func.func @main() -> (tensor<1xi32>, tensor<1xi32>) {
  %0, %1 = tf_executor.graph {
    %output_1, %token_1, %control_1 = tf_executor.NextIteration.Source : tensor<1xi32> {T = i32, device = ""}
    %output_2, %token_2, %control_2 = tf_executor.NextIteration.Source : tensor<1xi32> {T = i32, device = ""}
    tf_executor.NextIteration.Sink [%token_1] %output_1 : tensor<1xi32> {T = i32, device = ""}

// RUN: tf-opt %s -tfl-legalize-tf='preserve-assert-op=true' | FileCheck %s --dump-input=fail

func.func @preserve_assert(%arg0: tensor<1xi32>, %arg1: tensor<1xi32>) -> tensor<1xi1> {
  %0 = "tf.LessEqual"(%arg0, %arg1) : (tensor<1xi32>, tensor<1xi32>) -> tensor<1xi1>
  "tf.Assert"(%0, %arg1) {summarize = 3} : (tensor<1xi1>, tensor<1xi32>) -> ()
  func.return %0 : tensor<1xi1>
  // CHECK-LABEL: preserve_assert
  // CHECK: tfl.less_equal
  // CHECK: Assert

      %outputs_45, %control_46 = tf_executor.island wraps "tf.Const"() {device = "/device:CPU:0", value = dense<3> : tensor<1xi32>} : () -> tensor<1xi32>
      %outputs_47, %control_48 = tf_executor.island wraps "tf.Const"() {device = "/device:CPU:0", value = dense<1> : tensor<1xi32>} : () -> tensor<1xi32>

        %add = "tf.AddV2"(%cst, %cst) : (tensor<2xf32>, tensor<2xf32>) -> tensor<2xf32>
        %var_handle = "tf.VarHandleOp"() {container = "", device = "/device:CPU:0", shared_name = "var_0"} : () -> tensor<!tf_type.resource<tensor<2xf32>>>
        "tf.AssignVariableOp"(%var_handle, %add) : (tensor<!tf_type.resource<tensor<2xf32>>>, tensor<2xf32>) -> ()
        return
      }
    }

    %2 = "tf.MatMul"(%arg2, %arg1) {} : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
    %3 = "tf.AddV2" (%arg1, %arg1)  : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
    %4 = "tf.Identity"(%1) {device = ""} : (tensor<i32>) -> tensor<i32>
    %5 = "tf.Identity"(%3) {device = ""} : (tensor<*xf32>) -> tensor<*xf32>
    %6 = "tf.Identity"(%2) {device = ""} : (tensor<*xf32>) -> tensor<*xf32>

    %tl_set_item = "tf.TensorListSetItem"(%tl, %idx, %elem_1) : (tensor<!tf_type.variant<tensor<*xf32>>>, tensor<i32>, tensor<8xf32>) -> tensor<!tf_type.variant<tensor<*xf32>>>
    %elem_shape_2 = "tf.Const"() {value = dense<-1> : tensor<1xi32>} : () -> tensor<1xi32>

  %0 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
  %1 = "tfl.svdf"(%arg0, %arg1, %arg2, %arg3, %0) {fused_activation_function = "RELU", rank = 2 : i32} : (tensor<4xf32>, tensor<4xi8>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>
  func.return %1 : tensor<4xf32>

  %1 = "tfl.unidirectional_sequence_rnn"(%arg0, %arg1, %arg2, %arg3, %0) {fused_activation_function = "TANH", time_major = true} : (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>, tensor<4x4xf32>) -> tensor<4xf32>
  func.return %1 : tensor<4xf32>

    %1 = "tf.BiasAdd"(%0, %arg2) {data_format = "NHWC", device = ""} : (tensor<*xf32>, tensor<2xf32>) -> tensor<*xf32>
    %2 = "tf.Relu6"(%1) : (tensor<*xf32>) -> tensor<*xf32>
    func.return %2 : tensor<*xf32>
  }

// CHECK-LABEL: func @conv_with_default_attributes

func.func @transpose_simple_1d() -> tensor<2xf32> {
  %0 = stablehlo.constant dense<[0.000000e+0, 1.000000e+0]> : tensor<2xf32>
  %1 = stablehlo.transpose %0, dims = [0] : (tensor<2xf32>) -> tensor<2xf32>
  return %1 : tensor<2xf32>
}
// CHECK-DAG: %[[CONST_0:.+]] = stablehlo.constant dense<[0.000000e+00, 1.000000e+00]> : tensor<2xf32>
// CHECK-NOT: transpose
// CHECK: return %[[CONST_0]] : tensor<2xf32>

// -----