[mlir][sparse] Make three tests run with the codegen path.

[bixia]

Add one more test.

[aartbik]

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

98

yes, very neat!

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

-// RUN: mlir-opt %s --sparse-compiler | \
+// RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
+// RUN: mlir-cpu-runner \
+// RUN:  -e entry -entry-point-result=void  \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: FileCheck %s
+
+// RUN: mlir-opt %s --sparse-compiler="enable-runtime-library=false enable-buffer-initialization=true"| \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #Tensor1  = #sparse_tensor.encoding<{
   dimLevelType = [ "compressed", "compressed", "compressed" ],
   dimOrdering = affine_map<(i,j,k) -> (i,j,k)>

 //
 module {
   //
   // Output utilities.
   //
   func.func @dumpf64(%arg0: memref<?xf64>) {
     %c0 = arith.constant 0 : index
     %d0 = arith.constant -1.0 : f64
-    %0 = vector.transfer_read %arg0[%c0], %d0: memref<?xf64>, vector<25xf64>
-    vector.print %0 : vector<25xf64>
+    %0 = vector.transfer_read %arg0[%c0], %d0: memref<?xf64>, vector<24xf64>
+    vector.print %0 : vector<24xf64>
     return
   }
   func.func @dumpidx(%arg0: memref<?xindex>) {
     %c0 = arith.constant 0 : index
     %d0 = arith.constant 0 : index
     %0 = vector.transfer_read %arg0[%c0], %d0: memref<?xindex>, vector<25xindex>
     vector.print %0 : vector<25xindex>
     return
func.func @entry() {
     %d = sparse_tensor.convert %1 : tensor<2x3x4xf64, #Tensor1> to tensor<2x3x4xf64, #Tensor2>
     %e = sparse_tensor.convert %2 : tensor<2x3x4xf64, #Tensor2> to tensor<2x3x4xf64, #Tensor2>
     %f = sparse_tensor.convert %3 : tensor<2x3x4xf64, #Tensor3> to tensor<2x3x4xf64, #Tensor2>
     %g = sparse_tensor.convert %1 : tensor<2x3x4xf64, #Tensor1> to tensor<2x3x4xf64, #Tensor3>
     %h = sparse_tensor.convert %2 : tensor<2x3x4xf64, #Tensor2> to tensor<2x3x4xf64, #Tensor3>
     %i = sparse_tensor.convert %3 : tensor<2x3x4xf64, #Tensor3> to tensor<2x3x4xf64, #Tensor3>
 
