func.func @multiple_func_body_ops() {
  tf_executor.graph {
    tf_executor.island {
      "tf.NoOp"() : () -> ()
      tf_executor.yield
    }
    tf_executor.fetch
  }
  tf_executor.graph {
    tf_executor.island {
      "tf.NoOp"() : () -> ()
      tf_executor.yield
    }
    tf_executor.fetch
  }
  func.return
}

// -----

   * specified, may re-sleep or yield until time elapses.
   */
  static void delay(long millis) throws InterruptedException {
    long startTime = System.nanoTime();
    long ns = millis * 1000 * 1000;
    for (; ; ) {
      if (millis > 0L) Thread.sleep(millis);
      else // too short to sleep
      Thread.yield();
      long d = ns - (System.nanoTime() - startTime);

   * specified, may re-sleep or yield until time elapses.
   */
  static void delay(long millis) throws InterruptedException {
    long startTime = System.nanoTime();
    long ns = millis * 1000 * 1000;
    for (; ; ) {
      if (millis > 0L) Thread.sleep(millis);
      else // too short to sleep
      Thread.yield();
      long d = ns - (System.nanoTime() - startTime);

  ^bb0(%carg0: tensor<?x!tf_type.qint8>):
    %check = "tf.Equal"(%arg1, %one) : (tensor<i32>, tensor<i32>) -> tensor<i1>
    "tf.Yield"(%check) : (tensor<i1>) -> ()
    }, {
  ^bb0(%barg0: tensor<?x!tf_type.qint8>):
    %id = "tf.Identity"(%barg0) : (tensor<?x!tf_type.qint8>) -> tensor<?x!tf_type.qint8>
    "tf.Yield"(%id) : (tensor<?x!tf_type.qint8>) -> ()
  }) {is_stateless = false} : (tensor<?x!tf_type.qint8>) -> tensor<?x!tf_type.qint8>

    %4 = "tf.LayerNorm"(%a1, %a2, %a3, %a4) {_tfl_quant_trait = "fully_quantizable", device = ""} : (tensor<128x128xf32>, tensor<1xf32>, tensor<1xf32>, tensor<1xi32>) -> tensor<128x128xf32>
   "tfl.yield"(%4) : (tensor<128x128xf32>) -> ()
  }) {_tfl_quant_trait = "fully_quantizable", device = ""} : (tensor<128x128xf32>, tensor<1xf32>, tensor<1xf32>, tensor<1xi32>) -> tensor<128x128xf32>

  %0 = tf_executor.graph {
    %1:2 = tf_executor.island {
      %3 = "tf.opA"(%arg0) : (tensor<i1>) -> tensor<i1>
      tf_executor.yield %3 : tensor<i1>
    }
    %2:2 = tf_executor.island(%1#1) {
      %4 = "tf.opB"() : () -> tensor<f32>
      tf_executor.yield %4 : tensor<f32>
    }

// CHECK: "tf.opA"
// CHECK: tf_executor.island
// CHECK: "tf.opB"

    tf_executor.fetch %2#0 : tensor<f32>
  }

}

// Verifies that tf.Yield op which has no result and is not side effecting is
// preserved.
//
// CHECK-LABEL: func @yieldOp
func.func @yieldOp(%arg0: tensor<f32>, %arg1: tensor<f32>, %arg2: tensor<i1>) -> (tensor<f32>) {
  // CHECK-COUNT-2: tf.Yield
  %0 = "tf.IfRegion"(%arg2) ({
      "tf.Yield"(%arg0) : (tensor<f32>) -> ()
    }, {
      "tf.Yield"(%arg1) : (tensor<f32>) -> ()

    from docs_src.sql_databases.sql_app import alt_main

    # Ensure import side effects are re-executed
    importlib.reload(alt_main)

    with TestClient(alt_main.app) as c:
        yield c
    if test_db.is_file():  # pragma: nocover
        test_db.unlink()


# TODO: pv2 add version with Pydantic v2
@needs_pydanticv1
def test_create_user(client):

    from docs_src.sql_databases.sql_app_py39 import alt_main

    # Ensure import side effects are re-executed
    importlib.reload(alt_main)

    with TestClient(alt_main.app) as c:
        yield c
    if test_db.is_file():  # pragma: nocover
        test_db.unlink()
    os.chdir(cwd)


@needs_py39
# TODO: pv2 add version with Pydantic v2
@needs_pydanticv1
def test_create_user(client):

    from docs_src.sql_databases.sql_app_py310 import main

    # Ensure import side effects are re-executed
    importlib.reload(main)
    with TestClient(main.app) as c:
        yield c
    if test_db.is_file():  # pragma: nocover
        test_db.unlink()
    os.chdir(cwd)


@needs_py310
# TODO: pv2 add version with Pydantic v2
@needs_pydanticv1
def test_create_user(client):