}

  /**
   * Returns a new array of the given length with the same type as a reference array.
   *
   * @param reference any array of the desired type
   * @param length the length of the new array
   */
  /*
   * The new array contains nulls, even if the old array did not. If we wanted to be accurate, we
   * would declare a return type of `@Nullable T[]`. However, we've decided not to think too hard

  }

  /**
   * Returns a new array of the given length with the same type as a reference array.
   *
   * @param reference any array of the desired type
   * @param length the length of the new array
   */
  /*
   * The new array contains nulls, even if the old array did not. If we wanted to be accurate, we
   * would declare a return type of `@Nullable T[]`. However, we've decided not to think too hard

limitations under the License.
==============================================================================*/
#include "tensorflow/c/eager/gradient_checker.h"

#include <memory>

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/c_api_unified_experimental.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/ops/math_ops.h"

///

## Use `Annotated` in the type for the `q` parameter

Remember I told you before that `Annotated` can be used to add metadata to your parameters in the [Python Types Intro](../python-types.md#type-hints-with-metadata-annotations){.internal-link target=_blank}?

Now it's the time to use it with FastAPI. 🚀

We had this type annotation:

//// tab | Python 3.10+

```Python

   *
   * <blockquote>
   *
   * "Some collection implementations have restrictions on the elements that they may contain. For
   * example, some implementations prohibit null elements, and some have restrictions on the types
   * of their elements."
   *
   * </blockquote>
   */
  RESTRICTS_ELEMENTS,

  /**
   * Indicates that a collection has a well-defined ordering of its elements. The ordering may

 */

package jcifs.smb1.netbios;

import java.io.IOException;
import java.io.InputStream;

public abstract class SessionServicePacket { 

    // session service packet types 
    static final int SESSION_MESSAGE = 0x00; 
    static final int SESSION_REQUEST = 0x81; 
    public static final int POSITIVE_SESSION_RESPONSE = 0x82; 
    public static final int NEGATIVE_SESSION_RESPONSE = 0x83; 

Jeśli potrzebujesz szybkiego przypomnienia jak używać deklaracji typów w Pythonie (nawet jeśli nie używasz FastAPI), sprawdź krótki samouczek: [Python Types](python-types.md){.internal-link target=_blank}.

Wystarczy, że napiszesz standardowe deklaracje typów Pythona:

```Python
from datetime import date

from pydantic import BaseModel

# Zadeklaruj parametr jako str

### Sadece modern Python

Tamamiyle standartlar **Python 3.8**'nın type hintlerine dayanıyor (Pydantic'in sayesinde). Yeni bir syntax öğrenmene gerek yok. Sadece modern Python.


Eğer Python type hintlerini bilmiyorsan veya bir hatırlatmaya ihtiyacın var ise(FastAPI kullanmasan bile) şu iki dakikalık küçük bilgilendirici içeriğe bir göz at: [Python Types](python-types.md){.internal-link target=_blank}.

vous verrez comme réponse :

```JSON
{"item_id":"foo"}
```

## Paramètres de chemin typés

Vous pouvez déclarer le type d'un paramètre de chemin dans la fonction, en utilisant les annotations de type Python :


```Python hl_lines="7"
{!../../docs_src/path_params/tutorial002.py!}
```

Ici, `item_id` est déclaré comme `int`.

/// check | "vérifier"

limitations under the License.
==============================================================================*/
#include "tensorflow/c/eager/gradient_checker.h"

#include <memory>

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/experimental/ops/math_ops.h"
#include "tensorflow/c/tf_tensor.h"

namespace tensorflow {
namespace gradients {