     //
+    // Check number_of_entries.
+    //
+    // CHECK-COUNT-12: 24
+    %nv1 = sparse_tensor.number_of_entries %1 : tensor<2x3x4xf64, #Tensor1>
+    %nv2 = sparse_tensor.number_of_entries %2 : tensor<2x3x4xf64, #Tensor2>
+    %nv3 = sparse_tensor.number_of_entries %3 : tensor<2x3x4xf64, #Tensor3>
+    %nav = sparse_tensor.number_of_entries %a : tensor<2x3x4xf64, #Tensor1>
+    %nbv = sparse_tensor.number_of_entries %b : tensor<2x3x4xf64, #Tensor1>
+    %ncv = sparse_tensor.number_of_entries %c : tensor<2x3x4xf64, #Tensor1>
+    %ndv = sparse_tensor.number_of_entries %d : tensor<2x3x4xf64, #Tensor2>
+    %nev = sparse_tensor.number_of_entries %e : tensor<2x3x4xf64, #Tensor2>
+    %nfv = sparse_tensor.number_of_entries %f : tensor<2x3x4xf64, #Tensor2>
+    %ngv = sparse_tensor.number_of_entries %g : tensor<2x3x4xf64, #Tensor3>
+    %nhv = sparse_tensor.number_of_entries %h : tensor<2x3x4xf64, #Tensor3>
+    %niv = sparse_tensor.number_of_entries %i : tensor<2x3x4xf64, #Tensor3>
+    vector.print %nv1 : index
+    vector.print %nv2 : index
+    vector.print %nv3 : index
+    vector.print %nav : index
+    vector.print %nbv : index
+    vector.print %ncv : index
+    vector.print %ndv : index
+    vector.print %nev : index
+    vector.print %nfv : index
+    vector.print %ngv : index
+    vector.print %nhv : index
+    vector.print %niv : index
+
+    //
     // Check values.
     //
-    // CHECK:      ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, -1 )
-    // CHECK-NEXT: ( 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24, -1 )
-    // CHECK-NEXT: ( 1, 5, 9, 13, 17, 21, 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23, 4, 8, 12, 16, 20, 24, -1 )
-    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, -1 )
-    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, -1 )
-    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, -1 )
-    // CHECK-NEXT: ( 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24, -1 )
-    // CHECK-NEXT: ( 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24, -1 )
-    // CHECK-NEXT: ( 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24, -1 )
-    // CHECK-NEXT: ( 1, 5, 9, 13, 17, 21, 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23, 4, 8, 12, 16, 20, 24, -1 )
-    // CHECK-NEXT: ( 1, 5, 9, 13, 17, 21, 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23, 4, 8, 12, 16, 20, 24, -1 )
-    // CHECK-NEXT: ( 1, 5, 9, 13, 17, 21, 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23, 4, 8, 12, 16, 20, 24, -1 )
+    // CHECK:      ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 )
+    // CHECK-NEXT: ( 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24 )
+    // CHECK-NEXT: ( 1, 5, 9, 13, 17, 21, 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23, 4, 8, 12, 16, 20, 24 )
+    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 )
+    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 )
+    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 )
+    // CHECK-NEXT: ( 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24 )
+    // CHECK-NEXT: ( 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24 )
+    // CHECK-NEXT: ( 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24 )
+    // CHECK-NEXT: ( 1, 5, 9, 13, 17, 21, 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23, 4, 8, 12, 16, 20, 24 )
+    // CHECK-NEXT: ( 1, 5, 9, 13, 17, 21, 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23, 4, 8, 12, 16, 20, 24 )
+    // CHECK-NEXT: ( 1, 5, 9, 13, 17, 21, 2, 6, 10, 14, 18, 22, 3, 7, 11, 15, 19, 23, 4, 8, 12, 16, 20, 24 )
     //
     %v1 = sparse_tensor.values %1 : tensor<2x3x4xf64, #Tensor1> to memref<?xf64>
     %v2 = sparse_tensor.values %2 : tensor<2x3x4xf64, #Tensor2> to memref<?xf64>
     %v3 = sparse_tensor.values %3 : tensor<2x3x4xf64, #Tensor3> to memref<?xf64>
     %av = sparse_tensor.values %a : tensor<2x3x4xf64, #Tensor1> to memref<?xf64>
     %bv = sparse_tensor.values %b : tensor<2x3x4xf64, #Tensor1> to memref<?xf64>
     %cv = sparse_tensor.values %c : tensor<2x3x4xf64, #Tensor1> to memref<?xf64>
     %dv = sparse_tensor.values %d : tensor<2x3x4xf64, #Tensor2> to memref<?xf64>

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2dense.mlir

-// RUN: mlir-opt %s --sparse-compiler | \
+// RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
-// RUN:  | \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: FileCheck %s
+
+// RUN: mlir-opt %s --sparse-compiler="enable-runtime-library=false"| \
+// RUN: mlir-cpu-runner \
+// RUN:  -e entry -entry-point-result=void \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #Tensor1  = #sparse_tensor.encoding<{
   dimLevelType = [ "compressed", "compressed", "compressed" ],
   dimOrdering = affine_map<(i,j,k) -> (i,j,k)>
 }>
 
 #Tensor2  = #sparse_tensor.encoding<{

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

-// RUN: mlir-opt %s --sparse-compiler | \
-// RUN: mlir-cpu-runner -e entry -entry-point-result=void \
+// RxUN: mlir-opt %s --sparse-compiler=enable-runtime-library=true | \
+// RxUN: mlir-cpu-runner \
+// RxUN:  -e entry -entry-point-result=void  \
+// RxUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RxUN: FileCheck %s
+
+// RUN: mlir-opt %s --sparse-compiler=enable-runtime-library=false | \
+// RUN: mlir-cpu-runner \
+// RUN:  -e entry -entry-point-result=void  \
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{
   dimLevelType = ["compressed"]
 }>
 
