The old Keras optimizer will never be deleted, but will not see any
    new feature additions.
    New optimizers (e.g., `Adafactor`) will
    only be implemented based on `tf.keras.optimizers.Optimizer`, the new
    base class.

## Major Features and Improvements

*   `tf.lite`:

    *   New operations supported:
          * tf.unsortedsegmentmin op is supported.

		},
	}
	for _, test := range tests {
		test.new.ObjectMeta.ResourceVersion = "1"
		test.old.ObjectMeta.ResourceVersion = "1"

		// set required fields if old and new match and have no opinion on the value
		if test.new.Name == "" && test.old.Name == "" {
			test.new.Name = "name"
			test.old.Name = "name"
		}
		if test.new.Namespace == "" && test.old.Namespace == "" {

            "type": "boolean"
          },
          "driverName": {

   ...

created, its rank is the rank of the incoming `SparseTensor` objects plus N;
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