%cst_1 = "tf.Const"() <{value = dense<"y"> : tensor<1x!tf_type.string>}> : () -> tensor<1x!tf_type.string>
    %0 = "tf.RestoreV2"(%cst, %cst_1, %cst_0): (tensor<!tf_type.string>, tensor<1x!tf_type.string>, tensor<1x!tf_type.string>) -> tensor<3x1xf32>
    %1 = "tf.VarHandleOp"() <{container = "", shared_name = "y"}> : () -> tensor<!tf_type.resource<tensor<3x1xf32>>>

  %3 = "tf.Const"() {value = dense<"y (WhitespaceTokenize/RaggedConcat/RaggedNRows/Const:0) = "> : tensor<!tf_type.string>} : () -> tensor<!tf_type.string>
  "tf.Assert"(%arg0, %0, %1, %2, %arg1, %3, %arg2) {device = "", summarize = 3 : i64} : (tensor<i1>, tensor<!tf_type.string>, tensor<!tf_type.string>, tensor<!tf_type.string>, tensor<i64>, tensor<!tf_type.string>, tensor<i64>) -> ()

    %1 = "tf.LookupTableFindV2"(%0, %arg0, %cst) {device = ""} : (tensor<!tf_type.resource>, tensor<i64>, tensor<!tf_type.string>) -> tensor<*x!tf_type.string>
    func.return %1 : tensor<*x!tf_type.string>
    // CHECK-LABEL: @serving_default
    // CHECK: "tfl.call_once"() <{session_init_function = "init_all_tables"}> : () -> ()

  // CHECK-NEXT:  return [[FIND]] : tensor<*x!tf_type.string>
  func.return %1 : tensor<*x!tf_type.string>
}

// -----

// Test for case with unsupported string -> string mapping.
func.func @no_legalization_on_hashtable_string_to_string(%arg0: tensor<!tf_type.string>) {

func.func @variantAddN(%arg0: tensor<!tf_type.variant<tensor<*xi32>>>, %arg1: tensor<!tf_type.variant<tensor<*xi32>>>) -> tensor<!tf_type.variant<tensor<*xi32>>> {
  %1 = "tf.AddN"(%arg0, %arg1) : (tensor<!tf_type.variant<tensor<*xi32>>>, tensor<!tf_type.variant<tensor<*xi32>>>) -> tensor<!tf_type.variant<tensor<*xi32>>>

  } : (tensor<3x2x!tf_type.qint32>, tensor<3x2x!tf_type.qint32>, tensor<3x2x!tf_type.qint32>, tensor<2xf32>, tensor<2xi32>) -> tensor<3x2x!tf_type.qint32>
  func.return %1 : tensor<3x2x!tf_type.qint32>
}

// -----

// CHECK-LABEL: func @uniform_quantized_clip_by_value_min_not_const

  %output_0 = "tf.TensorArrayGatherV3"(%handle_1, %indices, %res_0#3) {device = "/job:localhost/replica:0/task:0/device:CPU:0", element_shape = #tf_type.shape<?x512>} : (tensor<2x!tf_type.resource<tensor<?x512xf32>>>,...

  %1 = "tf.MultiDeviceIteratorGetNextFromShard"(%0, %cst, %arg1) {device = ""} : (tensor<!tf_type.resource>, tensor<i32>, tensor<i64>) -> tensor<!tf_type.string>
  %2 = "tf.Identity"(%1) {device = ""} : (tensor<!tf_type.string>) -> tensor<!tf_type.string>
  return %2 : tensor<!tf_type.string>
}

//...

    %1 = "tf.EmptyTensorList"(%elem_shape, %max_size) { _xla_outside_compilation="0" } : (tensor<0xi32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<f32>>>
    %2 = "tf.Identity"(%1) : (tensor<!tf_type.variant<tensor<f32>>>) -> (tensor<!tf_type.variant<tensor<f32>>>)
    "tf.Identity"(%2) : (tensor<!tf_type.variant<tensor<f32>>>) -> (tensor<!tf_type.variant<tensor<f32>>>)
    tf_device.return
  }) {cluster_attr = "cluster_attr"} : () -> ()
  func.return
}