DeserializeSparse

Deserialize `SparseTensor` objects.

The input `serialized_sparse` must have the shape `[?, ?, ..., ?, 3]` where the last dimension stores serialized `SparseTensor` objects and the other N dimensions (N >= 0) correspond to a batch. The ranks of the original `SparseTensor` objects must all match. When the final `SparseTensor` is 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 standard lexicographic order. If this is not the case, after this step run `SparseReorder` to restore index ordering.

For example, if the serialized input is a `[2 x 3]` matrix representing two original `SparseTensor` objects:

index = [ 0] [10] [20] values = [1, 2, 3] shape = [50]

and

index = [ 2] [10] values = [4, 5] shape = [30]

then the final deserialized `SparseTensor` will be:

index = [0 0] [0 10] [0 20] [1 2] [1 10] values = [1, 2, 3, 4, 5] shape = [2 50]