{name: "SUBD", argLength: 2, reg: fp21, asm: "SUBD"},                    // arg0 - arg1
		{name: "MULF", argLength: 2, reg: fp21, asm: "MULF", commutative: true}, // arg0 * arg1
		{name: "MULD", argLength: 2, reg: fp21, asm: "MULD", commutative: true}, // arg0 * arg1
		{name: "DIVF", argLength: 2, reg: fp21, asm: "DIVF"},                    // arg0 / arg1

		{name: "FMSUBS", argLength: 3, reg: fp31, asm: "FMSUBS", commutative: true, typ: "Float32"},                                         // (arg0 * arg1) - arg2
		{name: "FNMADDS", argLength: 3, reg: fp31, asm: "FNMADDS", commutative: true, typ: "Float32"},                                       // -(arg0 * arg1) + arg2

brevity)
```mlir
  func.func @remove_first_result(%arg0, %arg1) {
    %0:2 = "tf.WhileRegion"(%arg0, %arg1) ({
    ^bb0(%arg2, %arg3):
      %1 = "tf.OpA"() {is_stateless = true}
      "tf.Yield"(%1)
    }, {
    ^bb0(%arg2, %arg3):
      %1 = "tf.OpB"(%arg2) {is_stateless = true}
      %2 = "tf.OpC"(%arg3) {is_stateless = true}
      "tf.Yield"(%1, %2)
    }) {is_stateless = true}

// CHECK-LABEL: func @replicate_result
func.func @replicate_result(%arg0: tensor<i1>, %arg1: tensor<i1>) {
  %0:4 = tf_executor.graph {
    %1:5 = tf_executor.island {
      %2:4 = tf_device.replicate([%arg0, %arg1] as %arg2: tensor<i1>) {n = 2 : i32} {
        %3 = "tf.opA"(%arg2) : (tensor<i1>) -> tensor<f32>
        %4 = "tf.opB"(%arg2) : (tensor<i1>) -> tensor<i32>
        tf_device.return %3, %4 : tensor<f32>, tensor<i32>

// -----

func.func private @branch_0(%arg0: tensor<!tf_type.resource>) -> tensor<*xf32>
func.func private @branch_1(%arg0: tensor<!tf_type.resource>) -> tensor<*xf32>

// CHECK-LABEL: func @testCase(%arg0: tensor<i32>, %arg1: tensor<!tf_type.resource<tensor<1x2x3xf32>>>)
func.func @testCase(%arg0: tensor<i32>, %arg1: tensor<!tf_type.resource<tensor<1x2x3xf32>>>) -> tensor<1x2x3xf32> {

// -----

func.func @multiple_return_no_controls_needed(%arg0: tensor<*xi32>, %arg1: tensor<i32>) -> (tensor<*xi32>, tensor<*xi32>) {
  %graph:2 = tf_executor.graph {
    %add1, %add1_control = tf_executor.island wraps "tf.Add"(%arg0, %arg1) : (tensor<*xi32>, tensor<i32>) -> tensor<*xi32>
    %add2, %add2_control = tf_executor.island wraps "tf.Add"(%add1, %arg1) : (tensor<*xi32>, tensor<i32>) -> tensor<*xi32>

func.func @QuantizeCustomTfOp(%arg0: tensor<128x128x!quant.uniform<u8:f32, 0.1:127>>,
    %arg1: tensor<1x!quant.uniform<u8:f32, 0.2:127>>, %arg2: tensor<1x!quant.uniform<u8:f32, 0.4:127>>,
    %arg3: tensor<1xi32>) -> (tensor<128x128x!quant.uniform<u8:f32, 0.2:125>>) {
  %0 = "tfl.dequantize"(%arg0) : (tensor<128x128x!quant.uniform<u8:f32, 0.1:127>>) -> tensor<128x128xf32>

func.func @addN_2(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>) -> tensor<*xf32> {
  // CHECK: %[[SUM0:.*]] = "tf.AddV2"(%arg0, %arg1)
  // return %[[SUM0]]
  %0 = "tf.AddN"(%arg0, %arg1) : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
  func.return %0 : tensor<*xf32>
}

// CHECK-LABEL: func @addN_3
func.func @addN_3(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>, %arg2: tensor<*xf32>) -> tensor<*xf32> {
  // CHECK: %[[SUM0:.*]] = "tf.AddV2"(%arg0, %arg1)

	// Memory operations
	{name: "Load", argLength: 2},                          // Load from arg0.  arg1=memory
	{name: "Dereference", argLength: 2},                   // Load from arg0.  arg1=memory.  Helper op for arg/result passing, result is an otherwise not-SSA-able "value".

}

func.func @testTanh(%arg0: tensor<10x10xf32>) -> tensor<10x10xf32> {
  // CHECK: _arithmetic_count = 6400 : i64
  %0 = "tfl.tanh"(%arg0) : (tensor<10x10xf32>) -> tensor<10x10xf32>
  func.return %0 : tensor<10x10xf32>
}

func.func @testAddN(%arg0: tensor<10x10xf32>, %arg1: tensor<10x10xf32>, %arg2: tensor<10x10xf32>) -> tensor<10x10xf32> {
  // CHECK: _arithmetic_count = 200 : i64