* other using {@code second = new PairedStatsAccumulator().addAll(first).snapshot()}, if both
   * were obtained by calling {@code snapshot()} on the same {@link PairedStatsAccumulator} without
   * adding any values in between the two calls, or if one is obtained from the other after
   * round-tripping through java serialization. However, floating point rounding errors mean that it

        options.addOption(Option.builder()
                .longOpt(YJP)
                .desc("Launch the JVM with Yourkit profiler (script option).")
                .build());

        // Adding this back to make Maven fail if used
        options.addOption(Option.builder("llr")
                .longOpt("legacy-local-repository")
                .desc("<deprecated> Use Maven 2 Legacy Local Repository behaviour.")

                               TF_Status* status, TF_Output* dy) {
#if defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
  status->status = tensorflow::errors::Unimplemented(
      "Adding gradients is not supported on mobile. File a bug at "
      "https://github.com/tensorflow/tensorflow/issues if this feature is "
      "important to you");
#else

        assertEquals("json", Constants.SEARCH_LOG_ACCESS_TYPE_JSON);
        assertEquals("gsa", Constants.SEARCH_LOG_ACCESS_TYPE_GSA);
        assertEquals("web", Constants.SEARCH_LOG_ACCESS_TYPE_WEB);
        assertEquals("admin", Constants.SEARCH_LOG_ACCESS_TYPE_ADMIN);
        assertEquals("other", Constants.SEARCH_LOG_ACCESS_TYPE_OTHER);
    }

    @Test
    public void test_accessType_llmNamesAreDifferentFromBuiltinTypes() {

 * }
 *
 * <p>{@link ValueGraphBuilder#build()} returns an instance of {@link MutableValueGraph}, which is a
 * subtype of {@code ValueGraph} that provides methods for adding and removing nodes and edges. If
 * you do not need to mutate a graph (e.g. if you write a method than runs a read-only algorithm on
 * the graph), you should use the non-mutating {@link ValueGraph} interface, or an {@link

/// tip | İpucu

Nokta (`.`) ile başlayan dosyalar, Linux ve macOS gibi Unix-benzeri sistemlerde gizli dosyadır.

Ancak dotenv dosyasının mutlaka bu dosya adına sahip olması gerekmez.

///

*   `tf.contrib`:

    *   `tf.contrib` has been deprecated, and functionality has been either
        migrated to the core TensorFlow API, to an ecosystem project such as
        [tensorflow/addons](https://www.github.com/tensorflow/addons) or
        [tensorflow/io](https://www.github.com/tensorflow/io), or removed
        entirely.
    *   Remove `tf.contrib.timeseries` dependency on TF distributions.

  const char remote_device_name[] =
      "/job:localhost/replica:0/task:1/device:CPU:0";
  CheckRemoteMatMulExecutesOK(ctx, remote_device_name, local_device_name);

  // Adding a non-existent remote worker to cluster def. This should cause the
  // UpdateServerDef call to fail.
  tensorflow::ClusterDef* cluster_def = server_def.mutable_cluster();

 * replace an existing pair with the same key and value, if such a pair is present. With collections
 * like {@link List} that allow duplicates, the collection will keep the existing key-value pairs
 * while adding a new pair.
 *
 * <p>This class is not threadsafe when any concurrent operations update the multimap, even if the
 * underlying map and {@link #createCollection()} method return threadsafe classes. Concurrent read

    return new ArrayList<>(computeArrayListCapacity(estimatedSize));
  }

  // LinkedList

  /**
   * Creates a <i>mutable</i>, empty {@code LinkedList} instance.
   *
   * <p><b>Note:</b> if you won't be adding any elements to the list, use {@link ImmutableList#of()}
   * instead.
   *
   * <p><b>Performance note:</b> {@link ArrayList} and {@link java.util.ArrayDeque} consistently