[mlir][sparse] add init sparse tensor operation

This is the first step towards supporting general sparse tensors as output
of operations. The init sparse tensor is used to materialize an empty sparse
tensor of given shape and sparsity into a subsequent computation (similar to
the dense tensor init operation counterpart).

Example:
  %c = sparse_tensor.init %d1, %d2 : tensor<?x?xf32, #SparseMatrix>
  %0 = linalg.matmul
    ins(%a, %b: tensor<?x?xf32>, tensor<?x?xf32>)
    outs(%c: tensor<?x?xf32, #SparseMatrix>) -> tensor<?x?xf32, #SparseMatrix>

Reviewed By: bixia

Differential Revision: https://reviews.llvm.org/D111684