}
	}
}

var parseReplicationDecisionTest = []struct {
	name   string
	dsc    string
	expDsc ReplicateDecision
	expErr error
}{
	{ // 1.
		name: "empty string",
		dsc:  "",
		expDsc: ReplicateDecision{
			targetsMap: map[string]replicateTargetDecision{},
		},
		expErr: nil,
	},

	{ // 2.
		name:   "replicate decision for one target",

     * @param model The model to serialize, must not be {@code null}.
     * @throws IOException If the model could not be serialized.
     */
    void write(File output, Map<String, Object> options, Model model) throws IOException;

    /**
     * Writes the supplied model to the specified character writer. The writer will be automatically closed before the
     * method returns.
     *

              <exclude>org.apache.maven.model.Contributor#addProperty(java.lang.String,java.lang.String):METHOD_REMOVED</exclude>
              <exclude>org.apache.maven.model.Dependency#clearManagementKey():METHOD_REMOVED</exclude>
              <exclude>org.apache.maven.model.ModelBase#addProperty(java.lang.String,java.lang.String):METHOD_REMOVED</exclude>

	}
	return fi, nil
}

// hashDeterministicString will return a deterministic hash for the map values.
// Trivial collisions are avoided, but this is by no means a strong hash.
func hashDeterministicString(m map[string]string) uint64 {
	// Seed (random)
	crc := uint64(0xc2b40bbac11a7295)
	// Xor each value to make order independent
	for k, v := range m {

# | JDBC Type     | Java Native          | CSharp Native |
# | ------------------------------------------------------
# | CHAR          | java.lang.String     | String        |
# | VARCHAR       | java.lang.String     | String        |
# | LONGVARCHAR   | java.lang.String     | String        |
# | NUMERIC       | java.math.BigDecimal | decimal?      |
# | DECIMAL       | java.math.BigDecimal | decimal?      |

// Returns a sorted vector of std::pair<function_name, gradient_func> from
// graph_def.library().gradient()
std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def);

// Returns a sorted vector of names contained in `grad_def`
std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def);

class CSession {
 public:

 */
@Deprecated(since = "4.0.0")
interface ModelCacheTag<T> {

    /**
     * Gets the name of the tag.
     *
     * @return The name of the tag, must not be {@code null}.
     */
    String getName();

    /**
     * Gets the type of data associated with this tag.
     *
     * @return The type of data, must not be {@code null}.
     */
    Class<T> getType();

    /**

@Singleton
public class DefaultMetadataReader implements MetadataReader {

    public Metadata read(File input, Map<String, ?> options) throws IOException {
        Objects.requireNonNull(input, "input cannot be null");

        return read(Files.newInputStream(input.toPath()), options);
    }

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

import java.util.Map;

@GwtCompatible
public class SingletonImmutableMapMapInterfaceTest
    extends AbstractImmutableMapMapInterfaceTest<String, Integer> {
  @Override
  protected Map<String, Integer> makePopulatedMap() {
    return ImmutableMap.of("one", 1);
  }

  @Override
  protected String getKeyNotInPopulatedMap() {
    return "minus one";
  }

  @Override
  protected Integer getValueNotInPopulatedMap() {

import (
	big "."
	"runtime"
)

func fibber(c chan *big.Int, out chan string, n int64) {
	// Keep the fibbers in dedicated operating system
	// threads, so that this program tests coordination
	// between pthreads and not just goroutines.
	runtime.LockOSThread()

	i := big.NewInt(n)
	if n == 0 {
		c <- i
	}
	for {
		j := <-c
		out <- j.String()
		i.Add(i, j)
		c <- i
	}
}

func main() {