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}

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)

// CHECK: %[[XLA_CALL_MODULE:.*]] = "tf.XlaCallModule"(%arg0, %[[CONST_0]], %[[CONST_1]])
// CHECK: return %[[XLA_CALL_MODULE:.*]] : tensor<1x3xf32>
// CHECK: }

// CHECK-LABEL: private @composite_dot_general_with_bias_same_shape_fn_1
// CHECK: %[[DOT_GENERAL:.*]] = stablehlo.dot_general %arg0, %arg1
// CHECK: %[[ADD:.*]] = stablehlo.add %[[DOT_GENERAL]], %arg2
// CHECK: return %[[ADD]] : tensor<1x3xf32>
// CHECK: }

// -----

  func.func private @composite_dot_general_with_bias_same_shape_fn(%arg0: tensor<1x2xf32>, %arg1: tensor<2x3xf32>, %arg2: tensor<1x3xf32>) -> tensor<1x3xf32> attributes {_from_xla_call_module} {
    %0 = stablehlo.dot_general %arg0, %arg1, contracting_dims = [1] x [0] : (tensor<1x2xf32>, tensor<2x3xf32>) -> tensor<1x3xf32>
    %1 = stablehlo.add %0, %arg2 : tensor<1x3xf32>
    return %1 : tensor<1x3xf32>
  }

    %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_b", device = "", transpose_a = false, transpose_b = false} : (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>
    return %0 : tensor<2x2xf32>
  }
  func.func private @composite_matmul_fn_2_0(%arg0: tensor<2x2xf32>, %arg1: tensor<2x2xf32>) -> tensor<2x2xf32> attributes {tf_quant.composite_function} {

  // CHECK-NEXT: return %[[CONST]]
  func.return %arg0, %arg1 : tensor<*x!tf_type.resource<tensor<f32>>>, tensor<*x!tf_type.resource<tensor<f32>>>
}
// CHECK: func @while_cond1(%arg0: tensor<f32>)
func.func @while_cond1(%arg0: tensor<*x!tf_type.resource<tensor<f32>>>, %arg1: tensor<*x!tf_type.resource<tensor<f32>>>) -> tensor<f32> {
  %id = "tf.Identity"(%arg0) : (tensor<*x!tf_type.resource<tensor<f32>>>) -> tensor<*x!tf_type.resource<tensor<f32>>>

func p384Selectznz(out1 *[6]uint64, arg1 p384Uint1, arg2 *[6]uint64, arg3 *[6]uint64) {
	var x1 uint64
	p384CmovznzU64(&x1, arg1, arg2[0], arg3[0])
	var x2 uint64
	p384CmovznzU64(&x2, arg1, arg2[1], arg3[1])
	var x3 uint64
	p384CmovznzU64(&x3, arg1, arg2[2], arg3[2])
	var x4 uint64
	p384CmovznzU64(&x4, arg1, arg2[3], arg3[3])
	var x5 uint64
	p384CmovznzU64(&x5, arg1, arg2[4], arg3[4])
	var x6 uint64

func KeyctlInt(cmd int, arg2 int, arg3 int, arg4 int, arg5 int) (ret int, err error) {
	r0, _, e1 := Syscall6(SYS_KEYCTL, uintptr(cmd), uintptr(arg2), uintptr(arg3), uintptr(arg4), uintptr(arg5), 0)
	ret = int(r0)
	if e1 != 0 {
		err = errnoErr(e1)
	}
	return
}

// THIS FILE IS GENERATED BY THE COMMAND AT THE TOP; DO NOT EDIT

func KeyctlBuffer(cmd int, arg2 int, buf []byte, arg5 int) (ret int, err error) {

  %0 = "tf.BatchMatMul"(%arg0, %arg1) : (tensor<4x5xf32>, tensor<5x6xf32>) -> tensor<4x6xf32>
  func.return %0 : tensor<4x6xf32>

  // CHECK-LABEL: batchMatMulMatrix
  // CHECK: %[[MATMUL_1:.*]] = "tf.MatMul"(%arg0, %arg1) <{grad_a = false, grad_b = false, transpose_a = false, transpose_b = false}> : (tensor<4x5xf32>, tensor<5x6xf32>) -> tensor<4x6xf32>

// optional arguments arg2 through arg5 depending on option. It returns a
// non-negative integer that is returned by the prctl syscall.
func PrctlRetInt(option int, arg2 uintptr, arg3 uintptr, arg4 uintptr, arg5 uintptr) (int, error) {
	ret, _, err := Syscall6(SYS_PRCTL, uintptr(option), uintptr(arg2), uintptr(arg3), uintptr(arg4), uintptr(arg5), 0)
	if err != 0 {
		return 0, err
	}