[mlir][sparse][bufferization] initialize reduction variable

[aartbik]

Summary

After recent bufferization improvement, this test
started failing due to missed zero initialization.

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dot.mlir

func.func @entry() {
     > : tensor<1024xf32>
     %s1 = sparse_tensor.convert %d1 : tensor<1024xf32> to tensor<1024xf32, #SparseVector>
     %s2 = sparse_tensor.convert %d2 : tensor<1024xf32> to tensor<1024xf32, #SparseVector>
 
     // Call the kernel and verify the output.
     //
     // CHECK: 53
     //
-    %x = bufferization.alloc_tensor() : tensor<f32>
+    %t = bufferization.alloc_tensor() : tensor<f32>
+    %z = arith.constant 0.0 : f32
+    %x = tensor.insert %z into %t[] : tensor<f32>
     %0 = call @sparse_dot(%s1, %s2, %x) : (tensor<1024xf32, #SparseVector>,
                                            tensor<1024xf32, #SparseVector>,
                                            tensor<f32>) -> tensor<f32>
     %1 = tensor.extract %0[] : tensor<f32>
     vector.print %1 : f32
 
     // Release the resources.
     sparse_tensor.release %s1 : tensor<1024xf32, #SparseVector>
     sparse_tensor.release %s2 : tensor<1024xf32, #SparseVector>
 
     return
   }
 }