start("3", id2),
            finished("3", id1),
            finished("2", id1),
            finished("1", id1),
            finished("3", id2),
            finished("2", id2),
            finished("1", id2),
        ]
    }

    def "does not forward progress notifications outside of start and finish"() {
        given:
        manager.addListener(recordingListener("1"))

    // CHECK: %[[MAX:.*]] = stablehlo.maximum %[[ARG1]], %[[ARG2]] : tensor<!quant.uniform<i8:f32, 3.000000e-01:1>>
    // CHECK: stablehlo.return %[[MAX]] : tensor<!quant.uniform<i8:f32, 3.000000e-01:1>>

	// l 1
	// l 1
	// o 1
	// , 1
	//   1
	// 世 3
	// 界 3
}

func ExampleDecodeRuneInString() {
	str := "Hello, 世界"

	for len(str) > 0 {
		r, size := utf8.DecodeRuneInString(str)
		fmt.Printf("%c %v\n", r, size)

		str = str[size:]
	}
	// Output:
	// H 1
	// e 1
	// l 1
	// l 1
	// o 1
	// , 1
	//   1
	// 世 3
	// 界 3
}

func ExampleEncodeRune() {
	r := '世'

			Original: []byte(`
mergingList:
  - name: 1
  - name: 3
`),
			TwoWay: []byte(`
$setElementOrder/mergingList:
  - name: 3
  - name: 2
  - name: 1
mergingList:
  - name: 3
    value: 3
  - name: 1
    value: 1
`),
			Modified: []byte(`
mergingList:
  - name: 3
    value: 3
  - name: 1
    value: 1
`),
		},
	},
	{

		t.Errorf("UpdateStatefulSetStatus mutated the sets replicas %d", set.Status.Replicas)
	}
}

func TestStatefulSetStatusUpdaterUpdatesObservedGeneration(t *testing.T) {
	set := newStatefulSet(3)
	status := apps.StatefulSetStatus{ObservedGeneration: 3, Replicas: 2}
	fakeClient := &fake.Clientset{}
	updater := NewRealStatefulSetStatusUpdater(fakeClient, nil)

  %1 = "tf.BiasAdd"(%0, %arg0) {data_format = "NHWC"} : (tensor<*xf32>, tensor<128xf32>) -> tensor<*xf32>
  %2 = "tf.Relu"(%1) : (tensor<*xf32>) -> tensor<*xf32>
  %3 = "tf.Identity"(%2) : (tensor<*xf32>) -> tensor<*xf32>
  func.return %3 : tensor<*xf32>
}

// CHECK-LABEL: conv2DBiasAdd_relu6Activation

        final byte[] outData = new byte[num * 3 + lastBytes];
        for (int i = 0; i < num; i++) {
            decode(inData, i * 4, outData, i * 3);
        }
        switch (lastBytes) {
        case 1:
            decode1byte(inData, num * 4, outData, num * 3);
            break;
        case 2:
            decode2byte(inData, num * 4, outData, num * 3);
            break;
        default:

  %2 = "tf.Relu6"(%1) {device = ""} : (tensor<*xf32>) -> tensor<*xf32>


  %3 = "tf.Conv2D"(%arg0, %arg1) {
    data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [],
    padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true
  } : (tensor<1x3x4x3xf32>, tensor<2x3x3x2xf32>) -> tensor<*xf32>
  %4 = "tf.BiasAdd"(%3, %cst) {data_format = "NHWC", device = ""} : (tensor<*xf32>, tensor<2xf32>) -> tensor<*xf32>

      %3 = "tf.A"() : () -> (tensor<f32>)
      "tf.Yield"(%3) : (tensor<f32>) -> ()
      }, {
      %3 = "tf.C"() : () -> (tensor<f32>)
      "tf.Yield"(%3) : (tensor<f32>) -> ()
     }) { is_stateless = true } : (tensor<i1>) -> (tensor<f32>)
    %2 = "tf.IfRegion"(%0) ({
      %3 = "tf.B"() : () -> (tensor<i32>)
      "tf.Yield"(%3) : (tensor<i32>) -> ()
      }, {
      %3 = "tf.D"() : () -> (tensor<i32>)

  %1 = "mhlo.broadcast_in_dim"(%0) <{broadcast_dimensions = dense<> : tensor<0xi64>}> : (tensor<f32>) -> tensor<2xf32>
  %2 = mhlo.constant dense<3.40282347E+38> : tensor<f32>
  %3 = "mhlo.broadcast_in_dim"(%2) <{broadcast_dimensions = dense<> : tensor<0xi64>}> : (tensor<f32>) -> tensor<2xf32>
  %4 = mhlo.constant dense<3.000000e+00> : tensor<f32>
  %5 = "mhlo.broadcast_in_dim"(%4) <{broadcast_dimensions = dense<> : tensor<0xi64>}> : (tensor<f32>) -> tensor<2xf32>