*   tf.data service now supports auto-sharding. Users specify the sharding
        policy with `tf.data.experimental.service.ShardingPolicy` enum. It can
        be one of `OFF` (equivalent to today's `"parallel_epochs"` mode),
        `DYNAMIC` (equivalent to today's `"distributed_epoch"` mode), or one of
        the static sharding policies: `FILE`, `DATA`, `FILE_OR_DATA`, or `HINT`

External declarations for constants GLOBL p256ord<>(SB), 8, $32 GLOBL p256<>(SB), 8, $80 GLOBL p256mul<>(SB), 8, $160 // The following macros are used to implement the ppc64le // equivalent function from the corresponding s390x // instruction for vector multiply high, low, and add, // since there aren't exact equivalent instructions. // The corresponding s390x instructions appear in the // comments. // Implementation for big endian would have to be // investigated, I think it would be different....

External declarations for constants GLOBL p256ord<>(SB), 8, $32 GLOBL p256<>(SB), 8, $80 GLOBL p256mul<>(SB), 8, $160 // The following macros are used to implement the ppc64le // equivalent function from the corresponding s390x // instruction for vector multiply high, low, and add, // since there aren't exact equivalent instructions. // The corresponding s390x instructions appear in the // comments. // Implementation for big endian would have to be // investigated, I think it would be different....

* Improve handling of custom classes for `Request`s and `APIRoute`s.
    * This helps to more easily solve use cases like:
        * Reading a body before and/or after a request (equivalent to a middleware).
        * Run middleware-like code only for a subset of *path operations*.
        * Process a request before passing it to a *path operation function*. E.g. decompressing, deserializing, etc.