import java.util.Set;
import org.jspecify.annotations.Nullable;

/** Emulation of AggregateFutureState. */
abstract class AggregateFutureState<OutputT extends @Nullable Object>
    extends AbstractFuture.TrustedFuture<OutputT> {
  // Lazily initialized the first time we see an exception; not released until all the input futures

 *   <li>Decrements a counter atomically
 * </ul>
 */
@GwtCompatible
@ReflectionSupport(value = ReflectionSupport.Level.FULL)
abstract class AggregateFutureState<OutputT extends @Nullable Object>
    extends AbstractFuture.TrustedFuture<OutputT> {
  /*
   * The following fields are package-private, even though we intend never to use them outside this
   * file. For discussion, see AbstractFutureState.
   */

 * @param <OutputT> the type of the output (i.e. this) future
 */
@GwtCompatible
@SuppressWarnings(
    // Whenever both tests are cheap and functional, it's faster to use &, | instead of &&, ||
    "ShortCircuitBoolean")
abstract class AggregateFuture<InputT extends @Nullable Object, OutputT extends @Nullable Object>
    extends AggregateFutureState<OutputT> {

        assertTrue(output1.contains("|"));

        // Test with less than 16 bytes
        baos.reset();
        byte[] data2 = { 0x41, 0x42, 0x43, 0x44 }; // "ABCD"
        Hexdump.hexdump(ps, data2, 0, 4);
        String output2 = baos.toString();

        assertNotNull(output2);
        assertTrue(output2.contains("00000:"));
        assertTrue(output2.contains(" 41 42 43 44"));

    private String[] newOutputs;

    /**
     * Constructs a new synonym item.
     *
     * @param id      The unique identifier of the item.
     * @param inputs  The input words.
     * @param outputs The output synonyms.
     */
    public SynonymItem(final long id, final String[] inputs, final String[] outputs) {
        this.id = id;
        this.inputs = inputs;
        this.outputs = outputs;

   *
   *   A =[[0, 1],[1, 0]]
   *   B =[[1, 0],[0, 1]]
   *
   *   output1, output2, output3 = two_adds_and_mm(A, B)
   *
   * We expect outputs:
   *
   *   output1 = [[1, 1],[1, 1]]
   *   output2 = [[2, 0],[0, 2]]
   *   output3 = [[2, 2],[2, 2]]
   *
   */

  // Build eager context.
  TFE_ContextOptions* opts = TFE_NewContextOptions();

    }
    inputs_.push_back(t->output_);
    *output = tensorflow::down_cast<TracingTensorHandle*>(outputs[0]);
    return absl::OkStatus();
  }

  absl::Status Finalize(OutputList* outputs, AbstractFunction** f) override {
    std::vector<TF_Output> graph_outputs;
    graph_outputs.reserve(outputs->outputs.size());
    for (auto* abstract_output : outputs->outputs) {
      GraphTensor* output = dyn_cast<GraphTensor>(abstract_output);

        Thread.sleep(50);

        String output1 = thread.getOutput();
        boolean contains1 = thread.contains("concurrent1");

        thread.join(1000);

        String output2 = thread.getOutput();
        boolean contains2 = thread.contains("concurrent1");

        assertNotNull(output1);
        assertNotNull(output2);
        assertTrue(contains2);
    }

    @Test

//  noutputs - number of elements in `outputs` array
//  outputs - array of TF_Outputs that specify the outputs of the function.
//            If `noutputs` is zero (the function returns no outputs), `outputs`
//            can be null. `outputs` can contain the same tensor more than once.
//  output_names - The names of the function's outputs. `output_names` array

  int num_dims_out = TF_NumDims(model_out_tensor);
  TF_DeleteTensor(model_out_tensor);

  // If the output is a scalar, then return the scalar output
  if (num_dims_out == 0) {
    outputs[0] = model_out.release();
    return absl::OkStatus();
  }

  // Else, reduce sum the output to get a scalar

  // Will sum all dimensions, so get a Tensor containing [0,...,num_dims_out-1].
  AbstractTensorHandlePtr sum_dims;