 #SparseMatrix = #sparse_tensor.encoding<{
func.func @entry() {
     %collapse10 = call @collapse_to_sparse_dyn(%dn) : (tensor<?x?x?x?xf64>) -> tensor<?x?xf64, #SparseMatrix>
     %collapse11 = call @collapse_sparse2sparse_dyn(%sdn) : (tensor<?x?x?x?xf64, #Sparse4dTensor>) -> tensor<?x?xf64, #SparseMatrix>
 
     //
     // Verify results of expand
     //
     // CHECK:      ( ( 1, 2, 3, 4 ), ( 5, 6, 7, 8 ), ( 9, 10, 11, 12 ) )
     // CHECK-NEXT: ( ( 1, 2, 3, 4 ), ( 5, 6, 7, 8 ), ( 9, 10, 11, 12 ) )
-    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, -1, -1, -1, -1 )
-    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, -1, -1, -1, -1 )
+    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 )
+    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 )
     // CHECK-NEXT: ( ( ( 1.1, 1.2 ), ( 1.3, 1.4 ) ), ( ( 2.1, 2.2 ), ( 2.3, 2.4 ) ), ( ( 3.1, 3.2 ), ( 3.3, 3.4 ) ) )
     // CHECK-NEXT: ( ( ( 1.1, 1.2 ), ( 1.3, 1.4 ) ), ( ( 2.1, 2.2 ), ( 2.3, 2.4 ) ), ( ( 3.1, 3.2 ), ( 3.3, 3.4 ) ) )
-    // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4, -1, -1, -1, -1 )
-    // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4, -1, -1, -1, -1 )
+    // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4 )
+    // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4 )
     // CHECK-NEXT: ( ( ( 1.1, 1.2 ), ( 1.3, 1.4 ) ), ( ( 2.1, 2.2 ), ( 2.3, 2.4 ) ), ( ( 3.1, 3.2 ), ( 3.3, 3.4 ) ) )
     // CHECK-NEXT: ( ( ( 1.1, 1.2 ), ( 1.3, 1.4 ) ), ( ( 2.1, 2.2 ), ( 2.3, 2.4 ) ), ( ( 3.1, 3.2 ), ( 3.3, 3.4 ) ) )
-    // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4, -1, -1, -1, -1 )
-    // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4, -1, -1, -1, -1 )
+    // CHECK-NEXT: 12
+    // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4 )
+    // CHECK-NEXT: 12
+    // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4 )
     //
 
     %m0 = vector.transfer_read %expand0[%c0, %c0], %df: tensor<3x4xf64>, vector<3x4xf64>
     vector.print %m0 : vector<3x4xf64>
     %m1 = vector.transfer_read %expand1[%c0, %c0], %df: tensor<3x4xf64>, vector<3x4xf64>
     vector.print %m1 : vector<3x4xf64>
     %a2 = sparse_tensor.values %expand2 : tensor<3x4xf64, #SparseMatrix> to memref<?xf64>
-    %m2 = vector.transfer_read %a2[%c0], %df: memref<?xf64>, vector<16xf64>
-    vector.print %m2 : vector<16xf64>
+    %m2 = vector.transfer_read %a2[%c0], %df: memref<?xf64>, vector<12xf64>
+    vector.print %m2 : vector<12xf64>
     %a3 = sparse_tensor.values %expand3 : tensor<3x4xf64, #SparseMatrix> to memref<?xf64>
-    %m3 = vector.transfer_read %a3[%c0], %df: memref<?xf64>, vector<16xf64>
-    vector.print %m3 : vector<16xf64>
+    %m3 = vector.transfer_read %a3[%c0], %df: memref<?xf64>, vector<12xf64>
+    vector.print %m3 : vector<12xf64>
 
