createInstrumentationClasspathMarker(outputs);
        // Output original file if it's safe to load from cache loader ELSE copy an entry
        if (input.isDirectory()) {
            // Directories are ok to use outside the cache, since they are not locked by the daemon.
            outputs.dir(input);
        } else if (internalServices.get().getGlobalCacheLocations().isInsideGlobalCache(input.getAbsolutePath())) {

// Creates parameters (placeholders) in the tracing `ctx` using the shape and
// dtype of `inputs`.
Status CreateParamsForInputs(AbstractContext* ctx,
                             absl::Span<AbstractTensorHandle* const> inputs,
                             std::vector<AbstractTensorHandle*>* params);

// A callable that takes tensor inputs and returns zero or more tensor outputs.
using Model = std::function<Status(AbstractContext*,

  3: 13
Enter selection (default: 12) [1..3] """)
    }

    def "accepts valid input"() {
        def event = new SelectOptionPromptEvent(123, "question", ["1", "2", "3", "4"], 1)

        expect:
        def result = event.convert(input)
        result.response == expected
        result.newPrompt == null

        where:
        input | expected
        '1'   | 0
        '4'   | 3
        ' 1 ' | 0
    }

                    .id(TextUtil.screamingSnakeToKebabCase(UNSUPPORTED_VALUE_TYPE) + "-for-input", "Unsupported value type for @Input annotation", GradleCoreProblemGroup.validation().property())
                    .contextualLabel(String.format("has @Input annotation used on type '%s' or a property of this type", URL.class.getName()))

    @Override
    public Model read(Reader input, Map<String, ?> options) throws IOException {
        Objects.requireNonNull(input, "input cannot be null");

        try (Reader in = input) {
            return read(in, null, options);
        }
    }

    @Override
    public Model read(InputStream input, Map<String, ?> options) throws IOException {
        Objects.requireNonNull(input, "input cannot be null");

	// in the analyzed source code such as a potential mistake.
	// It may be called by the Run function.
	Report func(Diagnostic)

	// ResultOf provides the inputs to this analysis pass, which are
	// the corresponding results of its prerequisite analyzers.
	// The map keys are the elements of Analysis.Required,
	// and the type of each corresponding value is the required

            @Override
            public void onInput(ForwardInput input) {
                LOGGER.debug("Writing forwarded input on this process' stdin.");
                stdInStream.received(input.getBytes());
            }

            @Override
            public void onUserResponse(UserResponse input) {
                inputReader.putInput(new UserInputReader.TextResponse(input.getResponse()));
            }

            @Override

	// sort.Float64s.
	input := []float64{1.0, 0.0, negzero, math.Inf(1), math.Inf(-1), math.NaN()}
	sort.Float64s(input)
	for i := 0; i < len(input)-1; i++ {
		if cmp.Less(input[i+1], input[i]) {
			t.Errorf("Less sort mismatch at %d in %v", i, input)
		}
		if cmp.Compare(input[i], input[i+1]) > 0 {
			t.Errorf("Compare sort mismatch at %d in %v", i, input)
		}
	}
}

func TestOr(t *testing.T) {

                    Assert.returnTypesFor task.inputs, "dir", TaskInputFilePropertyBuilder, TaskInputFilePropertyBuilderInternal
                    Assert.returnTypesFor task.inputs, "file", TaskInputFilePropertyBuilder, TaskInputFilePropertyBuilderInternal
                    Assert.returnTypesFor task.inputs, "files", TaskInputFilePropertyBuilder, TaskInputFilePropertyBuilderInternal
                }

  return Run(FeedType{}, fetch_outputs, {}, outputs);
}

Status ClientSession::Run(const FeedType& inputs,
                          const std::vector<Output>& fetch_outputs,
                          std::vector<Tensor>* outputs) const {
  return Run(inputs, fetch_outputs, {}, outputs);
}

Status ClientSession::Run(const FeedType& inputs,
                          const std::vector<Output>& fetch_outputs,