* (key) bits 'affects' a strictly smaller set of output bits. Funneling is bad because it can
   * result in more-than-ideal collisions for a non-uniformly distributed key space. In practice,
   * most key spaces are ANYTHING BUT uniformly distributed. A bit(i) in the input is said to
   * 'affect' a bit(j) in the output if two inputs, identical but for bit(i), will differ at output

        String[] values = null;
        if (input instanceof String[]) {
            values = (String[]) input;
        } else if (input instanceof List) {
            values = ((List<?>) input).stream().filter(Objects::nonNull).map(Object::toString).toArray(n -> new String[n]);
        } else if (input instanceof String) {
            return input.toString();
        }
        if (values != null) {

  }

  static void testSort(int[] input, int[] expected) {
    input = Arrays.copyOf(input, input.length);
    UnsignedInts.sort(input);
    assertThat(input).isEqualTo(expected);
  }

  static void testSort(int[] input, int from, int to, int[] expected) {
    input = Arrays.copyOf(input, input.length);
    UnsignedInts.sort(input, from, to);
    assertThat(input).isEqualTo(expected);
  }

  private static final class RoundToDoubleTester {
    private final BigDecimal input;
    private final Map<RoundingMode, Double> expectedValues = new EnumMap<>(RoundingMode.class);
    private boolean unnecessaryShouldThrow = false;

    RoundToDoubleTester(BigDecimal input) {
      this.input = input;
    }

    RoundToDoubleTester setExpectation(double expectedValue, RoundingMode... modes) {

   * (key) bits 'affects' a strictly smaller set of output bits. Funneling is bad because it can
   * result in more-than-ideal collisions for a non-uniformly distributed key space. In practice,
   * most key spaces are ANYTHING BUT uniformly distributed. A bit(i) in the input is said to
   * 'affect' a bit(j) in the output if two inputs, identical but for bit(i), will differ at output

    absl::Span<const int64_t> input_tensor_id,
    absl::Span<const tensorflow::DataType> input_dtypes,
    const std::function<BackwardFunction*()>& backward_function_getter,
    const std::function<void(BackwardFunction*)>& backward_function_deleter) {
  if (!ShouldRecord(input_tensor_id, input_dtypes)) {
    return;
  }
  std::vector<int64_t> ids;
  ids.reserve(input_tensor_id.size());

        {
            "detail": [
                {
                    "type": "missing",
                    "loc": ["query", "q"],
                    "msg": "Field required",
                    "input": None,
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {

    checkNotNull(keyFunction);
    checkNotNull(valuesFunction);
    return collectingAndThen(
        flatteningToMultimap(
            input -> checkNotNull(keyFunction.apply(input)),
            input -> valuesFunction.apply(input).peek(Preconditions::checkNotNull),
            MultimapBuilder.linkedHashKeys().arrayListValues()::<K, V>build),
        ImmutableListMultimap::copyOf);
  }

    @Input
    @Optional
    public abstract ListProperty<String> getMethodIncludes();

    @Input
    @Optional
    public abstract ListProperty<String> getMethodExcludes();

    @Input
    @Optional
    public abstract ListProperty<String> getFieldIncludes();

    @Input
    @Optional
    public abstract ListProperty<String> getFieldExcludes();

    @Input
    @Optional

  }

  static void testSort(byte[] input, byte[] expected) {
    input = Arrays.copyOf(input, input.length);
    UnsignedBytes.sort(input);
    assertThat(input).isEqualTo(expected);
  }

  static void testSort(byte[] input, int from, int to, byte[] expected) {
    input = Arrays.copyOf(input, input.length);
    UnsignedBytes.sort(input, from, to);
    assertThat(input).isEqualTo(expected);
  }