     %m4 = vector.transfer_read %expand4[%c0, %c0, %c0], %df: tensor<3x2x2xf64>, vector<3x2x2xf64>
     vector.print %m4 : vector<3x2x2xf64>
     %m5 = vector.transfer_read %expand5[%c0, %c0, %c0], %df: tensor<3x2x2xf64>, vector<3x2x2xf64>
     vector.print %m5 : vector<3x2x2xf64>
     %a6 = sparse_tensor.values %expand6 : tensor<3x2x2xf64, #Sparse3dTensor> to memref<?xf64>
-    %m6 = vector.transfer_read %a6[%c0], %df: memref<?xf64>, vector<16xf64>
-    vector.print %m6 : vector<16xf64>
+    %m6 = vector.transfer_read %a6[%c0], %df: memref<?xf64>, vector<12xf64>
+    vector.print %m6 : vector<12xf64>
     %a7 = sparse_tensor.values %expand7 : tensor<3x2x2xf64, #Sparse3dTensor> to memref<?xf64>
-    %m7 = vector.transfer_read %a7[%c0], %df: memref<?xf64>, vector<16xf64>
-    vector.print %m7 : vector<16xf64>
+    %m7 = vector.transfer_read %a7[%c0], %df: memref<?xf64>, vector<12xf64>
+    vector.print %m7 : vector<12xf64>
 
     %m8 = vector.transfer_read %expand8[%c0, %c0, %c0], %df: tensor<?x2x?xf64>, vector<3x2x2xf64>
     vector.print %m8 : vector<3x2x2xf64>
     %m9 = vector.transfer_read %expand9[%c0, %c0, %c0], %df: tensor<?x2x?xf64>, vector<3x2x2xf64>
     vector.print %m9 : vector<3x2x2xf64>
+    %n10 = sparse_tensor.number_of_entries %expand10 : tensor<?x2x?xf64, #Sparse3dTensor>
+    vector.print %n10 : index
     %a10 = sparse_tensor.values %expand10 : tensor<?x2x?xf64, #Sparse3dTensor> to memref<?xf64>
-    %m10 = vector.transfer_read %a10[%c0], %df: memref<?xf64>, vector<16xf64>
-    vector.print %m10 : vector<16xf64>
+    %m10 = vector.transfer_read %a10[%c0], %df: memref<?xf64>, vector<12xf64>
+    vector.print %m10 : vector<12xf64>
+    %n11 = sparse_tensor.number_of_entries %expand11 : tensor<?x2x?xf64, #Sparse3dTensor>
+    vector.print %n11 : index
     %a11 = sparse_tensor.values %expand11 : tensor<?x2x?xf64, #Sparse3dTensor> to memref<?xf64>
-    %m11 = vector.transfer_read %a11[%c0], %df: memref<?xf64>, vector<16xf64>
-    vector.print %m11 : vector<16xf64>
+    %m11 = vector.transfer_read %a11[%c0], %df: memref<?xf64>, vector<12xf64>
+    vector.print %m11 : vector<12xf64>
 
 
-    // 
+    //
     // Verify results of collapse
-    // 
+    //
     // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4 )
     // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4 )
-    // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4, -1, -1, -1, -1 )
-    // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4, -1, -1, -1, -1 )
+    // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4 )
+    // CHECK-NEXT: ( 1.1, 1.2, 1.3, 1.4, 2.1, 2.2, 2.3, 2.4, 3.1, 3.2, 3.3, 3.4 )
     // CHECK-NEXT: ( ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ), ( 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ), ( 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 ), ( 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 ), ( 41, 42, 43, 44, 45, 26, 47, 48, 49, 50 ), ( 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 ) )
     // CHECK-NEXT: ( ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ), ( 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ), ( 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 ), ( 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 ), ( 41, 42, 43, 44, 45, 26, 47, 48, 49, 50 ), ( 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 ) )
-    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 26, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, -1, -1, -1, -1 )
-    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 26, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, -1, -1, -1, -1 )
+    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 26, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 )
+    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 26, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 )
     // CHECK-NEXT: ( ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ), ( 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ), ( 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 ), ( 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 ), ( 41, 42, 43, 44, 45, 26, 47, 48, 49, 50 ), ( 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 ) )
     // CHECK-NEXT: ( ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ), ( 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 ), ( 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 ), ( 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 ), ( 41, 42, 43, 44, 45, 26, 47, 48, 49, 50 ), ( 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 ) )
-    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 26, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, -1, -1, -1, -1 )
-    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 26, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, -1, -1, -1, -1 )
+    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 26, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 )
+    // CHECK-NEXT: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 26, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 )
     //
 
