}

// CHECK-LABEL: func @main
func.func @main(%arg0: tensor<1x3xf32>) -> tensor<*xf32> {
  // CHECK:  "tf.BatchFunction"
  // CHECK-SAME: allowed_batch_sizes = [6]
  // CHECK-SAME: batch_timeout_micros = 100000 : i64
  // CHECK-SAME: batching_queue = ""
  // CHECK-SAME: container = ""
  // CHECK-SAME: enable_large_batch_splitting = false
  // CHECK-SAME: max_batch_size = 6 : i64

  // CHECK: [[y_future:%.*]] = tf_mlrt.batch_function
  // CHECK-SAME: f = @batched_function
  // CHECK-SAME: \22batch_function\22
  %y = "tf.BatchFunction"(%x) {
    allowed_batch_sizes = [6], batch_timeout_micros = 100000 : i64,
    batching_queue = "", container = "", device = "/device:CPU:0",
    enable_large_batch_splitting = false, f = @batched_function,
    max_batch_size = 6 : i64, max_enqueued_batches = 10 : i64,

          captured_tensors=computation.captured_inputs,
          Tout=[o.type for o in computation.definition.signature.output_arg],
          num_batch_threads=1,
          max_batch_size=10,
          batch_timeout_micros=100000,  # 100ms
          allowed_batch_sizes=[3, 10],
          batching_queue="")
  ```

If more than one session.run call is simultaneously trying to compute `b`