1.  Address the perceived conflict directly with those involved, preferably in a
    real-time medium.
2.  If this fails, get a third party (e.g. a mutual friend, and/or someone with
    background on the issue, but not involved in the conflict) to intercede.
3.  If you are still unable to resolve the conflict, and you believe it rises to
    harassment or another code of conduct violation, report it.

    *   Added `ignore_class` argument in the loss
        `SparseCategoricalCrossentropy` and metrics `IoU` and `MeanIoU`, to
        specify a class index to be ignored during loss/metric computation (e.g.
        a background/void class).
    *   Added
        [`tf.keras.models.experimental.SharpnessAwareMinimization`](https://www.tensorflow.org/api_docs/python/tf/keras/models/experimental/SharpnessAwareMinimization).