// license that can be found in the LICENSE file.

// Package bufio implements buffered I/O. It wraps an io.Reader or io.Writer
// object, creating another object (Reader or Writer) that also implements
// the interface but provides buffering and some help for textual I/O.
package bufio

import (
	"bytes"
	"errors"
	"io"
	"strings"
	"unicode/utf8"
)

const (
	defaultBufSize = 4096
)

var (

  correctly with an external cloud provider. ([#124516](https://github.com/kubernetes/kubernetes/pull/124516), [@danwinship](https://github.com/danwinship))
- Fixed an issue that prevents the linking of trace spans for requests that are proxied through kube-aggregator. ([#124189](https://github.com/kubernetes/kubernetes/pull/124189), [@toddtreece](https://github.com/toddtreece))

   */
  private static String getLockName(Enum<?> rank) {
    return rank.getDeclaringClass().getSimpleName() + "." + rank.name();
  }

  /**
   * A {@code CycleDetectingLockFactory.WithExplicitOrdering} provides the additional enforcement of
   * an application-specified ordering of lock acquisitions. The application defines the allowed
   * ordering with an {@code Enum} whose values each correspond to a lock type. The order in which

- The userspace proxy now respects the IPTables proxy's minSyncInterval parameter. ([#71735](https://github.com/kubernetes/kubernetes/pull/71735), [@dcbw](https://github.com/dcbw))

- iptables proxier: now routes local traffic to LB IPs to service chain ([#77523](https://github.com/kubernetes/kubernetes/pull/77523), [@andrewsykim](https://github.com/andrewsykim))

have both been migrated.

### gRPC Probes Graduate to Beta

With Kubernetes 1.24, the [gRPC probes functionality](https://github.com/kubernetes/enhancements/issues/2727)
has entered beta and is available by default. You can now [configure startup, liveness, and readiness probes](https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes/#configure-probes) for your gRPC app

"mesma", "mesmas", "mesmo", "mesmos", "na", "nas", "nao", "nas", "nem", "nesse", "neste", "nos", "o", "os", "ou", "outra", "outras", "outro", "outros", "pelas", "pelas", "pelo", "pelos", "perante", "pois", "por", "porque", "portanto", "proprio", "propios", "quais", "qual", "qualquer", "quando", "quanto", "que", "quem", "quer", "se", "seja", "sem", "sendo", "seu", "seus", "sob", "sobre", "sua", "suas", "tal", "tambem", "teu", "teus", "toda", "todas", "todo", "todos", "tua", "tuas", "tudo", "um", "uma",...

"mesma", "mesmas", "mesmo", "mesmos", "na", "nas", "nao", "nas", "nem", "nesse", "neste", "nos", "o", "os", "ou", "outra", "outras", "outro", "outros", "pelas", "pelas", "pelo", "pelos", "perante", "pois", "por", "porque", "portanto", "proprio", "propios", "quais", "qual", "qualquer", "quando", "quanto", "que", "quem", "quer", "se", "seja", "sem", "sendo", "seu", "seus", "sob", "sobre", "sua", "suas", "tal", "tambem", "teu", "teus", "toda", "todas", "todo", "todos", "tua", "tuas", "tudo", "um", "uma",...

  }

  public void testPowerSetIteration_manual() {
    ImmutableSet<Integer> elements = ImmutableSet.of(1, 2, 3);
    Set<Set<Integer>> powerSet = powerSet(elements);
    // The API doesn't promise this iteration order, but it's convenient here.
    Iterator<Set<Integer>> i = powerSet.iterator();
    assertEquals(ImmutableSet.of(), i.next());
    assertEquals(ImmutableSet.of(1), i.next());

  }

  /**
   * Returns a builder that creates immutable sorted sets whose elements are ordered by their
   * natural ordering. The sorted sets use {@link Ordering#natural()} as the comparator. This method
   * provides more type-safety than {@link #builder}, as it can be called only for classes that
   * implement {@link Comparable}.
   */
  public static <E extends Comparable<?>> Builder<E> naturalOrder() {

    process.
    *   TensorFlow 2.15.0 Python package was requesting `tensorrt`-related
        packages that cannot be found unless the user installs them beforehand
        or provides additional installation flags.
    *   This dependency affected anyone installing TensorFlow 2.15 alongside
        NVIDIA CUDA dependencies via `pip install tensorflow[and-cuda]`.