/// info | 说明

Python 3.4 及之后版本支持<a href="https://docs.python.org/zh-cn/3/library/enum.html" class="external-link" target="_blank">枚举（即 enums）</a>。

///

/// tip | 提示

**AlexNet**、**ResNet**、**LeNet** 是机器学习<abbr title="技术上来说是深度学习模型架构">模型</abbr>。

///

### 声明*路径参数*

使用 Enum 类（`ModelName`）创建使用类型注解的*路径参数*：

{* ../../docs_src/path_params/tutorial005.py hl[16] *}

### 查看文档

Em seguida, crie atributos de classe com valores fixos, que serão os valores válidos disponíveis:

{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}

/// tip | Dica
Se você está se perguntando, "AlexNet", "ResNet" e "LeNet" são apenas nomes de <abbr title="Tecnicamente, arquiteturas de modelos de Deep Learning">modelos</abbr> de Aprendizado de Máquina.
///

### Declare um parâmetro de path { #declare-a-path-parameter }

/// info | 情報

<a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">Enumerations (もしくは、enums)はPython 3.4以降で利用できます</a>。

///

/// tip | 豆知識

"AlexNet"、"ResNet"そして"LeNet"は機械学習<abbr title="Technically, Deep Learning model architectures">モデル</abbr>の名前です。

///

### *パスパラメータ*の宣言

次に、作成したenumクラスである`ModelName`を使用した型アノテーションをもつ*パスパラメータ*を作成します:

                    throw new SmbException("Account '" + username + "' is locked out until " + account.getLockoutExpiry());
                } else {
                    // Lockout expired, reset
                    account.reset();
                }
            }
        }

        // Check per-IP limit
        if (sourceIp != null) {

        assertEquals(State.OPEN, circuitBreaker.getState(), "Circuit should be OPEN");

        // Manually reset
        circuitBreaker.reset();
        assertEquals(State.CLOSED, circuitBreaker.getState(), "Circuit should be CLOSED after reset");
        assertEquals(0, circuitBreaker.getFailureCount(), "Failure count should be reset");
    }

    @Test
    public void testCustomFailureDetection() throws CIFSException {

    assertEquals("9.999 \u03bcs", stopwatch.toString());
    stopwatch.reset();
    stopwatch.start();
    ticker.advance(1234567);
    assertEquals("1.235 ms", stopwatch.toString());
    stopwatch.reset();
    stopwatch.start();
    ticker.advance(5000000000L);
    assertEquals("5.000 s", stopwatch.toString());
    stopwatch.reset();
    stopwatch.start();
    ticker.advance((long) (1.5 * 60 * 1000000000L));

    var_to_data_type_map_.swap(result.second);
  } else {
    reader_.reset(new TensorSliceReader(filename));
    if (!reader_->status().ok()) {
      tsl::Set_TF_Status_from_Status(status, reader_->status());
      return;
    }
    var_to_shape_map_.reset(
        new TensorSliceReader::VarToShapeMap(reader_->GetVariableToShapeMap()));
    var_to_data_type_map_.reset(new TensorSliceReader::VarToDataTypeMap(

            HMACT64 hmac = new HMACT64(TEST_KEY);
            hmac.engineReset();
            verify(mockMd5, times(2)).reset(); // Once in constructor, once in reset
            verify(mockMd5, times(2)).update(any(byte[].class)); // Once in constructor, once in reset
        }
    }

    @Test
    void testEngineGetDigestLength() throws NoSuchAlgorithmException {
        // Test engineGetDigestLength()

	)

	if config.Colorful {
		infoStr = Green + "%s\n" + Reset + Green + "[info] " + Reset
		warnStr = BlueBold + "%s\n" + Reset + Magenta + "[warn] " + Reset
		errStr = Magenta + "%s\n" + Reset + Red + "[error] " + Reset
		traceStr = Green + "%s\n" + Reset + Yellow + "[%.3fms] " + BlueBold + "[rows:%v]" + Reset + " %s"
		traceWarnStr = Green + "%s " + Yellow + "%s\n" + Reset + RedBold + "[%.3fms] " + Yellow + "[rows:%v]" + Magenta + " %s" + Reset

    assertTrue(reader.markSupported());

    assertEquals(string, readFully(reader));
    assertFullyRead(reader);

    // reset and read again
    reader.reset();
    assertEquals(string, readFully(reader));
    assertFullyRead(reader);

    // reset, skip, mark, then read the rest
    reader.reset();
    assertEquals(5, reader.skip(5));
    reader.mark(Integer.MAX_VALUE);
    assertEquals(string.substring(5), readFully(reader));