private static final String ITEM_ENDPOINT_SUFFIX = "setting";
    private static final String DICT_TYPE = "mapping";

    private static final String KEY_PROPERTY = "inputs";

    @Override
    protected String getNamePrefix() {
        return NAME_PREFIX;
    }

    @Override
    protected String getApiPath() {
        return API_PATH;
    }

    @Override

    assert response.status_code == 422
    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):

  @SafeVarargs
  public static <T extends @Nullable Object> Iterator<T> concat(Iterator<? extends T>... inputs) {
    return concatNoDefensiveCopy(Arrays.copyOf(inputs, inputs.length));
  }

  /**
   * Combines multiple iterators into a single iterator. The returned iterator iterates across the
   * elements of each iterator in {@code inputs}. The input iterators are not polled until
   * necessary.
   *

   */
  @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.
   *

      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);

  TF_Operation* neg = Neg(feed, func_graph.get(), s.get());

  TF_Output inputs[] = {{feed, 0}};
  TF_Output outputs[] = {{neg, 0}};
  *func = TF_GraphToFunction(func_graph.get(), name, append_hash, -1,
                             /*opers=*/nullptr, 1, inputs, 1, outputs,
                             /*output_names=*/nullptr,
                             /*opts=*/nullptr, description, s.get());

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

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

## Summary

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

/// tip

        javadocs = objects.newInstance(Javadocs.class);
        kotlinDslReference = objects.newInstance(KotlinDslReference.class);
    }

    /**
     * The root directory of all documentation inputs
     */
    public abstract DirectoryProperty getSourceRoot();

    /**
     * Collection of CSS files to include in generated documentation.
     */
    public abstract ConfigurableFileCollection getCssFiles();

    assert response.status_code == 422
    assert response.json() == {
        "detail": [
            {
                "type": "extra_forbidden",
                "loc": ["body", "extra"],
                "msg": "Extra inputs are not permitted",
                "input": "extra",
            }
        ]
    }


@needs_pydanticv2
@needs_py39
def test_post_body_form_no_password(client: TestClient):