.put(RowSortedTable.class, Tables.unmodifiableRowSortedTable(TreeBasedTable.create()))
          .put(ClassToInstanceMap.class, ImmutableClassToInstanceMap.builder().build())
          .put(ImmutableClassToInstanceMap.class, ImmutableClassToInstanceMap.builder().build())
          .put(Comparable.class, ByToString.INSTANCE)
          .put(Comparator.class, AlwaysEqual.INSTANCE)
          .put(Ordering.class, AlwaysEqual.INSTANCE)

class AutobahnTester {
  val client = OkHttpClient()

  private fun newWebSocket(
    path: String,
    listener: WebSocketListener,
  ): WebSocket {
    val request =
      Request.Builder()
        .url(HOST + path)
        .build()
    return client.newWebSocket(request, listener)
  }

  fun run() {
    try {
      val count = getTestCount()
      println("Test count: $count")
      for (number in 1..count) {

    }

    private static TransferEvent event(
            RepositorySystemSession session, TransferResource resource, TransferEvent.EventType type) {
        return new TransferEvent.Builder(session, resource).setType(type).build();
    }

 * by a G, selecting appropriate tests by matching them against specified features.
 *
 * @param <B> The concrete type of this builder (the 'self-type'). All the Builder methods of this
 *     class (such as {@link #named}) return this type, so that Builder methods of more derived
 *     classes can be chained onto them without casting.

}

void TF_DeleteAttrBuilder(TF_AttrBuilder* builder) { delete builder; }

void TF_AttrBuilderSetType(TF_AttrBuilder* builder, const char* attr_name,
                           TF_DataType value) {
  auto iter = builder->attr_names.insert(attr_name).first;
  builder->Set(*iter, static_cast<tensorflow::DataType>(value));
}

void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder, const char* attr_name,

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  // Build an abstract operation.
  auto* op = TF_NewAbstractOp(ctx);
  TF_AbstractOpSetOpType(op, "Add", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  // Build inputs and outputs.
  TF_AbstractTensor* inputs[2] = {at, at};
  TF_OutputList* o = TF_NewOutputList();

  return millis.toInt()
}

internal fun List<Header>.toHeaders(): Headers {
  val builder = Headers.Builder()
  for ((name, value) in this) {
    builder.addLenient(name.utf8(), value.utf8())
  }
  return builder.build()
}

internal fun Headers.toHeaderList(): List<Header> =
  (0 until size).map {
    Header(name(it), value(it))
  }

  fun setUp() {
    platform.assumeLoom()
    assertThat(System.getProperty("jdk.tracePinnedThreads")).isNotEmpty()

    client =
      OkHttpClient.Builder()
        .trustMockServer()
        .dispatcher(Dispatcher(newVirtualThreadPerTaskExecutor()))
        .build()

    executor = newVirtualThreadPerTaskExecutor()

    // Capture non-deterministic but probable sysout warnings of pinned threads

            Exception exception) {
        RepositoryEvent.Builder event = new RepositoryEvent.Builder(session, EventType.METADATA_INVALID);
        event.setTrace(trace);
        event.setMetadata(metadata);
        event.setException(exception);
        event.setRepository(repository);

        repositoryEventDispatcher.dispatch(event.build());
    }

    Random random = new Random(2211275185798966364L);
    ImmutableList.Builder<Double> largeDatasetBuilder = ImmutableList.builder();
    for (int i = 0; i < PSEUDORANDOM_DATASET_SIZE; i++) {
      largeDatasetBuilder.add(random.nextGaussian());
    }
    return largeDatasetBuilder.build();
  }

  private static double expectedLargeDatasetPercentile(int index) {