The key here is the `await`. It tells Python that it has to wait ⏸ for `get_burgers(2)` to finish doing its thing 🕙 before storing the results in `burgers`. With that, Python will know that it can go and do something else 🔀 ⏯ in the meanwhile (like receiving another request).

For `await` to work, it has to be inside a function that supports this asynchronicity. To do that, you just declare it with `async def`:

```Python hl_lines="1"

            of this change, please inform us (file an issue) about your use case
            and you can unblock yourself by setting
            `experimental_run_tf_function=False` in compile meanwhile. We have
            seen couple of use cases where the model usage pattern is not as
            expected and would not work with this change.
    *   output tensors of one layer is used in the constructor of another.