[mlir][sparse] fix some asan detected leaks in integration tests

[aartbik]

Summary

One was an oversight, but the others seem something that regressed.
Matthias to have look later.

https://github.com/llvm/llvm-project/issues/57663

[Peiming]

Thanks!

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

func.func @entry() {
     %c3 = arith.constant 3 : index
     %t1 = bufferization.alloc_tensor() : tensor<4x5xf64, #DCSR>
     %t2 = bufferization.alloc_tensor(%c2, %c3) : tensor<?x?xf64, #DCSR>
 
     %d1_0 = tensor.dim %t1, %c0 : tensor<4x5xf64, #DCSR>
     %d2_0 = tensor.dim %t2, %c0 : tensor<?x?xf64, #DCSR>
     %d1_1 = tensor.dim %t1, %c1 : tensor<4x5xf64, #DCSR>
     %d2_1 = tensor.dim %t2, %c1 : tensor<?x?xf64, #DCSR>
+
     // CHECK: 4
     vector.print %d1_0 : index
     // CHECK-NEXT: 2
     vector.print %d2_0 : index
     // CHECK-NEXT: 5
     vector.print %d1_1 : index
     // CHECK-NEXT: 3
     vector.print %d2_1 : index
+
+    // Release resources.
+    bufferization.dealloc_tensor %t1 : tensor<4x5xf64, #DCSR>
+    bufferization.dealloc_tensor %t2 : tensor<?x?xf64, #DCSR>
+
     return
   }
 }
 

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

func.func @entry() {
     // CHECK: ( 889, 1514, -21, -3431 )
     //
     %v = vector.transfer_read %0[%c0], %i0: tensor<?xi32>, vector<4xi32>
     vector.print %v : vector<4xi32>
 
     // Release the resources.
     bufferization.dealloc_tensor %a : tensor<?x?xi32, #SparseMatrix>
 
+    // TODO(springerm): auto release!
+    bufferization.dealloc_tensor %b : tensor<?xi32>
+    bufferization.dealloc_tensor %x : tensor<?xi32>
+
     return
   }
 }

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

func.func @entry() {
     //
     %v = vector.transfer_read %0[%cst0, %cst0], %f0
           : tensor<?x?xf64>, vector<2x5xf64>
     vector.print %v : vector<2x5xf64>
 
     // Release the resources.
     bufferization.dealloc_tensor %b : tensor<?x?x?xf64, #SparseTensor>
 
+    // TODO(springerm): auto release!
+    bufferization.dealloc_tensor %a : tensor<?x?xf64>
+    bufferization.dealloc_tensor %c : tensor<?x?xf64>
+    bufferization.dealloc_tensor %d : tensor<?x?xf64>
+
     return
   }
 }

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

func.func @entry() {
     scf.for %i = %c0 to %c5 step %c1 {
       %v = vector.transfer_read %0[%i, %c0], %d0: tensor<?x?xf32>, vector<5xf32>
       vector.print %v : vector<5xf32>
     }
 
     // Release the resources.
     bufferization.dealloc_tensor %s : tensor<?x?xf32, #SparseMatrix>
 
+    // TODO(springerm): auto release!
+    bufferization.dealloc_tensor %x : tensor<?x?xf32>
+    bufferization.dealloc_tensor %a : tensor<?x?xf32>
+    bufferization.dealloc_tensor %b : tensor<?x?xf32>
+
     return
   }
 }

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

^bb0(%i : index, %j : index):
       %k = arith.sitofp %k2 : i32 to f64
       tensor.yield %k : f64
     } : tensor<?x?xf64>
 
     %x = tensor.generate %c4, %c4 {
     ^bb0(%i : index, %j : index):
       tensor.yield %i0 : f64
     } : tensor<?x?xf64>
-  
     // Call kernel.
     %0 = call @kernel_spmm(%a, %b, %x)
       : (tensor<?x?xf64, #SparseMatrix>, tensor<?x?xf64>, tensor<?x?xf64>) -> tensor<?x?xf64>
 
     // Print the result for verification.
     //
     // CHECK: ( ( 3548, 3550, 3552, 3554 ), ( 6052, 6053, 6054, 6055 ), ( -56, -63, -70, -77 ), ( -13704, -13709, -13714, -13719 ) )
     //
     %v = vector.transfer_read %0[%c0, %c0], %i0: tensor<?x?xf64>, vector<4x4xf64>
     vector.print %v : vector<4x4xf64>
 
     // Release the resources.
     bufferization.dealloc_tensor %a : tensor<?x?xf64, #SparseMatrix>
 
+    // TODO(springerm): auto release!
+    bufferization.dealloc_tensor %b : tensor<?x?xf64>
+    bufferization.dealloc_tensor %x : tensor<?x?xf64>
+
     return
   }
 }