/*
 * Copyright 2020 the original author or authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,

/*
 * Copyright 2012-2024 CodeLibs Project and the Others.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,

 * #asMap}, and {@link #toString}.
 *
 * <p>Instances of this class may be used by multiple threads concurrently. All operations are
 * atomic unless otherwise noted.
 *
 * <p>Instances of this class are serializable if the keys are serializable.
 *
 * <p><b>Note:</b> If your values are always positive and less than 2^31, you may wish to use a
 * {@link com.google.common.collect.Multiset} such as {@link

 * </ul>
 *
 * <p>See the Guava User Guide article on <a href=
 * "https://github.com/google/guava/wiki/NewCollectionTypesExplained#table">{@code Table}</a>.
 *
 * @author Jared Levy
 * @param <R> the type of the table row keys
 * @param <C> the type of the table column keys
 * @param <V> the type of the mapped values
 * @since 7.0
 */
@DoNotMock("Use ImmutableTable, HashBasedTable, or another implementation")

TensorFlow was originally developed by researchers and engineers working within
the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)
and [C++](https://www.tensorflow.org/api_docs/cc) APIs, as well as a
non-guaranteed backward compatible API for

 * Returns the <tt>NtlmPasswordAuthentication</tt> object used as
 * credentials with this file or pipe. This can be used to retrieve the
 * username for example:
 * <tt>
 * String username = f.getPrincipal().getName();
 * </tt>
 * The <tt>Principal</tt> object returned will never be <tt>null</tt>
 * however the username can be <tt>null</tt> indication anonymous
 * credentials were used (e.g. some IPC$ services).
 */

  val authParams: Map<String?, String>

  /** Returns the protection space. */
  @get:JvmName("realm")
  val realm: String?
    get() = authParams["realm"]

  /** The charset that should be used to encode the credentials. */
  @get:JvmName("charset")
  val charset: Charset
    get() {
      val charset = authParams["charset"]
      if (charset != null) {
        try {
          return Charset.forName(charset)

import com.google.common.annotations.GwtCompatible;
import java.io.Serializable;
import java.util.Iterator;
import javax.annotation.CheckForNull;
import org.checkerframework.checker.nullness.qual.Nullable;

/** An ordering that uses the reverse of a given order. */
@GwtCompatible(serializable = true)
@ElementTypesAreNonnullByDefault
final class ReverseOrdering<T extends @Nullable Object> extends Ordering<T>
    implements Serializable {

/**
 * Implementation of {@link ImmutableMap} with exactly one entry.
 *
 * @author Jesse Wilson
 * @author Kevin Bourrillion
 */
@GwtCompatible(serializable = true, emulated = true)
@SuppressWarnings("serial") // uses writeReplace(), not default serialization
@ElementTypesAreNonnullByDefault
final class SingletonImmutableBiMap<K, V> extends ImmutableBiMap<K, V> {

  final transient K singleKey;
  final transient V singleValue;

   * will return {@code Double.MAX_VALUE}, not {@code Double.POSITIVE_INFINITY}.
   *
   * <p>For the case of {@link RoundingMode#HALF_EVEN}, this implementation uses the IEEE 754
   * default rounding mode: if the two nearest representable values are equally near, the one with
   * the least significant bit zero is chosen. (In such cases, both of the nearest representable