}
		}
	}

	conds := make([]clause.Expression, 0, 4)
	args = append([]interface{}{query}, args...)
	for idx, arg := range args {
		if arg == nil {
			continue
		}
		if valuer, ok := arg.(driver.Valuer); ok {
			arg, _ = valuer.Value()
		}

		switch v := arg.(type) {
		case clause.Expression:
			conds = append(conds, v)
		case *DB:
			v.executeScopes()

        resolvedOwner, (Class<?>) resolvedRawType, resolvedArgs);
  }

  private static <T> T expectArgument(Class<T> type, Object arg) {
    try {
      return type.cast(arg);
    } catch (ClassCastException e) {
      throw new IllegalArgumentException(arg + " is not a " + type.getSimpleName());
    }
  }

  /** A TypeTable maintains mapping from {@link TypeVariable} to types. */

      Parameter param = params.get(i);
      Object arg = args.get(i);
      // Use new fresh value generator because 'args' were populated with new fresh generator each.
      // Two newFreshValueGenerator() instances should normally generate equal value sequence.
      Object shouldBeEqualArg = generateDummyArg(param, newFreshValueGenerator());
      if (arg != shouldBeEqualArg
          && Objects.equal(arg, shouldBeEqualArg)

        final StringBuilder buf = new StringBuilder(100);
        buf.append(methodName).append("(");
        if (methodArgs != null && methodArgs.length > 0) {
            for (final Object arg : methodArgs) {
                buf.append(arg == null ? null : arg.getClass().getName()).append(", ");
            }
            buf.setLength(buf.length() - 2);
        }
        buf.append(")");
        return buf.toString();
    }

        type_annotation = annotated_args[0]
        fastapi_annotations = [
            arg
            for arg in annotated_args[1:]
            if isinstance(arg, (FieldInfo, params.Depends))
        ]
        fastapi_specific_annotations = [
            arg
            for arg in fastapi_annotations
            if isinstance(arg, (params.Param, params.Body, params.Depends))
        ]
        if fastapi_specific_annotations:

      Parameter param = params.get(i);
      Object arg = args.get(i);
      // Use new fresh value generator because 'args' were populated with new fresh generator each.
      // Two newFreshValueGenerator() instances should normally generate equal value sequence.
      Object shouldBeEqualArg = generateDummyArg(param, newFreshValueGenerator());
      if (arg != shouldBeEqualArg
          && Objects.equal(arg, shouldBeEqualArg)

         */
        public int add2(final int arg1, final int arg2) {
            return arg1 + arg2;
        }

        /**
         * @param arg
         * @return Integer
         */
        public Integer echo(final Integer arg) {
            return arg;
        }

        /**
         *
         */
        public void throwException() {
            throw new IllegalStateException("hoge");

            argumentsToParameters.entries.firstOrNull { (arg, _) ->
                when (arg) {
                    // TODO: better to utilize. See `createArgumentMapping` in [KtFirCallResolver]
                    is FirNamedArgumentExpression, is FirSpreadArgumentExpression ->
                        arg.psi == argumentExpression.parent
                    else ->
                        arg.psi == argumentExpression
                }

                                                  TF_Status* status) {
  auto* cc_ctx = reinterpret_cast<tensorflow::OpKernelContext*>(ctx);
  const tensorflow::Tensor& arg_tensor = cc_ctx->input(index);
  absl::Status cc_status;
  if (arg_tensor.dtype() != tensorflow::DT_RESOURCE) {
    cc_status = absl::InvalidArgumentError(
        absl::StrCat("Trying to obtain resource handle from Input[", index,

  if (!status->status.ok()) return nullptr;

  if (input_index >= op_def->input_arg_size() || input_index < 0) {
    status->status = tensorflow::errors::InvalidArgument(
        input_index, " out of range for ", op_name);
    return nullptr;
  }

  const tensorflow::OpDef_ArgDef& input_arg = op_def->input_arg()[input_index];

  if (input_arg.number_attr().empty()) {
    status->status = tensorflow::errors::NotFound(