func.func @simple_independent_chains(%arg0: !tf_res, %arg1: !tf_res, %arg2: tensor<f32>) {
  // CHECK: tf_executor.graph {
  tf_executor.graph {
    // CHECK: %[[A_CONTROL:.*]] = tf_executor.island wraps "tf.OpA"() : () -> ()
    %control_A = tf_executor.island wraps "tf.OpA"() : () -> ()
    // CHECK: %[[CHAIN_CONSTANT:.*]], %{{.*}} = tf_executor.island wraps "tf.Const"() <{value = dense<1> : tensor<i32>}> : () -> tensor<i32>

```
### `-tf-executor-to-functional-conversion`

_Lifts tf_executor.island inner ops from a tf_executor.graph_

This pass converts tf_executor.graphs consisting of only tf_executor.islands and
a tf_executor.fetch into a sea of nodes consisting of TensorFlow Dialect ops by
lifting such ops out of a tf_executor.graph's tf_executor.islands. If V1 control
flow ops are present in a tf_executor.graph, an error will be returned.

    TFE_Execute(matmul, &retvals[0], &num_retvals, status);
    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
    if (state.iterations() >= state.max_iterations && async) {
      TFE_Executor* executor = TFE_ContextGetExecutorForThread(ctx);
      TFE_ExecutorWaitForAllPendingNodes(executor, status);
      ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
      TFE_DeleteExecutor(executor);
    }