panic("variable value type must be a pointer")
	}
	defVal := reflect.ValueOf(val)
	if defVal.Kind() == reflect.Ptr {
		defVal = defVal.Elem()
	}
	if defVal.Type() != ptrVal.Type().Elem() {
		panic(fmt.Sprintf("default type does not match variable type: %v != %v", defVal.Type(), ptrVal.Type().Elem()))
	}
	ptrVal.Elem().Set(defVal)
	return textValue{p}
}

func (v textValue) Set(s string) error {

		case int64:
			ii = intstr.FromInt32(int32(item))
		case string:
			ii = intstr.FromString(item)
		default:
			ii = intstr.FromInt32(0)
		}
		intVal, err := intstr.GetScaledValueFromIntOrPercent(&ii, 100, false)
		if err != nil || intVal == 0 {
			return true
		}
		return false
	}
	if spec["maxUnavailable"] != nil && spec["minAvailable"] != nil {

			return
		}

		p.expectKeyword("i")
		reval := constant.MakeFromLiteral(re, token.FLOAT, 0)
		if reval == nil {
			p.error("could not parse real component of complex literal")
		}
		imval := constant.MakeFromLiteral(im+"i", token.IMAG, 0)
		if imval == nil {
			p.error("could not parse imag component of complex literal")
		}
		val = constant.BinaryOp(reval, token.ADD, imval)
		typ = types.Typ[types.UntypedComplex]

  auto a = ops::_Arg(scope.WithOpName("A"), DT_INT32, 0);
  auto b = ops::_Arg(scope.WithOpName("B"), DT_INT32, 1);
  auto c = ops::Add(scope.WithOpName("C"), a, b);
  auto d = ops::_Retval(scope.WithOpName("D"), c, 0);
  TF_RETURN_IF_ERROR(scope.ToGraph(graph.get()));
  return graph;
}

absl::StatusOr<FunctionDef> SampleFuntionAddXY(const std::string& name) {

    func.func @main(%arg0: tensor<3x3x10xbf16>, %arg1: tensor<3xi32>) -> tensor<1x?x4xbf16> attributes {allow_soft_placement = false, tf.entry_function = {control_outputs = "", inputs = "_arg0,_arg1,_arg2", outputs = "_retval0"}} {
      %cst = "tf.Const"() {value = dense<[1, -1, 4]> : tensor<3xi32>} : () -> tensor<3xi32>

	for _, e := range envs {
		if !shouldExtract(e, prefix) {
			continue
		}
		v := e[metaPrefixLen:]
		if !isEnvVar(v) {
			continue
		}
		metaKey, metaVal := parseEnvVar(v)
		set(meta, metaKey, metaVal)
	}
}

func shouldExtract(envVar, prefix string) bool {
	return strings.HasPrefix(envVar, prefix)
}

func isEnvVar(str string) bool {
	return strings.Contains(str, "=")

// NewReferencedResourceNotFound returns a new diag.Message based on ReferencedResourceNotFound.
func NewReferencedResourceNotFound(r *resource.Instance, reftype string, refval string) diag.Message {
	return diag.NewMessage(
		ReferencedResourceNotFound,
		r,
		reftype,
		refval,
	)
}

// NewNamespaceNotInjected returns a new diag.Message based on NamespaceNotInjected.

  // CHECK-NEXT: %[[SIZE:.*]] = "tf.Reshape"(%[[NUM]], %[[SIZE_SHAPE]])
  %tl = "tf.TensorListReserve"(%elem_shape, %num) : (tensor<0xi32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<f32>>>
  // CHECK-NEXT: %[[SETVAL:.*]] = "tf._SomeOp"()
  %elem = "tf._SomeOp"() : () -> tensor<f32>
  // CHECK-NEXT: %[[SIZE_SHAPE1:.*]] = "tf.Const"() <{value = dense<1> : tensor<1xi32>}>

static const char kImportModelDefaultGraphFuncName[] = "main";

// Please refer to the TFG dialect description for the list of used attributes.
// Belows are the attributes in TFE.
// TFE Arguments and Results (Got from "_Arg",
// "_Retval", .etc)
//  NodeDef.device <-> "tf.device"
//  NodeDef.attr <-> "tf."
//
// TFE general operations
//  NodeDef.device <-> "device"
//
// The following two functions are only used for mapping/excluding attributes

    code: IST0101
    level: Error
    description: "A resource being referenced does not exist."
    template: "Referenced %s not found: %q"
    args:
      - name: reftype
        type: string
      - name: refval
        type: string

  - name: "NamespaceNotInjected"
    code: IST0102
    level: Info
    description: "A namespace is not enabled for Istio injection."