[mli][sparse] Remove manual dense dealloc from test case

[springerm]

Summary

aartbik

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

#DCSR = #sparse_tensor.encoding<{
   dimLevelType = [ "compressed", "compressed" ],
   dimOrdering = affine_map<(i,j) -> (i,j)>
 }>
 
 module {
   //
   // Computes C = A x B with all matrices dense.
   //
-  func.func @matmul1(%A: tensor<4x8xf64>,
-                %B: tensor<8x4xf64>) -> tensor<4x4xf64> {
-    %C = arith.constant dense<0.0> : tensor<4x4xf64>
+  func.func @matmul1(%A: tensor<4x8xf64>, %B: tensor<8x4xf64>,
+                     %C: tensor<4x4xf64>) -> tensor<4x4xf64> {
     %D = linalg.matmul
       ins(%A, %B: tensor<4x8xf64>, tensor<8x4xf64>)
-         outs(%C: tensor<4x4xf64>) -> tensor<4x4xf64>
     return %D: tensor<4x4xf64>
   }
 
   //
   // Computes C = A x B with all matrices sparse (SpMSpM) in CSR.
   //
   func.func @matmul2(%A: tensor<4x8xf64, #CSR>,
                      %B: tensor<8x4xf64, #CSR>) -> tensor<4x4xf64, #CSR> {
     %C = bufferization.alloc_tensor() : tensor<4x4xf64, #CSR>
     %D = linalg.matmul
       ins(%A, %B: tensor<4x8xf64, #CSR>, tensor<8x4xf64, #CSR>)
          outs(%C: tensor<4x4xf64, #CSR>) -> tensor<4x4xf64, #CSR>
     return %D: tensor<4x4xf64, #CSR>
   }
 
   //
   // Computes C = A x B with all matrices sparse (SpMSpM) in DCSR.
   //
   func.func @matmul3(%A: tensor<4x8xf64, #DCSR>,
                      %B: tensor<8x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR> {
     %C = bufferization.alloc_tensor() : tensor<4x4xf64, #DCSR>
     %D = linalg.matmul
       ins(%A, %B: tensor<4x8xf64, #DCSR>, tensor<8x4xf64, #DCSR>)
          outs(%C: tensor<4x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR>
     return %D: tensor<4x4xf64, #DCSR>
   }
 
   //
%sb = arith.constant dense<[
         [ 0.0, 0.0, 2.0, 0.0 ],
         [ 0.0, 3.0, 0.0, 0.0 ],
         [ 4.0, 0.0, 0.0, 0.0 ],
         [ 0.0, 0.0, 0.0, 0.0 ],
         [ 0.0, 5.0, 0.0, 0.0 ],
         [ 0.0, 0.0, 6.0, 0.0 ],
         [ 0.0, 0.0, 7.0, 8.0 ]
     ]> : tensor<8x4xf64>
+    %zero = arith.constant dense<0.0> : tensor<4x4xf64>
 
     // Convert all these matrices to sparse format.
     %a1 = sparse_tensor.convert %da : tensor<4x8xf64> to tensor<4x8xf64, #CSR>
     %a2 = sparse_tensor.convert %da : tensor<4x8xf64> to tensor<4x8xf64, #DCSR>
     %a3 = sparse_tensor.convert %sa : tensor<4x8xf64> to tensor<4x8xf64, #CSR>
     %a4 = sparse_tensor.convert %sa : tensor<4x8xf64> to tensor<4x8xf64, #DCSR>
     %b1 = sparse_tensor.convert %db : tensor<8x4xf64> to tensor<8x4xf64, #CSR>
     %b2 = sparse_tensor.convert %db : tensor<8x4xf64> to tensor<8x4xf64, #DCSR>
     %b3 = sparse_tensor.convert %sb : tensor<8x4xf64> to tensor<8x4xf64, #CSR>
     %b4 = sparse_tensor.convert %sb : tensor<8x4xf64> to tensor<8x4xf64, #DCSR>
 
     // Call kernels with dense.
-    %0 = call @matmul1(%da, %db)
-       : (tensor<4x8xf64>, tensor<8x4xf64>) -> tensor<4x4xf64>
+    %0 = call @matmul1(%da, %db, %zero)
+       : (tensor<4x8xf64>, tensor<8x4xf64>, tensor<4x4xf64>) -> tensor<4x4xf64>
     %1 = call @matmul2(%a1, %b1)
        : (tensor<4x8xf64, #CSR>,
           tensor<8x4xf64, #CSR>) -> tensor<4x4xf64, #CSR>
     %2 = call @matmul3(%a2, %b2)
        : (tensor<4x8xf64, #DCSR>,
           tensor<8x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR>
 
     // Call kernels with one sparse.
-    %3 = call @matmul1(%sa, %db)
-       : (tensor<4x8xf64>, tensor<8x4xf64>) -> tensor<4x4xf64>
+    %3 = call @matmul1(%sa, %db, %zero)
+       : (tensor<4x8xf64>, tensor<8x4xf64>, tensor<4x4xf64>) -> tensor<4x4xf64>
     %4 = call @matmul2(%a3, %b1)
        : (tensor<4x8xf64, #CSR>,
           tensor<8x4xf64, #CSR>) -> tensor<4x4xf64, #CSR>
     %5 = call @matmul3(%a4, %b2)
        : (tensor<4x8xf64, #DCSR>,
           tensor<8x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR>
 
     // Call kernels with sparse.
-    %6 = call @matmul1(%sa, %sb)
-       : (tensor<4x8xf64>, tensor<8x4xf64>) -> tensor<4x4xf64>
+    %6 = call @matmul1(%sa, %sb, %zero)
+       : (tensor<4x8xf64>, tensor<8x4xf64>, tensor<4x4xf64>) -> tensor<4x4xf64>
     %7 = call @matmul2(%a3, %b3)
        : (tensor<4x8xf64, #CSR>,
           tensor<8x4xf64, #CSR>) -> tensor<4x4xf64, #CSR>
     %8 = call @matmul3(%a4, %b4)
        : (tensor<4x8xf64, #DCSR>,
           tensor<8x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR>
 
     //
func.func @entry() {
     sparse_tensor.release %b4 : tensor<8x4xf64, #DCSR>
     sparse_tensor.release %1 : tensor<4x4xf64, #CSR>
     sparse_tensor.release %2 : tensor<4x4xf64, #DCSR>
     sparse_tensor.release %4 : tensor<4x4xf64, #CSR>
     sparse_tensor.release %5 : tensor<4x4xf64, #DCSR>
     sparse_tensor.release %7 : tensor<4x4xf64, #CSR>
     sparse_tensor.release %8 : tensor<4x4xf64, #DCSR>
 
-    // TODO(springerm): needed?
-    %m0 = bufferization.to_memref %0 : memref<4x4xf64>
-    memref.dealloc %m0 : memref<4x4xf64>
-    %m3 = bufferization.to_memref %3 : memref<4x4xf64>
-    memref.dealloc %m3 : memref<4x4xf64>
-    %m6 = bufferization.to_memref %6 : memref<4x4xf64>
-    memref.dealloc %m6 : memref<4x4xf64>
     return
   }
 }