}

// NamedRuleWithOperations is a tuple of Operations and Resources with ResourceNames.
// +structType=atomic
message NamedRuleWithOperations {
  // ResourceNames is an optional white list of names that the rule applies to.  An empty set means that everything is allowed.
  // +listType=atomic
  // +optional
  repeated string resourceNames = 1;

  // RuleWithOperations is a tuple of Operations and Resources.

// functionality of `gradient_checker` by comparing the result with expected
// manual user-provided gradients.
class GradientCheckerTest
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());

    {

		w.writeType(buf, typ.Elem())

	case *types.Struct:
		buf.WriteString("struct")

	case *types.Pointer:
		buf.WriteByte('*')
		w.writeType(buf, typ.Elem())

	case *types.Tuple:
		panic("should never see a tuple type")

	case *types.Signature:
		buf.WriteString("func")
		w.writeSignature(buf, typ)

	case *types.Interface:
		buf.WriteString("interface{")

  return ops::BiasAdd(ctx, inputs[0], inputs[1], &outputs[0], "NHWC",
                      "BiasAdd");
}

class CppGradients
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());

   *
   * <pre>{@code
   * for (B b0 : lists.get(0)) {
   *   for (B b1 : lists.get(1)) {
   *     ...
   *     ImmutableList<B> tuple = ImmutableList.of(b0, b1, ...);
   *     // operate on tuple
   *   }
   * }
   * }</pre>
   *
   * <p>Note that if any input list is empty, the Cartesian product will also be empty. If no lists

```Python hl_lines="1"
{!../../../docs_src/body_nested_models/tutorial002.py!}
```

### Declare a `List` com um parâmetro de tipo

Para declarar tipos que têm parâmetros de tipo(tipos internos), como `list`, `dict`, `tuple`:

* Importe os do modulo `typing`
* Passe o(s) tipo(s) interno(s) como "parâmetros de tipo" usando colchetes: `[` e `]`

```Python
from typing import List

my_list: List[str]
```

### typing의 `List` 임포트

먼저, 파이썬 표준 `typing` 모듈에서 `List`를 임포트합니다:

```Python hl_lines="1"
{!../../../docs_src/body_nested_models/tutorial002.py!}
```

### 타입 매개변수로 `List` 선언

`list`, `dict`, `tuple`과 같은 타입 매개변수(내부 타입)를 갖는 타입을 선언하려면:

* `typing` 모듈에서 임포트
* 대괄호를 사용하여 "타입 매개변수"로 내부 타입 전달: `[` 및 `]`

```Python
from typing import List

my_list: List[str]
```

이 모든 것은 타입 선언을 위한 표준 파이썬 문법입니다.

  // are executed asynchronously this must outlive the queued op, so it can't be
  // function-local to Execute.
  mutable std::unique_ptr<CancellationManager> default_cancellation_manager_;
};

// Contains a tuple of tensors, one on each of the `underlying_devices_` of the
// ParallelDevice.
class ParallelTensor {
 public:
  // Construct a ParallelTensor from TensorHandles placed on the component

```Python hl_lines="1"
{!> ../../../docs_src/body_nested_models/tutorial002.py!}
```

### Eine `list`e mit einem Typ-Parameter deklarieren

Um Typen wie `list`, `dict`, `tuple` mit inneren Typ-Parametern (inneren Typen) zu deklarieren:

* Wenn Sie eine Python-Version kleiner als 3.9 verwenden, importieren Sie das Äquivalent zum entsprechenden Typ vom `typing`-Modul

```

!!! tip
    `{"name", "description"}` 语法创建一个具有这两个值的 `set`。

    等同于 `set(["name", "description"])`。

#### 使用 `list` 而不是 `set`

如果你忘记使用 `set` 而是使用 `list` 或 `tuple`，FastAPI 仍会将其转换为 `set` 并且正常工作：

```Python hl_lines="31  37"
{!../../../docs_src/response_model/tutorial006.py!}
```

## 总结

使用*路径操作装饰器*的 `response_model` 参数来定义响应模型，特别是确保私有数据被过滤掉。