is available everywhere in the cluster and has infinite capacity. Topology constraints addressed the first point, but up to now pod scheduling was still done without considering that the remaining storage capacity may not be enough to start a new pod. [Storage capacity tracking](https://github.com/kubernetes/enhancements/tree/master/keps/sig-storage/1472-storage-capacity-tracking), a new alpha feature, addresses that by adding an API for a CSI driver to report storage capacity and uses that information...

        (corresponding to values of `tf.data.experimental.AutoShardPolicy`).

        Static sharding (auto-sharding) requires the number of tf.data service
        workers be fixed. Users need to specify the worker addresses in
        `tensorflow.data.experimental.DispatcherConfig`.

    *   `tf.data.experimental.service.register_dataset` now accepts optional
        `compression` argument.

*   Keras:

20F1..20FF    ; disallowed                             # NA   <reserved-20F1>..<reserved-20FF>
2100          ; disallowed_STD3_mapped ; 0061 002F 0063 #1.1  ACCOUNT OF
2101          ; disallowed_STD3_mapped ; 0061 002F 0073 #1.1  ADDRESSED TO THE SUBJECT
2102          ; mapped                 ; 0063          # 1.1  DOUBLE-STRUCK CAPITAL C
2103          ; mapped                 ; 00B0 0063     # 1.1  DEGREE CELSIUS