*
   * <p><b>Note:</b> {@code a.asSet(d).equals(b.asSet(d))} does not imply {@code a.equals(b)}! For
   * example, {@code a} and {@code b} could be {@code [2..4]} and {@code (1..5)}, or the empty
   * ranges {@code [3..3)} and {@code [4..4)}.
   *
   * <p><b>Warning:</b> Be extremely careful what you do with the {@code asSet} view of a large

    Set<String> expected = Collections.singleton("a");
    assertEquals(expected, Optional.of("a").asSet());
  }

  public void testAsSet_absent() {
    assertTrue("Returned set should be empty", Optional.absent().asSet().isEmpty());
  }

  public void testAsSet_presentIsImmutable() {
    Set<String> presentAsSet = Optional.of("a").asSet();
    try {
      presentAsSet.add("b");
      fail();

    public static Test suite() {
      TestSuite suite = new TestSuite();

      suite.addTest(
          NavigableSetTestSuiteBuilder.using(new ContiguousSetGenerator())
              .named("Range.asSet")
              .withFeatures(
                  CollectionSize.ANY,
                  KNOWN_ORDER,
                  ALLOWS_NULL_QUERIES,
                  NON_STANDARD_TOSTRING,

  "tf_saved_model.session_initializer"() {initializers = [@legacy_init_op]} : () -> ()
  "tf_saved_model.asset"() {filename = "assets/foo.txt", sym_name = "asset"} : () -> ()
  // CHECK: @legacy_init_op
  func.func @legacy_init_op(%arg0: tensor<!tf_type.string> {tf_saved_model.bound_input = @asset}) attributes {tf_saved_model.exported_names = ["f"]} {

        this.capabilities = capabilities;
    }

    @Override
    public List<? extends Capability> getCapabilities() {
        return capabilities.asSet().asList();
    }

    function_aliases: Function name -> function alias mapping.
    asset_file_defs: `AssetFileDef`s that associates the asset files and the
      name of the tensors to which the asset file names should be fed. The
      caller should make sure the asset files exist in the output saved model
      directory.

  Raises:
    ValueError iff the graph does not contain a valid signature or the file

// Sets up and runs the passes for exporting `module_op`. The behavior of the
// exporting passes is controlled by `export_opts`. Returns `AssetFileDef`s that
// associate the input arguments of @main and the asset file names. Asset file
// names will be used to feed the corresponding tensors during initialization
// upon model loading.
// TODO: b/329206105 - Add unit tests after decomposing post processing passes.

  "tf_saved_model.global_tensor"() {is_mutable, sym_name = "y", type = tensor<3x1xi32>, value = dense<[[1], [2], [3]]> : tensor<3x1xi32>} : () -> ()
  "tf_saved_model.asset"() {sym_name = "z", filename = "file"} : () -> ()
  func.func @serving_default(
      %arg0: tensor<1x3xi32> {tf_saved_model.index_path = ["x"]},
      %arg1: tensor<!tf_type.resource<tensor<3x1xi32>>> {tf_saved_model.bound_input = @y},

namespace mlir::quant {

// Converts arguments of the @main function that are bound to
// `tf_saved_model::AssetOp`s into regular tensor args. Returns `AsestFileDef`s
// that associates the arg with the asset.
//
// In detail, this function performs the following:
// * Replaces "tf_saved_model.bound_input" attributes to
//   "tf_saved_model.index_path", if the bound input is attached to the
//   `tf_saved_model::AssetOp`.

# CHECK-SAME: bad_consumers
# CHECK-SAME: min_consumer
# CHECK-SAME: producer

# CHECK: tf_saved_model.session_initializer
# CHECK-SAME: initializers = [@[[restore:.*]]]

# CHECK: "tf_saved_model.asset"()
# CHECK-SAME: <{filename = [[filename:.*]], sym_name = "[[sym_name:.*]]"}> : () -> ()

# CHECK:      func @[[restore]](
# CHECK-SAME:   [[variable_path:%.*]]: tensor<!tf_type.string> {tf_saved_model.bound_input = @[[sym_name]]}