// destroy an instance of this class.
  virtual void Release() = 0;

  // Creates an operation builder and ties it to this context.
  // The returned object can be used for setting operation's attributes,
  // adding inputs and finally executing (immediately or lazily as in tracing)
  // it in this context.
  virtual AbstractOperation* CreateOperation() = 0;

  // Registers a function with this context, after this the function is

        final StopwordsItem other = (StopwordsItem) obj;
        return java.util.Objects.equals(input, other.input);
    }

    @Override
    public String toString() {
        return "StopwordsItem [id=" + id + ", inputs=" + input + ", newInputs=" + newInput + "]";
    }

    /**
     * Converts the item to a string representation for writing to a file.
     *
     * @return The stopword as a string.
     */

```json
{
    "detail": [
        {
            "type": "extra_forbidden",
            "loc": ["header", "tool"],
            "msg": "Extra inputs are not permitted",
            "input": "plumbus",
        }
    ]
}
```

## Desativar conversão de underscores { #disable-convert-underscores }

```json
{
    "detail": [
        {
            "type": "extra_forbidden",
            "loc": ["header", "tool"],
            "msg": "Extra inputs are not permitted",
            "input": "plumbus",
        }
    ]
}
```

## Desactivar la conversión de guiones bajos { #disable-convert-underscores }

```

他们将收到一个**错误**响应，告诉他们查询参数 `tool` 是不允许的：

```json
{
    "detail": [
        {
            "type": "extra_forbidden",
            "loc": ["query", "tool"],
            "msg": "Extra inputs are not permitted",
            "input": "plumbus"
        }
    ]
}
```

## 总结

你可以使用 **Pydantic 模型**在 **FastAPI** 中声明**查询参数**。😎

/// tip

    assert response.json() == snapshot(
        {
            "detail": [
                {
                    "type": "extra_forbidden",
                    "loc": ["header", "tool"],
                    "msg": "Extra inputs are not permitted",
                    "input": "plumbus",
                }
            ]
        }
    )


def test_openapi_schema(client: TestClient):
    response = client.get("/openapi.json")

/**
 * Tests for the MacHashFunction.
 *
 * @author Kurt Alfred Kluever
 */
@NullUnmarked
public class MacHashFunctionTest extends TestCase {

  private static final ImmutableSet<String> INPUTS = ImmutableSet.of("", "Z", "foobar");

  private static final SecretKey MD5_KEY =
      new SecretKeySpec("secret key".getBytes(UTF_8), "HmacMD5");
  private static final SecretKey SHA1_KEY =

  private static final int[] nonzero = new int[ARRAY_SIZE];
  private static final int[] ints = new int[ARRAY_SIZE];

  @BeforeExperiment
  void setUp() {
    for (int i = 0; i < ARRAY_SIZE; i++) {
      positive[i] = randomPositiveBigInteger(Integer.SIZE - 2).intValue();
      nonzero[i] = randomNonZeroBigInteger(Integer.SIZE - 2).intValue();
      ints[i] = RANDOM_SOURCE.nextInt();
    }
  }

Therefore, if you run a `tf.train.Server` in your network, anybody with access
to the network can execute arbitrary code with the privileges of the user
running the `tf.train.Server`.

## Untrusted inputs during training and prediction

TensorFlow supports a wide range of input data formats. For example it can
process images, audio, videos, and text. There are several modules specialized

  public void testIteratorMinAndMax() {
    List<Integer> ints = Lists.newArrayList(5, 3, 0, 9);
    assertEquals(9, (int) numberOrdering.max(ints.iterator()));
    assertEquals(0, (int) numberOrdering.min(ints.iterator()));

    // when the values are the same, the first argument should be returned
    Integer a = new Integer(4);
    Integer b = new Integer(4);
    ints = Lists.newArrayList(a, b, b);