// ppc64x: "MOVWZ", "RLWNM\t[$]1, R[0-9]*, [$]28, [$]3, R"
	io64[4] = uint64(bits.RotateLeft32(io32[0], 1) & 0xF000000F)

	// ppc64x: "RLWNM\t[$]0, R[0-9]*, [$]4, [$]19, R"
	io32[0] = io32[0] & 0x0FFFF000
	// ppc64x: "RLWNM\t[$]0, R[0-9]*, [$]20, [$]3, R"
	io32[1] = io32[1] & 0xF0000FFF
	// ppc64x: -"RLWNM", MOVD, AND
	io32[2] = io32[2] & 0xFFFF0002

	var bigc uint32 = 0x12345678
	// ppc64x: "ANDCC\t[$]22136"

		panic("u16 != ju16")
	}
	if u32 != iu32 {
		panic("u32 != iu32")
	}
	if u32 != ju32 {
		panic("u32 != ju32")
	}
	if u64 != iu64 {
		panic("u64 != iu64")
	}
	if u64 != ju64 {
		panic("u64 != ju64")
	}
	if u128 != iu128 {
		panic("u128 != iu128")
	}
	if u128 != ju128 {
		panic("u128 != ju128")
	}
	if f32 != if32 {
		panic("f32 != if32")
	}
	if f32 != jf32 {

         %cond = "tf.NotEqual"(%carg0, %limit) : (tensor<i32>, tensor<i32>) -> tensor<i1>
         "tf.Yield"(%cond) : (tensor<i1>) -> ()
      }, {
       // CHECK: {{.*}}({{.+}}: tensor<i32>, {{.+}}: tensor<1x2x3xf32>):
       ^bb0(%barg0: tensor<i32>, %barg1: tensor<*xf32>):
        %one = arith.constant dense<1> : tensor<i32>
        %sub = "tf.Sub"(%barg0, %one) : (tensor<i32>, tensor<i32>) -> tensor<i32>

    %1 = "tf.Add"(%val_var1, %cst_0) : (tensor<i32>, tensor<i32>) -> tensor<i32>
    %2 = "tf.Mul"(%1, %cst_1) : (tensor<i32>, tensor<i32>) -> tensor<i32>
    %3 = "tf.AddV2"(%arg2, %1) : (tensor<i32>, tensor<i32>) -> tensor<i32>
    %4 = "tf.Div"(%arg3, %2) : (tensor<i32>, tensor<i32>) -> tensor<i32>
    "tf.Yield"(%3, %4) : (tensor<i32>, tensor<i32>) -> ()

    tf_executor.fetch %ro#0, %ro#1 : tensor<i32>, tensor<i32>
  }
  return %0#0, %0#1 : tensor<i32>, tensor<i32>
}

// -----

func.func @validate_tpu_replicate_wrong_attr(%arg0: tensor<i32>, %arg1: tensor<i32>, %arg2: tensor<i32>, %arg3: tensor<i32>) -> (tensor<i32>, tensor<i32>) {
  %0:2 = tf_executor.graph {

  // CHECK: [[z:%.*]] = tf_mlrt.executeop
  %z = "tf.Identity"(%x) {__op_key = 1: i32}: (tensor<i32>) -> tensor<i32>
  // CHECK: [[y:%.*]] = tf_mlrt.await [[y_future]]
  // CHECK-NEXT: tf_mlrt.executeop([[y]]
  %w = "tf.AddV2"(%y, %z) {__op_key = 2: i32}: (tensor<i32>, tensor<i32>) -> tensor<i32>
  // CHECK-NEXT: tf_mlrt.executeop([[y]]

  %a6 = "tf.AddV2"(%a5, %a) : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %a7 = "tf.AddV2"(%a6, %a) : (tensor<i32>, tensor<i32>) -> tensor<i32>

  %b0 = "tf.Sub"(%a3, %b) : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %b1 = "tf.Sub"(%b0, %b) : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %b2 = "tf.Sub"(%b1, %b) : (tensor<i32>, tensor<i32>) -> tensor<i32>

  %1 = "tf.Less"(%arg, %0) : (tensor<i32>, tensor<i32>) -> tensor<i1>
  func.return %1 : tensor<i1>
}

func.func @side_effect_body(%arg: tensor<i32>, %handle: tensor<!tf_type.resource<tensor<i32>>>) -> (tensor<i32>, tensor<!tf_type.resource<tensor<i32>>>) {
  %0 = "tf.ReadVariableOp"(%handle) : (tensor<!tf_type.resource<tensor<i32>>>) -> tensor<i32>
  %1 = "tf.AddV2"(%arg, %0) : (tensor<i32>, tensor<i32>) -> tensor<i32>

}

func.func @consecutive_add_sub(%arg0: tensor<i32>) -> (tensor<i32>) {
  %cst = "tf.Const"() {value = dense<-18> : tensor<i32>} : () -> tensor<i32>
  %cst_1 = "tf.Const"() {value = dense<-12> : tensor<i32>} : () -> tensor<i32>
  %0 = "tf.AddV2"(%arg0, %cst) {T = i32, device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %1 = "tf.Sub"(%0, %cst_1) {T = i32, device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>
  return %1 : tensor<i32>

  %1 = "tf.PartitionedCall"(%arg0) {config = "", config_proto = "", executor_type = "", f = @callee1} : (tensor<i32>) -> tensor<i32>
  func.return %1 : tensor<i32>
}

// CHECK-LABEL: func @callee1
// CHECK-SAME: ([[ARG0:%.*]]: tensor<i32>)
func.func @callee1(%arg0: tensor<i32>) -> tensor<i32> {
  // CHECK-NOT:  "tf.Identity"
  // CHECK:      return [[ARG0]]
  %0 = "tf.Identity"(%arg0) : (tensor<i32>) -> tensor<i32>