%0:1 = "tfl.while"(%arg0, %arg1) ({
  ^bb0(%arg2: tensor<*xi32>, %arg3: tensor<*xf32>):
    %1 = func.call @WhileOp_cond(%arg2, %arg3) : (tensor<*xi32>, tensor<*xf32>) -> tensor<i1>
    "tfl.yield"(%1) : (tensor<i1>) -> ()
  },  {
  ^bb0(%arg2: tensor<*xi32>, %arg3: tensor<*xf32>):
    %1:2 = func.call @WhileOp_body(%arg2, %arg3) : (tensor<*xi32>, tensor<*xf32>) -> (tensor<*xi32>, tensor<*xf32>)

func.func @select(%arg0: tensor<8xi1>, %arg1: tensor<8xf32>, %arg2: tensor<8xf32>) -> tensor<8xf32> {
  %0 = "tf.Select"(%arg0, %arg1, %arg2) : (tensor<8xi1>, tensor<8xf32>, tensor<8xf32>) -> tensor<8xf32>
  func.return %0: tensor<8xf32>

// CHECK-LABEL: select
// CHECK:  "tfl.select"(%arg0, %arg1, %arg2)
// CHECK:  return
}

func.func @select_multidim(%arg0: tensor<8xi1>, %arg1: tensor<8x3xf32>, %arg2: tensor<8x3xf32>) -> tensor<8x3xf32> {

      "tf.Yield"(%arg1, %arg2, %true_value, %arg2) : (tensor<f32>, tensor<!tf_type.resource>, tensor<f32>, tensor<!tf_type.resource>) -> ()
    }, {
      %false_value = "tf.Sub"(%arg0, %arg1) : (tensor<f32>, tensor<f32>) -> tensor<f32>
      "tf.Yield"(%arg1, %arg2, %false_value, %arg2) : (tensor<f32>, tensor<!tf_type.resource>, tensor<f32>, tensor<!tf_type.resource>) -> ()

		// unsigned arg0 >> arg2, shifting in bits from arg1 (==(arg1<<64+arg0)>>arg2, keeping low 64 bits), shift amount is mod 64
		{name: "SHRDQ", argLength: 3, reg: gp31shift, asm: "SHRQ", resultInArg0: true, clobberFlags: true},
		// unsigned arg0 << arg2, shifting in bits from arg1 (==(arg0<<64+arg1)<<arg2, keeping high 64 bits), shift amount is mod 64

func p521Selectznz(out1 *[9]uint64, arg1 p521Uint1, arg2 *[9]uint64, arg3 *[9]uint64) {
	var x1 uint64
	p521CmovznzU64(&x1, arg1, arg2[0], arg3[0])
	var x2 uint64
	p521CmovznzU64(&x2, arg1, arg2[1], arg3[1])
	var x3 uint64
	p521CmovznzU64(&x3, arg1, arg2[2], arg3[2])
	var x4 uint64
	p521CmovznzU64(&x4, arg1, arg2[3], arg3[3])
	var x5 uint64
	p521CmovznzU64(&x5, arg1, arg2[4], arg3[4])
	var x6 uint64

  %r3 = "tf.Reshape"(%arg2, %shape1) : (tensor<10000xf32>, tensor<2xi32>) -> tensor<100x100xf32>
  %shape3 = arith.constant dense<[-1, 100]> : tensor<2xi32>
  %r4 = "tf.Reshape"(%arg2, %shape3) : (tensor<10000xf32>, tensor<2xi32>) -> tensor<100x100xf32>
  %r5 = "tf.Reshape"(%arg0, %arg3) : (tensor<*xf32>, tensor<*xi32>) -> tensor<*xf32>
  %r6 = "tf.Reshape"(%arg2, %arg3) : (tensor<10000xf32>, tensor<*xi32>) -> tensor<*xf32>

  %4 = "tf.Add"(%2, %arg2) : (tensor<?x8x10xf32>, tensor<8x10xf32>) -> tensor<?x8x10xf32>
  %5 = "tf.Add"(%arg1, %arg2) : (tensor<8x10xf32>, tensor<8x10xf32>) -> tensor<8x10xf32>
  %6 = "tf.Const"() {_output_shapes = ["tfshape$"], device = "/device:CPU:0", dtype = f32, value = dense<1.000000e+00> : tensor<f32>} : () -> tensor<f32>
  %7 = "tf.Add"(%arg1, %arg2) : (tensor<8x10xf32>, tensor<8x10xf32>) -> tensor<8x10xf32>

        %assign_1_control = tf_executor.island(%chain_1_src) wraps "tf.AssignVariableOp"(%arg1, %arg3) : (!tf_res, tensor<f32>) -> ()
        %add_out, %add_control = tf_executor.island wraps "tf.Add"(%arg2, %arg3) : (tensor<f32>, tensor<f32>) -> tensor<f32>
        %mul_out, %mul_control = tf_executor.island wraps "tf.Mul"(%arg2, %arg3) : (tensor<f32>, tensor<f32>) -> tensor<f32>

  func.func @passthrough_mapdataset(
      %arg0 : tensor<!tf_type.variant>,
      %arg1 : tensor<!tf_type.resource>,
      %arg2 : tensor<i64>,
      %arg3 : tensor<10xi32>) {
    %74 = "tf.ParallelMapDatasetV2"(%arg0, %arg1, %arg2, %arg2) {
      Targuments = [!tf_type.resource, i64], deterministic = "default",
      device = "/job:localhost/replica:0/task:0/device:CPU:0",

        // expected-remark@above {{ID: 7}}
        // expected-remark@above {{Successors: {8}}}
        // expected-remark@above {{Predecessors: {3}}}