     %v0 = vector.transfer_read %collapse0[%c0], %df: tensor<12xf64>, vector<12xf64>
     vector.print %v0 : vector<12xf64>
     %v1 = vector.transfer_read %collapse1[%c0], %df: tensor<12xf64>, vector<12xf64>
     vector.print %v1 : vector<12xf64>
     %b2 = sparse_tensor.values %collapse2 : tensor<12xf64, #SparseVector> to memref<?xf64>
-    %v2 = vector.transfer_read %b2[%c0], %df: memref<?xf64>, vector<16xf64>
-    vector.print %v2 : vector<16xf64>
+    %v2 = vector.transfer_read %b2[%c0], %df: memref<?xf64>, vector<12xf64>
+    vector.print %v2 : vector<12xf64>
     %b3 = sparse_tensor.values %collapse3 : tensor<12xf64, #SparseVector> to memref<?xf64>
-    %v3 = vector.transfer_read %b3[%c0], %df: memref<?xf64>, vector<16xf64>
-    vector.print %v3 : vector<16xf64>
+    %v3 = vector.transfer_read %b3[%c0], %df: memref<?xf64>, vector<12xf64>
+    vector.print %v3 : vector<12xf64>
 
     %v4 = vector.transfer_read %collapse4[%c0, %c0], %df: tensor<6x10xf64>, vector<6x10xf64>
     vector.print %v4 : vector<6x10xf64>
     %v5 = vector.transfer_read %collapse5[%c0, %c0], %df: tensor<6x10xf64>, vector<6x10xf64>
     vector.print %v5 : vector<6x10xf64>
     %b6 = sparse_tensor.values %collapse6 : tensor<6x10xf64, #SparseMatrix> to memref<?xf64>
-    %v6 = vector.transfer_read %b6[%c0], %df: memref<?xf64>, vector<64xf64>
-    vector.print %v6 : vector<64xf64>
+    %v6 = vector.transfer_read %b6[%c0], %df: memref<?xf64>, vector<60xf64>
+    vector.print %v6 : vector<60xf64>
     %b7 = sparse_tensor.values %collapse7 : tensor<6x10xf64, #SparseMatrix> to memref<?xf64>
-    %v7 = vector.transfer_read %b7[%c0], %df: memref<?xf64>, vector<64xf64>
-    vector.print %v7 : vector<64xf64>
+    %v7 = vector.transfer_read %b7[%c0], %df: memref<?xf64>, vector<60xf64>
+    vector.print %v7 : vector<60xf64>
 
     %v8 = vector.transfer_read %collapse8[%c0, %c0], %df: tensor<?x?xf64>, vector<6x10xf64>
     vector.print %v8 : vector<6x10xf64>
     %v9 = vector.transfer_read %collapse9[%c0, %c0], %df: tensor<?x?xf64>, vector<6x10xf64>
     vector.print %v9 : vector<6x10xf64>
     %b10 = sparse_tensor.values %collapse10 : tensor<?x?xf64, #SparseMatrix> to memref<?xf64>
-    %v10 = vector.transfer_read %b10[%c0], %df: memref<?xf64>, vector<64xf64>
-    vector.print %v10 : vector<64xf64>
+    %v10 = vector.transfer_read %b10[%c0], %df: memref<?xf64>, vector<60xf64>
+    vector.print %v10 : vector<60xf64>
     %b11 = sparse_tensor.values %collapse11 : tensor<?x?xf64, #SparseMatrix> to memref<?xf64>
-    %v11 = vector.transfer_read %b11[%c0], %df: memref<?xf64>, vector<64xf64>
-    vector.print %v11 : vector<64xf64>
+    %v11 = vector.transfer_read %b11[%c0], %df: memref<?xf64>, vector<60xf64>
+    vector.print %v11 : vector<60xf64>
 
 
     // Release sparse resources.
     bufferization.dealloc_tensor %sv : tensor<12xf64, #SparseVector>
     bufferization.dealloc_tensor %sm : tensor<3x4xf64, #SparseMatrix>
     bufferization.dealloc_tensor %sn : tensor<2x3x5x2xf64, #Sparse4dTensor>
     bufferization.dealloc_tensor %sdm : tensor<?x?xf64, #SparseMatrix>
     bufferization.dealloc_tensor %sdn : tensor<?x?x?x?xf64, #Sparse4dTensor>