<option value="io.reactivex.annotations.Experimental" />
          <option value="org.apache.http.annotation.Beta" />
          <option value="org.gradle.api.Incubating" />
          <option value="org.jetbrains.annotations.ApiStatus.Experimental" />
          <option value="rx.annotations.Beta" />
          <option value="rx.annotations.Experimental" />
        </set>
      </option>
    </inspection_tool>

.multi-language-selector {
    display: block;
}

.multi-language-selector .language-option[data-lang='groovy'] {
    background-position: 20px center;
    padding-left: 32px;
}

.multi-language-selector .language-option[data-lang='kotlin'] {
    background-position: 30px center;
    padding-left: 27px;
}

.multi-language-selector .language-option {
    background-color: white;
    border: 1px solid #f7f7f8;

  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
  let options = [
    Option<"default_min_", "default-min", "double", "-1.0",
               "Default minimum value for TFLite quantization">,
    Option<"default_max_", "default-max", "double", "1.0",
               "Default maximum value for TFLite quantization">,
    Option<"is_signed_", "is-signed", "bool", "false",
               "Is the corresponding integer signed">,

        return optionFile.addPathOption(option);
    }

    public JavadocOptionFileOption<List<File>> addPathOption(String option, String joinBy) {
        return optionFile.addPathOption(option, joinBy);
    }

    public JavadocOptionFileOption<List<String>> addStringsOption(String option) {
        return optionFile.addStringsOption(option);
    }

    /**

        return baselines
    }

    @Option(option = "warmups", description = "Number of warmups before measurements")
    void setWarmups(@Nullable String warmups) {
        this.warmups = warmups
    }

    @Option(option = "runs", description = "Number of iterations of measurements")
    void setRuns(@Nullable String runs) {
        this.runs = runs
    }

  }
  if (values.empty()) {
    return errors::InvalidArgument(
        "SetConfiguration() needs number of values > 0");
  }

  TF_Filesystem_Option option;
  memset(&option, 0, sizeof(option));
  option.name = const_cast<char*>(name.c_str());
  TF_Filesystem_Option_Value option_value;
  memset(&option_value, 0, sizeof(option_value));
  option_value.type_tag = TF_Filesystem_Option_Type_Buffer;

// Other strategies are also viable, though:
// Option 1) Return an empty string in case of error, but allow the user to
//    specify explicitly which errors to ignore.
// Option 2) Return the partially evaluated string if it is itself a valid
//    string, otherwise return the empty string in case of error.
// Option 3) Option 1 and 2.
// Option 4) Always return an empty string for now and implement Option 1 as

        def action = Mock(Function)

        when:
        def input = userInputHandler.askUser(action)

        then:
        0 * action._
        0 * outputEventBroadcaster._
        0 * userInputHandler._

        when:
        def result = input.get()

        then:

  let summary = "Quantize composite functions with QDQ input / outputs.";
  let options = [
    Option<"enable_per_channel_quantized_weight_",
        "enable-per-channel-quantized-weight",
        "bool", /*default=*/"true",
        "Whether to enable per-channel quantized weights.">,
    Option<"mlir_dump_file_name_", "mlir-dump-file-name",
        "std::optional<std::string>", /*default=*/"std::nullopt",

	dynInformerFactory dynamicinformer.DynamicSharedInformerFactory,
	recorderFactory profile.RecorderFactory,
	opts ...Option) (*Scheduler, error) {

	logger := klog.FromContext(ctx)
	stopEverything := ctx.Done()

	options := defaultSchedulerOptions
	for _, opt := range opts {
		opt(&options)
	}

	if options.applyDefaultProfile {
		var versionedCfg configv1.KubeSchedulerConfiguration
		scheme.Scheme.Default(&versionedCfg)