V> ImmutableMap<N, GraphConnections<N, V>> getNodeConnections(
      ValueGraph<N, V> graph) {
    // ImmutableMap.Builder maintains the order of the elements as inserted, so the map will have
    // whatever ordering the graph's nodes do, so ImmutableSortedMap is unnecessary even if the
    // input nodes are sorted.

	PDEPD R1, R2, R3                        // 7c231138
	PEXTD R1, R2, R3                        // 7c231178
	PLBZ 1234(R1), $0, R3                   // 06000000886104d260000000
	// Note, PLD crosses a 64B boundary, and a nop is inserted between PLBZ and PLD
	PLD 1234(R1), $0, R3                    // 04000000e46104d2
	PLFD 1234(R1), $0, F3                   // 06000000c86104d2
	PLFS 1234567890(R4), $0, F3             // 06004996c06402d2

{* ../../docs_src/security/tutorial002_an_py310.py hl[19:22,26:27] *}

## Inyectar al usuario actual { #inject-the-current-user }

Entonces ahora podemos usar el mismo `Depends` con nuestro `get_current_user` en la *path operation*:

{* ../../docs_src/security/tutorial002_an_py310.py hl[31] *}

                if (label != null && allowedLabels.contains(label)) {
                    validLabels.add(label);
                } else if (logger.isDebugEnabled()) {
                    logger.debug("Rejected unknown label filter value: {}", label);
                }
            }
            if (!validLabels.isEmpty()) {
                fields.put("label", validLabels.toArray(new String[0]));
            }
        }

import com.google.common.escape.Escaper;

/**
 * {@code Escaper} instances suitable for strings to be included in particular sections of URLs.
 *
 * <p>If the resulting URLs are inserted into an HTML or XML document, they will require additional
 * escaping with {@link com.google.common.html.HtmlEscapers} or {@link
 * com.google.common.xml.XmlEscapers}.
 *
 * @author David Beaumont
 * @author Chris Povirk

    @DisplayName("initSecContext throws on invalid token type")
    void testInitSecContextInvalidTokenType(byte firstByte) throws Exception {
        SpnegoContext ctx = newContext();

        // Invalid first byte should be rejected by token parsing
        CIFSException ex = assertThrows(CIFSException.class, () -> ctx.initSecContext(new byte[] { firstByte }, 0, 1));
        assertEquals("Invalid token", ex.getMessage());

vulnerabilities.

## Security properties of execution modes

TensorFlow has several execution modes, with Eager-mode being the default in v2.
Eager mode lets users write imperative-style statements that can be easily
inspected and debugged and it is intended to be used during the development
phase.

As part of the differences that make Eager mode easier to debug, the [shape
inference