[mlir][sparse][bufferization] fix doc on new init operation

[aartbik]

Summary

The example was still using the -now- removed sparse_tensor.init_tensor.
Also, I made the input operands of the matrix multiplication sparse too
(since it looks a bit strange to multiply two dense matrices into a sparse).

mlir/include/mlir/Dialect/Bufferization/IR/BufferizationOps.td

let description = [{
     another op.
 
     Both dense and sparse tensor types are supported. The result of a
     `bufferization.alloc_tensor` is a tensor value that can be used like any
     other tensor value. In practice, it is often used as the "out" operand of
     another op. E.g.:
 
     ```mlir
-    %c = sparse_tensor.init_tensor [%d1, %d2] : tensor<?x?xf32, #SparseMatrix>
+    %c = bufferization.alloc_tensor [%d1, %d2] : tensor<?x?xf32, #SparseMatrix>
     %0 = linalg.matmul
-      ins(%a, %b: tensor<?x?xf32>, tensor<?x?xf32>)
+      ins(%a, %b: tensor<?x?xf32, #SparseMatrix>, tensor<?x?xf32, #SparseMatrix>)
       outs(%c: tensor<?x?xf32, #SparseMatrix>) -> tensor<?x?xf32, #SparseMatrix>
     ```
   }];
 
   let arguments = (ins Variadic<Index>:$dynamicSizes);
 
   let results = (outs AnyTensor:$result);