import static org.gradle.util.internal.CollectionUtils.sort;

/**
 * Provides access to {@link GradleDistribution}s for versions of Gradle that have been released.
 *
 * Only versions that are suitable for testing against are made available.
 */
public class ReleasedVersionDistributions {

    private final IntegrationTestBuildContext buildContext;

    private final Factory<Properties> versionsFactory;

// bound to `func`, which is bound to the TF_SavedModel it was loaded from.
TF_CAPI_EXPORT extern TF_FunctionMetadata* TF_ConcreteFunctionGetMetadata(
    TF_ConcreteFunction* func);

// Returns a TFE_Op suitable for executing this function. Caller must provide
// all function inputs in `inputs`, and must not add any additional inputs on
// the returned op. (i.e. don't call TFE_OpAddInput or TFE_OpAddInputList).

 * the whole resource itself.
 *
 * @param <IN> a service specific type, representing a query of the service, which can be replayed later
 * @param <OUT> the fingerprint result of a service query, suitable for checking up-to-date status
 * @param <SERVICE> the type of the service
 */
public interface ImplicitInputsProvidingService<IN, OUT, SERVICE> {

    SERVICE withImplicitInputRecorder(ImplicitInputRecorder registrar);

type xchacha20poly1305 struct {
	key [KeySize]byte
}

// NewX returns a XChaCha20-Poly1305 AEAD that uses the given 256-bit key.
//
// XChaCha20-Poly1305 is a ChaCha20-Poly1305 variant that takes a longer nonce,
// suitable to be generated randomly without risk of collisions. It should be
// preferred when nonce uniqueness cannot be trivially ensured, or whenever
// nonces are randomly generated.
func NewX(key []byte) (cipher.AEAD, error) {

import org.gradle.internal.typeconversion.NotationParser;

import javax.annotation.Nullable;

/**
 * Adapts a mutable module component resolve metadata instance into a form that is suitable
 * for mutation through the Gradle DSL: we don't want to expose all the resolve component
 * metadata methods, only those which make sense, and that we can reason about safely. The adapter

#include "tensorflow/core/lib/core/status.h"

namespace tensorflow {
namespace tf2xla {
namespace v2 {

// Run all the passes involved in transforming the graph before execution so
// that it is suitable for targeting devices when called with the TF 2 Function
// API. Users that need clustering with the Session API should use the v1 Bridge
// API. These transformations take as input a Tensorflow Graph as an MLIR Module

	ret := &unstructured.Unstructured{}
	ret.SetGroupVersionKind(kind)
	return ret, nil
}

type unstructuredDefaulter struct {
}

// NewUnstructuredDefaulter returns defaulter suitable for unstructured types that doesn't default anything
func NewUnstructuredDefaulter() runtime.ObjectDefaulter {
	return unstructuredDefaulter{}
}

func (d unstructuredDefaulter) Default(in runtime.Object) {

// a certain combination:
// - no object exists with suitable topology and storage class name
// - such an object exists, but the capacity is unset
// - such an object exists, but the capacity is zero
//
// The producer of these objects can decide which approach is more suitable.
//
// They are consumed by the kube-scheduler when a CSI driver opts into

	// See https://lemire.me/blog/2016/06/27/a-fast-alternative-to-the-modulo-reduction/
	return uint32((uint64(uint32(rand())) * uint64(n)) >> 32)
}

// cheaprand is a non-cryptographic-quality 32-bit random generator
// suitable for calling at very high frequency (such as during scheduling decisions)
// and at sensitive moments in the runtime (such as during stack unwinding).
// it is "cheap" in the sense of both expense and quality.
//

func NewRequest(method, target string, body io.Reader) *http.Request {
	return NewRequestWithContext(context.Background(), method, target, body)
}

// NewRequestWithContext returns a new incoming server Request, suitable
// for passing to an [http.Handler] for testing.
//
// The target is the RFC 7230 "request-target": it may be either a
// path or an absolute URL. If target is an absolute URL, the host name