繼承自 `str` 之後，API 文件就能知道這些值的型別必須是 `string`，並能正確地呈現。

然後建立具有固定值的類別屬性，這些就是可用的有效值：

{* ../../docs_src/path_params/tutorial005_py310.py hl[1,6:9] *}

/// tip

如果你在想，「AlexNet」、「ResNet」和「LeNet」只是一些機器學習 <dfn title="嚴格來說是深度學習的模型架構">模型</dfn> 的名字。

///

### 宣告一個「路徑參數」 { #declare-a-path-parameter }

接著使用你建立的列舉類別（`ModelName`）作為型別註記，建立一個「路徑參數」：

    getAll(cache, asList(46));
    CacheTesting.drainRecencyQueues(cache);
    assertThat(keySet).contains(0);
  }

  public void testEviction_invalidateAll() {
    // test that .invalidateAll() resets total weight state correctly
    IdentityLoader<Integer> loader = identityLoader();
    LoadingCache<Integer, Integer> cache =
        CacheBuilder.newBuilder().concurrencyLevel(1).maximumSize(10).build(loader);

{* ../../docs_src/path_params/tutorial005_py310.py hl[1,6:9] *}

/// tip | Astuce

Si vous vous demandez, « AlexNet », « ResNet » et « LeNet » sont juste des noms de <dfn title="Techniquement, architectures de modèles de Deep Learning">modèles</dfn> de Machine Learning.

///

### Déclarer un paramètre de chemin { #declare-a-path-parameter }

            // Write valid response data
            SMBUtil.writeInt4(15, buffer, 0);
            SMBUtil.writeInt4(16384, buffer, 4);
            SMBUtil.writeInt4(245760, buffer, 8);
            // Fill rest with random data
            for (int i = 12; i < buffer.length; i++) {
                buffer[i] = (byte) (i % 256);
            }

            int bytesDecoded = response.decode(buffer, 0, buffer.length);

            byte[] buffer = new byte[10];
            int bufferIndex = 0;

            // Write structure size = 4
            SMBUtil.writeInt2(4, buffer, bufferIndex);

            // Fill rest of buffer with garbage
            for (int i = 2; i < buffer.length; i++) {
                buffer[i] = (byte) 0xFF;
            }

            // Should only read the structure size (2 bytes) and not go beyond

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/fastapi/fastapi/pull/26"><small>(ref)</small></a></div>

---

"_We adopted the **FastAPI** library to spawn a **REST** server that can be queried to obtain **predictions**. [for Ludwig]_"

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/fastapi/fastapi/pull/26"><small>(ref)</small></a></div>

---

"_我們採用了 **FastAPI** 函式庫來啟動一個 **REST** 伺服器，供查詢以取得**預測**。[for Ludwig]_"

<div style="text-align: right; margin-right: 10%;">Piero Molino, Yaroslav Dudin, and Sai Sumanth Miryala - <strong>Uber</strong> <a href="https://eng.uber.com/ludwig-v0-2/"><small>(ref)</small></a></div>

        b = Multisets.immutableEntry(entries.get(1), sortedMultiset.count(entries.get(1)));
        c = Multisets.immutableEntry(entries.get(2), sortedMultiset.count(entries.get(2)));
      }
    }
  }

  /** Resets the contents of sortedMultiset to have entries a, c, for the navigation tests. */
  // Needed to stop Eclipse whining
  private void resetWithHole() {
    List<E> container = new ArrayList<>();

Then, using the certificate, the client and the TLS Termination Proxy **decide how to encrypt** the rest of the **TCP communication**. This completes the **TLS Handshake** part.

The important thing to remember is that **the first *type parameter*** you pass to `Annotated` is the **actual type**. The rest, is just metadata for other tools.

For now, you just need to know that `Annotated` exists, and that it's standard Python. 😎

Later you will see how **powerful** it can be.

/// tip