String gradleApiInfoJarPrefix = getGradleApiInfoJarPrefix().get();
        File gradleRuntimeApiInfoJar = from.filter(file -> file.getName().startsWith(gradleApiInfoJarPrefix)).getSingleFile();
        URI uri = URI.create("jar:" + gradleRuntimeApiInfoJar.getAbsoluteFile().toURI());
        try (FileSystem fs = FileSystems.newFileSystem(uri, Collections.emptyMap())) {
            Path upgradedPropertiesJson = fs.getPath(UPGRADED_PROPERTIES_FILE);

# Query Parameter Models { #query-parameter-models }

If you have a group of **query parameters** that are related, you can create a **Pydantic model** to declare them.

This would allow you to **re-use the model** in **multiple places** and also to declare validations and metadata for all the parameters at once. 😎

/// note

This is supported since FastAPI version `0.115.0`. 🤓

///

    // Input parameters for WitnessUnregister
    private byte[] contextHandle;

    /**
     * Creates a new WitnessUnregister RPC message.
     */
    public WitnessUnregisterMessage() {
        super(WITNESS_UNREGISTER);
        this.contextHandle = new byte[20]; // Standard DCE/RPC context handle size
    }

    /**
     * Creates a new WitnessUnregister RPC message with the specified context handle.
     *

    protected
    fun generateSubprojectsJson(): String {
        val subprojects = generateSubprojects()
        val gson = GsonBuilder().setPrettyPrinting().create()
        return gson.toJson(subprojects) + '\n'
    }

    private
    fun generateSubprojectsDirectories(): List<File> {
        val subprojectRoots = platformsFolder.asFile.listFiles(File::isDirectory)

  @CollectionSize.Require(absent = {ZERO, ONE})
  public void testRemoveAll_duplicate() {
    ArrayWithDuplicate<E> arrayAndDuplicate = createArrayWithDuplicateElement();
    collection = getSubjectGenerator().create(arrayAndDuplicate.elements);
    E duplicate = arrayAndDuplicate.duplicate;

    assertTrue(
        "removeAll(intersectingCollection) should return true",
        getList().removeAll(MinimalCollection.of(duplicate)));

  @CollectionSize.Require(absent = {ZERO, ONE})
  public void testRemoveAll_duplicate() {
    ArrayWithDuplicate<E> arrayAndDuplicate = createArrayWithDuplicateElement();
    collection = getSubjectGenerator().create(arrayAndDuplicate.elements);
    E duplicate = arrayAndDuplicate.duplicate;

    assertTrue(
        "removeAll(intersectingCollection) should return true",
        getList().removeAll(MinimalCollection.of(duplicate)));

/**
 * Response data for FSCTL_QUERY_NETWORK_INTERFACE_INFO
 */
public class QueryNetworkInterfaceInfoResponse implements Decodable {

    private List<NetworkInterfaceInfo> interfaces;

    /**
     * Create query network interface info response
     */
    public QueryNetworkInterfaceInfoResponse() {
        this.interfaces = new ArrayList<>();
    }

    /**
     * Get the list of network interfaces
     *

     */
    private final int lineNumber;

    /**
     * The one-based index of the column containing the error.
     */
    private final int columnNumber;

    /**
     * Creates a new parser exception with the specified details.
     *
     * @param message The error message, may be {@code null}.
     * @param lineNumber The one-based index of the line containing the error or {@code -1} if unknown.

     */
    private final Duration wallTime;

    /**
     * The total amount of time spent for to run mojos in milliseconds.
     */
    private final Duration execTime;

    /**
     * Creates a new build summary for the specified project.
     *
     * @param project The project being summarized, must not be {@code null}.
     * @param time The build time of the project in milliseconds.
     */

      status->status = TF_TensorToTensor(input_tensors[i], &input_tensor);
      if (!status->status.ok()) return;
      input_tensors_vector[i] = &input_tensor;
    }
  }

  // Create an inference context with dummy values, which will be updated later.
  InferenceContext c(TF_GRAPH_DEF_VERSION, node_def, op_reg_data->op_def,
                     std::vector<ShapeHandle>(num_inputs), input_tensors_vector,