const std::vector<TF_Tensor*>& input_tensors,
      const absl::optional<std::vector<int64_t>>& expected_shape) {
    // Create input_shapes.
    TF_ShapeAndTypeList* input_shapes =
        TF_NewShapeAndTypeList(input_shapes_vec.size());
    for (size_t i = 0; i < input_shapes_vec.size(); ++i) {
      const auto& input_shape = input_shapes_vec[i];

    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:

  private static void testReverse(float[] input, float[] expectedOutput) {
    input = Arrays.copyOf(input, input.length);
    Floats.reverse(input);
    assertThat(input).isEqualTo(expectedOutput);
  }

  private static void testReverse(
      float[] input, int fromIndex, int toIndex, float[] expectedOutput) {
    input = Arrays.copyOf(input, input.length);
    Floats.reverse(input, fromIndex, toIndex);

  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();

    }

    @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

  // Build an abstract input tensor.
  TFE_Context* eager_ctx =
      TF_ExecutionContextGetTFEContext(eager_execution_ctx, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  TFE_TensorHandle* input_eager = TestScalarTensorHandle(eager_ctx, 2.0f);
  TF_AbstractTensor* input_t =
      TF_CreateAbstractTensorFromEagerTensor(input_eager, status.get());