IsDict(
                    {
                        "type": "extra_forbidden",
                        "loc": ["header", "tool"],
                        "msg": "Extra inputs are not permitted",
                        "input": "plumbus",
                    }
                )
                | IsDict(
                    # TODO: remove when deprecating Pydantic v1
                    {

					Signature: [4]byte{2, 1, 1, 1},
					Type:      ObjectType,
					Flags:     0,
				}},
			},
		},
	}
	inputSerialized := make([]metaCacheEntry, len(inputs))
	for i, xl := range inputs {
		xl.sortByModTime()
		var err error
		entry := metaCacheEntry{
			name: "testobject",
		}
		entry.metadata, err = xl.AppendTo(nil)
		if err != nil {
			t.Fatal(err)
		}

    TFE_TensorHandle* input = TFE_OpGetFlatInput(original_op, j, s);
    if (TF_GetCode(s) != TF_OK) return;
    const char* input_device = TFE_TensorHandleDeviceName(input, s);
    if (TF_GetCode(s) != TF_OK) return;
    if (dev->device_name == input_device) {
      LoggedTensor* t = reinterpret_cast<LoggedTensor*>(
          TFE_TensorHandleDevicePointer(input, s));
      if (TF_GetCode(s) != TF_OK) return;

      TF_GraphToFunction(
          /* fn_body */ body.get(), /* fn_name */ function_name,
          /* append_hash_to_fn_name */ 0, /* num_opers */ 2,
          /* opers */ operations, /* ninputs */ 1, /* inputs */ &x,
          /* noutputs */ 1, /* outputs */ &y, /* output_names */ &output_name,
          /* opts */ nullptr, /* description */ "", /* status */ status),
      TF_DeleteFunction);

@ElementTypesAreNonnullByDefault
public interface Interner<E> {
  /**
   * Chooses and returns the representative instance for any of a collection of instances that are
   * equal to each other. If two {@linkplain Object#equals equal} inputs are given to this method,
   * both calls will return the same instance. That is, {@code intern(a).equals(a)} always holds,
   * and {@code intern(a) == intern(b)} if and only if {@code a.equals(b)}. Note that {@code

ame:"dimension",validatorFunction:function(b,d,e,g,h){if(c){var i=e.get(0).files||[],j=this;e.attr("data-validation").indexOf("mime")===-1?(alert("You should validate file type being jpg, gif or png on input "+e[0].name),b(!1)):i.length>1?(alert("Validating image dimensions does not support inputs allowing multiple files"),b(!1)):0===i.length?b(!0):f(i[0],function(c){var d=!1;e.valAttr("dimension")&&(d=a.formUtils.checkImageDimension(c,e.valAttr("dimension"),h)),!d&&e.valAttr("ratio")&&(d=a.form...

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


@needs_pydanticv2
def test_post_body_form_no_password(client: TestClient):
    response = client.post("/login/", data={"username": "Foo"})

     *
     * @param    input    input block
     * @param    offset    start of meaningful bytes in input
     * @param    len        count of bytes in input block to consider
     */
    public void engineUpdate (byte[] input, int offset, int len) {
        // make sure we don't exceed input's allocated size/length
        if (offset < 0 || len < 0 || (long)offset + len > input.length)

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

## Resumo

Você pode utilizar **modelos Pydantic** para declarar **parâmetros de consulta** no **FastAPI**. 😎

/// tip | Dica

  @SafeVarargs
  public static <T extends @Nullable Object> Iterable<T> concat(Iterable<? extends T>... inputs) {
    return FluentIterable.concat(inputs);
  }

  /**
   * Combines multiple iterables into a single iterable. The returned iterable has an iterator that
   * traverses the elements of each iterable in {@code inputs}. The input iterators are not polled
   * until necessary.
   *