AUTHORS OR CONTRIBUTORS BE // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR // BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, // WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE // OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, // EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. //...

AUTHORS OR CONTRIBUTORS BE // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR // BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, // WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE // OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, // EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. //...

        to handle worker preemption/maintenance and cluster-wise consistent
        error reporting for `tf.distribute.MultiWorkerMirroredStrategy`.
        Specifically, for the type of interruption with advance notice, it
        automatically saves a checkpoint, exits the program without raising an
        unrecoverable error, and restores the progress when training restarts.

*   `tf.math`: