// CHECK-SAME:    (%[[ARG0:.*]]: tensor<i32>)
func.func @identity(%arg0: tensor<i32>) -> tensor<i32> {
  // CHECK-NOT: "tf.Identity"
  %0 = "tf.Identity"(%arg0) : (tensor<i32>) -> tensor<i32>
  // CHECK: return %[[ARG0]]
  func.return %0 : tensor<i32>
}

// CHECK-LABEL: func @identity_terminator
// CHECK-SAME:    (%[[ARG0:.*]]: tensor<i32>)
func.func @identity_terminator(%arg0: tensor<i32>) -> (tensor<*xi32>, tensor<i32>) {

  %6 = "tf.Identity"(%1) : (tensor<!tf_type.int32ref>) -> tensor<i32>

  func.return %6 : tensor<i32>
}

// CHECK-LABEL: @inference
func.func @inference() -> (tensor<i32>, tensor<i32>, tensor<i32>) {
  // CHECK-NOT: tf.VariableV2

  // CHECK: [[handle:%.*]] = "tf.VarHandleOp"
  // CHECK-SAME: shared_name = "x"
  // CHECK: "tf.ReadVariableOp"([[handle]])

  %0:3 = "tfl.while"(%cst_0, %cst_1, %cst_2) (
    // cond
    {
    ^bb0(%arg0: tensor<f32>, %arg1: tensor<f32>, %arg2: tensor<i32>):
      %cst_3 = "arith.constant" () {value = dense<3> : tensor<i32>} : () -> tensor<i32>
      %1 = "tfl.less"(%arg2, %cst_3) : (tensor<i32>, tensor<i32>) -> tensor<i1>
      "tfl.yield"(%1) : (tensor<i1>) -> ()
    },
    // body
    {

  %2 = "tf.AddV2"(%y, %1) : (tensor<i32>, tensor<i32>) -> tensor<i32>
  func.return %1, %2 : tensor<i32>, tensor<i32>
}

func.func @no_side_effect_then_1(%x: tensor<i32>, %y: tensor<i32>) -> tensor<i32> {
  %0 = "tf.AddV2"(%x, %y) : (tensor<i32>, tensor<i32>) -> tensor<i32>
  func.return %0 : tensor<i32>
}

func.func @no_side_effect_else_1(%x: tensor<i32>, %y: tensor<i32>) -> tensor<i32> {

// 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: "tf.WhileRegion"([[ARG0]], [[ARG1]])
  // CHECK: (tensor<i32>, tensor<1xf32>) -> (tensor<i32>, tensor<1xf32>)
  %0:2 = "tf.WhileRegion"(%arg0, %arg1) (
    // cond
    {

func.func @listReserveScalarShapeI32(%arg0: tensor<i32>, %arg1: tensor<i32>) -> tensor<!tf_type.variant<tensor<*xi32>>> {
  %0 = "tf.TensorListReserve"(%arg0, %arg1) : (tensor<i32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<*xi32>>>
  // CHECK: %0 = "tfl.custom"(%arg0, %arg1) <{custom_code = "TensorListReserve", custom_option = #tfl<const_bytes : "0x02">}> : (tensor<i32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<*xi32>>>

    tf_device.return %1 : tensor<i32>
  }) {cluster_attr = "cluster_attr"} : () -> tensor<i32>
  %2 = "tf.Const"() {value = dense<5> : tensor<i32>} : () -> tensor<i32>
  %3 = "tf.Add"(%2, %0) : (tensor<i32>, tensor<i32>) -> tensor<i32>
  func.return %3 : tensor<i32>
}

// -----

// CHECK-LABEL: func @multi_return_values_in_cluster_op

  func.return %0#2, %0#3, %0#4 : tensor<i32>, tensor<256x256xf32>, tensor<?x256x256xf32>
}

    %2 = "tf.AddV2"(%arg0, %arg1) : (tensor<i32>, tensor<i32>) -> tensor<i32>
    // CHECK: %[[SUB:.*]] = "tf.Sub"
    %3 = "tf.Sub"(%arg0, %arg1) : (tensor<i32>, tensor<i32>) -> tensor<i32>
    // CHECK: tf_device.return %arg0, %[[ADD]], %[[MUL]], %[[SUB]]
    tf_device.return %arg0, %2, %0, %3 : tensor<i32>, tensor<i32>, tensor<i32>, tensor<i32>
  }) : () -> (tensor<i32>, tensor<i32>, tensor<i32>, tensor<i32>)

    %Enter, %ctl_0 = Enter(%Const) [%arg.ctl] name("while/Enter") {T = i32, frame_name = "while/while_context", is_constant = false, parallel_iterations = 10 : i64} : (tensor<i32>) -> (tensor<*xi32>)
    %NextIteration, %ctl_1 = NextIteration(%Const) [%arg.ctl] name("while/NextIteration") {T = i32} : (tensor<i32>) -> (tensor<*xi32>)