/**
     * Processes and saves an image from the input stream to the output file as a thumbnail.
     *
     * <p>This method reads image data, validates dimensions, applies subsampling and scaling
     * transformations based on configuration settings, and writes the processed thumbnail
     * to the specified output file.</p>
     *
     * @param input the image input stream containing the source image data

from pydantic import BaseModel


def forwardref_method(input: "ForwardRefModel") -> "ForwardRefModel":
    return ForwardRefModel(x=input.x + 1)


class ForwardRefModel(BaseModel):

                "loc": ["query", "token"],
                "msg": "Field required",
                "input": None,
            },
            {
                "type": "missing",
                "loc": ["header", "x-token"],
                "msg": "Field required",
                "input": None,
            },
        ]
    }


def test_put_invalid_header(client: TestClient):

    public LhaExtractor() {
        super();
    }

    /**
     * Extracts text content from an LHA archive input stream.
     *
     * @param in the input stream containing the LHA archive
     * @param params extraction parameters
     * @return the extracted text data
     * @throws CrawlerSystemException if the input stream is null
     * @throws ExtractException if an error occurs during extraction

	}
}

// NewLexer returns a lexer for the named file and the given link context.
func NewLexer(name string) TokenReader {
	input := NewInput(name)
	fd, err := os.Open(name)
	if err != nil {
		log.Fatalf("%s\n", err)
	}
	input.Push(NewTokenizer(name, fd, fd))
	return input
}

// The other files in this directory each contain an implementation of TokenReader.

    assert response.json() == {
        "detail": [
            {
                "type": "missing",
                "loc": IsOneOf(["body"], ["body", "p"]),
                "msg": "Field required",
                "input": IsOneOf(None, {}),
            }
        ]
    }


@pytest.mark.parametrize(
    "path",
    ["/required-str", "/model-required-str"],
)
def test_required_str(path: str):
    client = TestClient(app)

    response = client.get("/items/item1")
    assert response.status_code == 422, response.text
    assert response.json() == {
        "detail": [
            {
                "input": "item1",
                "loc": ["path", "item_id"],
                "msg": "Input should be a valid integer, unable to parse string as an integer",
                "type": "int_parsing",
            }
        ]
    }


def test_openapi_schema():

 *
 * Each test is a line of the file `toascii.json`.
 */
@Serializable
class WebPlatformToAsciiData {
  var input: String? = null
  var output: String? = null
  var comment: String? = null

  override fun toString() = "input=$input output=$output"

  companion object {
    fun load(): List<WebPlatformToAsciiData> {

     */
    @CustomSize(maxKey = "form.admin.max.input.size")
    public String includedPaths;

    /**
     * The paths to exclude for this label type.
     */
    @CustomSize(maxKey = "form.admin.max.input.size")
    public String excludedPaths;

    /**
     * The permissions required to view this label type.
     */
    @CustomSize(maxKey = "form.admin.max.input.size")
    public String permissions;

    /**

    }
  }

  static void checkInRangeForRoundingInputs(boolean condition, double input, RoundingMode mode) {
    if (!condition) {
      throw new ArithmeticException(
          "rounded value is out of range for input " + input + " and rounding mode " + mode);
    }
  }

  static void checkNoOverflow(boolean condition, String methodName, int a, int b) {
    if (!condition) {