available, along with experimental support for multi worker and Cloud TPUs.
    Check out the
    [guide](https://www.tensorflow.org/beta/guide/distribute_strategy) for more
    details.
*   Functions, not Sessions. The traditional declarative programming model of
    building a graph and executing it via a `tf.Session` is discouraged, and
    replaced with by writing regular Python functions. Using the `tf.function`

* Update [SQL Tutorial](https://fastapi.tiangolo.com/tutorial/sql-databases/#create-a-middleware-to-handle-sessions) to close database sessions even when there are exceptions. PR [#89](https://github.com/tiangolo/fastapi/pull/89) by [@alexiri](https://github.com/alexiri).

from the value obtained by executing and rounding the instructions individually.
An explicit <a href="#Numeric_types">floating-point type</a> <a href="#Conversions">conversion</a> rounds to
the precision of the target type, preventing fusion that would discard that rounding.
</p>

<p>
For instance, some architectures provide a "fused multiply and add" (FMA) instruction