}

  private static void testSortDescending(byte[] input, byte[] expectedOutput) {
    input = Arrays.copyOf(input, input.length);
    SignedBytes.sortDescending(input);
    assertThat(input).isEqualTo(expectedOutput);
  }

  private static void testSortDescending(
      byte[] input, int fromIndex, int toIndex, byte[] expectedOutput) {
    input = Arrays.copyOf(input, input.length);

# Separate OpenAPI Schemas for Input and Output or Not

When using **Pydantic v2**, the generated OpenAPI is a bit more exact and **correct** than before. 😎

In fact, in some cases, it will even have **two JSON Schemas** in OpenAPI for the same Pydantic model, for input and output, depending on if they have **default values**.

Let's see how that works and how to change it if you need to do that.

## Pydantic Models for Input and Output

    false

-   type: input id: Mobile attributes: label: Mobile device description:
    placeholder: e.g., Linux Ubuntu 16.04 validations: required: false

-   type: input id: Python attributes: label: Python version description:
    placeholder: e.g., 3.9 validations: required: false

-   type: input id: Bazel attributes: label: Bazel version description: if

    "input": "aa--",
    "output": "aa--"
  },
  {
    "input": "a†--",
    "output": "xn--a---kp0a"
  },
  {
    "input": "ab--c",
    "output": "ab--c"
  },
  {
    "comment": "Label with leading hyphen",
    "input": "-x",
    "output": "-x"
  },
  {
    "input": "-†",
    "output": "xn----xhn"
  },
  {
    "input": "-x.xn--zca",
    "output": "-x.xn--zca"

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

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

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

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

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

  - type: input
    id: Mobile
    attributes:
      label: Mobile device
      placeholder: e.g., Linux Ubuntu 16.04
  - type: input
    id: Python
    attributes:
      label: Python version
      placeholder: e.g., 3.9
  - type: input
    id: Bazel
    attributes:
      label: Bazel version
      description: If compiling from source
  - type: input
    id: Compiler
    attributes:

    }

    @get:Input
    abstract val version: Property<String>

    @get:Input
    abstract val baseVersion: Property<String>

    @get:Input
    @get:Optional
    abstract val commitId: Property<String>

    @get:Input
    abstract val snapshot: Property<Boolean>

    @get:Input
    abstract val promotionBuild: Property<Boolean>

    @get:Input
    @get:Optional

  private static final Predicate<@Nullable String> NOT_LENGTH_3 =
      input -> input == null || input.length() != 3;
  private static final Predicate<@Nullable Integer> EVEN = input -> input == null || input % 2 == 0;
  static final Predicate<Entry<String, Integer>> CORRECT_LENGTH =
      input -> input.getKey().length() == input.getValue();

  abstract Map<String, Integer> createUnfiltered();

  private static final Predicate<@Nullable String> NOT_LENGTH_3 =
      input -> input == null || input.length() != 3;
  private static final Predicate<@Nullable Integer> EVEN = input -> input == null || input % 2 == 0;
  static final Predicate<Entry<String, Integer>> CORRECT_LENGTH =
      input -> input.getKey().length() == input.getValue();

  abstract Map<String, Integer> createUnfiltered();

// Creates parameters (placeholders) in the tracing `ctx` using the shape and
// dtype of `inputs`.
Status CreateParamsForInputs(AbstractContext* ctx,
                             absl::Span<AbstractTensorHandle* const> inputs,
                             std::vector<AbstractTensorHandle*>* params);

// A callable that takes tensor inputs and returns zero or more tensor outputs.
using Model = std::function<Status(AbstractContext*,