public object KaDeclarationModifiersRendererForSource {
    public val NO_IMPLICIT_MODIFIERS: KaDeclarationModifiersRenderer = KaDeclarationModifiersRenderer {
        modifierListRenderer = KaModifierListRenderer.AS_LIST
        modifiersSorter = KaModifiersSorter.CANONICAL
        modalityProvider = KaRendererModalityModifierProvider.WITHOUT_IMPLICIT_MODALITY
        visibilityProvider = KaRendererVisibilityModifierProvider.NO_IMPLICIT_VISIBILITY

    attrs=['mode: {"REFLECT", "SYMMETRIC"}'],
    derived_attrs=['T: type', 'Tpaddings: {int32, int64} = DT_INT32'],
    outputs=['output: T'])
def _composite_mirror_pad(input_, paddings, mode):
  shape = input_.shape.as_list()
  for i in range(len(shape)):
    rdims = tf.raw_ops.OneHot(
        indices=i, depth=len(shape), on_value=True, off_value=False, axis=-1)
    rarray = tf.raw_ops.Reverse(tensor=input_, dims=rdims)

    public fun renderSuperTypes(
        analysisSession: KaSession,
        symbol: KaClassOrObjectSymbol,
        declarationRenderer: KaDeclarationRenderer,
        printer: PrettyPrinter,
    )

    public object AS_LIST : KaSuperTypeListRenderer {
        override fun renderSuperTypes(
            analysisSession: KaSession,
            symbol: KaClassOrObjectSymbol,
            declarationRenderer: KaDeclarationRenderer,

        analysisSession: KaSession,
        symbol: KaDeclarationSymbol,
        declarationModifiersRenderer: KaDeclarationModifiersRenderer,
        printer: PrettyPrinter,
    )

    public object AS_LIST : KaModifierListRenderer {
        override fun renderModifiers(
            analysisSession: KaSession,
            symbol: KaDeclarationSymbol,
            declarationModifiersRenderer: KaDeclarationModifiersRenderer,

        bodyMemberScopeSorter = KaRendererBodyMemberScopeSorter.ENUM_ENTRIES_AT_BEGINING

        superTypeRenderer = KaSuperTypeRenderer.WITH_OUT_APPROXIMATION
        superTypeListRenderer = KaSuperTypeListRenderer.AS_LIST
        superTypesFilter = KaSuperTypesFilter.NO_DEFAULT_TYPES
        superTypesArgumentRenderer = KaSuperTypesCallArgumentsRenderer.EMPTY_PARENS
        functionLikeBodyRenderer = KaFunctionLikeBodyRenderer.NO_BODY

     kernel_initializer=tf.variance_scaling_initializer(),
     data_format=data_format)

    # Use the image size without space-to-depth transform as the input of conv0.
    batch_size, h, w, channel = inputs.get_shape().as_list()
    conv0.build([
     batch_size, h * space_to_depth_block_size, w * space_to_depth_block_size,
     channel // (space_to_depth_block_size**2)
    ])

    kernel = conv0.weights[0]

            copy.call();
        } else {
            Object[] argList = new Object[inputs.size() + 1];
            argList[0] = subject;
            int i = 1;
            for (Object arg : inputs) {
                argList[i++] = arg;
            }
            copy.call(argList);
        }
    }

    private List<Class<?>> parseInputTypes(Closure<?> closure) {

            (K k, V v) -> {
              int index = keys().asList().indexOf(k);
              return values().asList().get(index + 1);
            });
    List<Entry<K, V>> expectedEntries = new ArrayList<>();
    for (Entry<K, V> entry : getSampleEntries()) {
      int index = keys().asList().indexOf(entry.getKey());
      expectedEntries.add(Helpers.mapEntry(entry.getKey(), values().asList().get(index + 1)));
    }

        actual = Arrays.asList(KuromojiCSVUtil.parse(value));
        assertThat(actual, is(expected));

        value = "\"Fess,FESS\"";
        expected = Arrays.asList("\"Fess,FESS\"");
        actual = Arrays.asList(KuromojiCSVUtil.parse(value));
        assertThat(actual, is(expected));

        value = " ";
        expected = Arrays.asList(" ");

    }
    return Longs.asList(temp);
  }

  @J2ktIncompatible
  @GwtIncompatible // suite
  public static Test suite() {
    List<ListTestSuiteBuilder<Long>> builders =
        ImmutableList.of(
            ListTestSuiteBuilder.using(new LongsAsListGenerator()).named("Longs.asList"),
            ListTestSuiteBuilder.using(new LongsAsListHeadSubListGenerator())
                .named("Longs.asList, head subList"),