`validation_split` argument, for returning both dataset splits at once,
        as a tuple.
    *   Added `tf.keras.utils.split_dataset` utility to split a `Dataset` object
        or a list/tuple of arrays into two `Dataset` objects (e.g. train/test).
    *   Added step granularity to `BackupAndRestore` callback for handling
        distributed training failures & restarts. The training state can now be

the sparse tensors have been concatenated along new dimensions, one for each
batch.

The output `SparseTensor` object's shape values for the original dimensions
are the max across the input `SparseTensor` objects' shape values for the
corresponding dimensions. The new dimensions match the size of the batch.

The input `SparseTensor` objects' indices are assumed ordered in

                    - name
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        required:
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    storage: true
    subresources:
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---

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                type: object
            required:
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            type: object
          status:
            type: object
            x-kubernetes-preserve-unknown-fields: true
        required:
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        type: object
    served: true
    storage: true
    subresources:
      status: {}
---