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
in taking those formats, modifying them, and/or converting them to intermediate

        // Arrange: choose a small set of known DOS codes
        List<Integer> inputs = Arrays.asList(0x00000000, 0x00050001, 0x007b0001, 0x0BADF00D);
        @SuppressWarnings("unchecked")
        BiConsumer<Integer, Integer> consumer = mock(BiConsumer.class);

        // Act: for each input, if a mapping exists, notify the consumer
        for (int dos : inputs) {
            int nt = findNtStatusOrMinusOne(dos);
            if (nt != -1) {

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

## Zusammenfassung { #summary }

Sie können **Pydantic-Modelle** verwenden, um **Query-Parameter** in **FastAPI** zu deklarieren. 😎

/// tip | Tipp

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

## Summary { #summary }

You can use **Pydantic models** to declare **query parameters** in **FastAPI**. 😎

/// tip

        )
        for field in list(fields) + list(unique_flat_model_fields)
    ]
    field_mapping, definitions = schema_generator.generate_definitions(inputs=inputs)
    for item_def in cast(dict[str, dict[str, Any]], definitions).values():
        if "description" in item_def:
            item_description = cast(str, item_def["description"]).split("\f")[0]

```json
{
    "detail": [
        {
            "type": "extra_forbidden",
            "loc": ["body", "extra"],
            "msg": "Extra inputs are not permitted",
            "input": "Mr. Poopybutthole"
        }
    ]
}
```

## Resumo { #summary }

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

## Підсумок

Ви можете використовувати **Pydantic-моделі** для оголошення **query параметрів** у **FastAPI**. 😎

/// tip | Підказка

        {
            "detail": [
                {
                    "type": "extra_forbidden",
                    "loc": ["cookie", "extra"],
                    "msg": "Extra inputs are not permitted",
                    "input": "track-me-here-too",
                }
            ]
        }
    )


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

```json
{
    "detail": [
        {
            "type": "extra_forbidden",
            "loc": ["body", "extra"],
            "msg": "Extra inputs are not permitted",
            "input": "Mr. Poopybutthole"
        }
    ]
}
```

## Summary { #summary }

他们将收到一条错误响应，表明字段 `extra` 是不被允许的：

```json
{
    "detail": [
        {
            "type": "extra_forbidden",
            "loc": ["body", "extra"],
            "msg": "Extra inputs are not permitted",
            "input": "Mr. Poopybutthole"
        }
    ]
}
```

## 总结