for key in received_body.keys():
        if key not in field_aliases:
            param_values = received_body.getlist(key)
            if len(param_values) == 1:
                values[key] = param_values[0]
            else:
                values[key] = param_values
    return values


async def request_body_to_args(
    body_fields: list[ModelField],

  }

  private static @Nullable Object[] getParameterValues(Method method) {
    FreshValueGenerator paramValues = new FreshValueGenerator();
    List<@Nullable Object> passedArgs = new ArrayList<>();
    for (Class<?> paramType : method.getParameterTypes()) {
      passedArgs.add(paramValues.generateFresh(paramType));
    }
    return passedArgs.toArray();
  }

    private RequestManager createMockRequestManager(final String paramValue) {
        return new org.lastaflute.web.servlet.request.SimpleRequestManager() {
            @Override
            public OptionalThing<String> getParameter(String name) {
                if (paramValue != null) {
                    return OptionalThing.of(paramValue);
                }
                return OptionalThing.empty();
            }

        if (initParamMap != null) {
            try {
                final Object paramValue = initParamMap.get(key);
                if (paramValue == null) {
                    return defaultValue;
                }

                return convertObj(paramValue, clazz);
            } catch (final Exception e) {

  }

  private static @Nullable Object[] getParameterValues(Method method) {
    FreshValueGenerator paramValues = new FreshValueGenerator();
    List<@Nullable Object> passedArgs = new ArrayList<>();
    for (Class<?> paramType : method.getParameterTypes()) {
      passedArgs.add(paramValues.generateFresh(paramType));
    }
    return passedArgs.toArray();
  }

    *   `LinearOperator.matmul` now returns a new `LinearOperator`.
*   New ops and improved op functionality
    *   Add a Nearest Neighbor Resize op.
    *   Add an `ignore_unknown` argument to `parse_values` which suppresses
        ValueError for unknown hyperparameter types. Such * Add
        `tf.linalg.matvec` convenience function.
    *   `tf.einsum()`raises `ValueError` for unsupported equations like