# inference_func.

# CHECK: f = @inference_func[[post_fix:[^,]*]]
# CHECK-SAME: shared_name = "batch"
# CH#CK: sym_name = "predict0"

# CHECK: f = @inference_func[[post_fix]],
# CHECK-SAME: shared_name = "batch"
# CH#CK: sym_name = "predict1"

meta_graphs: {
  meta_info_def: {
    tags: ["serve", "tpu"]
  }
  graph_def: {
    node: {
      name: "input0"
      op: "Placeholder"

/**
 * Legacy version of {@link java.util.function.Predicate java.util.function.Predicate}. Determines a
 * true or false value for a given input.
 *
 * <p>As this interface extends {@code java.util.function.Predicate}, an instance of this type may
 * be used as a {@code Predicate} directly. To use a {@code java.util.function.Predicate} where a
 * {@code com.google.common.base.Predicate} is expected, use the method reference {@code

   *       Objects.equal}{@code (a, b)} implies that {@code predicate.apply(a) ==
   *       predicate.apply(b))}.
   * </ul>
   *
   * @throws NullPointerException if {@code input} is null and this predicate does not accept null
   *     arguments
   */
  boolean apply(@ParametricNullness T input);

  /**
   * Indicates whether another object is equal to this predicate.
   *

		case *PredicateFailureError:
			reason = re.PredicateName
			message = re.Error()
			klog.V(2).InfoS("Predicate failed on Pod", "pod", klog.KObj(admitPod), "err", message)
		case *InsufficientResourceError:
			reason = fmt.Sprintf("OutOf%s", re.ResourceName)
			message = re.Error()
			klog.V(2).InfoS("Predicate failed on Pod", "pod", klog.KObj(admitPod), "err", message)
		default:
			reason = "UnexpectedPredicateFailureType"

type Predicates struct {
	SelectEnv    SelectEnvFn
	SelectMetric SelectMetricFn
}

// SelectEnvFn is a predicate function for selecting environment variables when generating collateral documents.
type SelectEnvFn func(env.Var) bool

// SelectMetricFn is a predicate function for selecting metrics when generating collateral documents.
type SelectMetricFn func(monitoring.MetricDefinition) bool

////////////////////////////////////////////////////////////////////////////////
/// Predict API constants.

/// Predict inputs.
static constexpr char kPredictInputs[] = "inputs";

/// Predict method name used in a SignatureDef.
static constexpr char kPredictMethodName[] = "tensorflow/serving/predict";

/// Predict outputs.
static constexpr char kPredictOutputs[] = "outputs";

        assert response.json() == {
            "openapi": "3.1.0",
            "info": {"title": "FastAPI", "version": "0.1.0"},
            "paths": {
                "/predict": {
                    "get": {
                        "summary": "Predict",
                        "operationId": "predict_predict_get",
                        "parameters": [
                            {
                                "required": True,

  }

  private static void assertEvalsToTrue(Predicate<? super @Nullable Integer> predicate) {
    assertTrue(predicate.apply(0));
    assertTrue(predicate.apply(1));
    assertTrue(predicate.apply(null));
  }

  private static void assertEvalsToFalse(Predicate<? super @Nullable Integer> predicate) {
    assertFalse(predicate.apply(0));
    assertFalse(predicate.apply(1));
    assertFalse(predicate.apply(null));
  }

    <T extends @Nullable Object> Predicate<T> withNarrowedType() {
      return (Predicate<T>) this;
    }
  }

  /** @see Predicates#not(Predicate) */
  private static class NotPredicate<T extends @Nullable Object>
      implements Predicate<T>, Serializable {
    final Predicate<T> predicate;

    NotPredicate(Predicate<T> predicate) {
      this.predicate = checkNotNull(predicate);
    }

  }

  Predicate* MakeAndOrImpl(absl::Span<Predicate* const> operands, bool is_and);
  Predicate* MakeInternedAndOr(std::vector<Predicate*> simplified_ops,
                               Predicate::Kind pred_kind);

  // Predicate instances are interned, meaning that there is only a single
  // instance of a Predicate object with a given content.  This makes checking