%conv = "tfl.conv_2d"(%arg0, %w, %b) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 2 : i32, stride_w = 2 : i32} : (tensor<1x224x224x3xf32>, tensor<64x3x3x3xf32>, tensor<64xf32>) -> tensor<1x112x112x64xf32>

module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 1399 : i32}} {

// CHECK-LABEL: stateless_op
func.func @stateless_op() -> tensor<i32> {
  // CHECK: %cst = "tf.Const"() <{value = dense<1> : tensor<i32>}> : () -> tensor<i32>
  %0 = "tf.StatelessRandomGetAlg"() {device = ""} : () -> tensor<i32>
  return %0 : tensor<i32>
}

    },
    {
      // loop body
      ^bb0(%barg0: tensor<i32>, %barg1: tensor<i32>):
      %one = arith.constant dense<1> : tensor<i32>
      %sub0 = "tf.Sub"(%barg0, %one) : (tensor<i32>, tensor<i32>) -> tensor<i32>
      %sub1 = "tf.Sub"(%barg1, %one) : (tensor<i32>, tensor<i32>) -> tensor<i32>
      "tf.Yield"(%sub0, %sub1) : (tensor<i32>, tensor<i32>) -> ()
    }

  {
    %cst = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
    %0 = "tf.AddV2"(%arg2, %cst) {device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>
    %1 = "tf.Identity"(%0) {device = ""} : (tensor<i32>) -> tensor<i32>

    %cst = "tf.Const"() <{value = dense<0> : tensor<i32>}> : () -> tensor<i32>
    %11:4 = "tf.Split"(%cst, %0) {num_split = 4 : i32} : (tensor<i32>, tensor<128x1024xf32>) -> (tensor<32x1024xf32>, tensor<32x1024xf32>, tensor<32x1024xf32>, tensor<32x1024xf32>)
    %cst_0 = "tf.Const"() <{value = dense<0> : tensor<i32>}> : () -> tensor<i32>

    ^bb0 (%carg0: tensor<!tf_type.resource>, %carg1: tensor<i32>):
    %pred = "tf._SomeOp"(%carg1) : (tensor<i32>) -> tensor<i1>
    "tf.Yield"(%pred) : (tensor<i1>) -> ()
  }, {
    ^bb0 (%carg0: tensor<!tf_type.resource>, %carg1: tensor<i32>):
    %const1 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
    %sub = "tf.Sub"(%carg1, %const1) : (tensor<i32>, tensor<i32>) -> tensor<i32>

^bb0(%arg0: tensor<256x32x32x3xf32>, %arg1: tensor<16x3x3x3xf32>, %arg2: tensor<16xf32>):
  // CHECK: tac.cost = 0x4D5C0000
  %0 = "tfl.conv_2d"(%arg0, %arg1, %arg2) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32, fused_activation_function = "RELU6", tac.device = "CPU"} : (tensor<256x32x32x3xf32>, tensor<16x3x3x3xf32>, tensor<16xf32>) -> tensor<256x32x32x16xf32>
  func.return %0 : tensor<256x32x32x16xf32>

func.func @dead_island(%arg0 : i32) -> i32 {
// CHECK: tf_executor.island
// CHECK-NOT: tf_executor.island
  %0 = tf_executor.graph {
    %1:2 = tf_executor.island {
      %a = "tf.opA"(%arg0) : (i32) -> i32
      %b = "tf.opB"(%a) : (i32) -> i32
      tf_executor.yield %b : i32
    }
    %2:2 = tf_executor.island {
      %a = "tf.opA"(%1#0) : (i32) -> i32
      tf_executor.yield %a : i32
    }
    tf_executor.fetch %1#0 : i32

module attributes {tf.versions = {producer = 179 : i32}} {
  func.func @main() -> (tensor<300x?xf32>, tensor<300x?xf32>) {
    %elem_shape = "tf.Const"() {value = dense<-1> : tensor<i32>} : () -> tensor<i32>
    %size = "tf.Const"() {value = dense<300> : tensor<i32>} : () -> tensor<i32>
    %tl = "tf.TensorListReserve"(%elem_shape, %size) : (tensor<i32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<*xf32>>>

// CHECK: while_1([[ARG0:%[^ :]*]]: tensor<i32>, [[ARG1:%[^ :]*]]: tensor<1xf32>)
func.func @while_1(%arg0: tensor<i32>, %arg1: tensor<1xf32>) -> tensor<1xf32> {
  // CHECK: [[CST:%[^ ]*]] = arith.constant dense<1> : tensor<i32>
  // CHECK: "tfl.while"([[ARG0]], [[ARG1]])
  // CHECK: (tensor<i32>, tensor<1xf32>) -> (tensor<i32>, tensor<1xf32>)
  %0:2 = "tfl.while"(%arg0, %arg1) (
    // cond
    {