diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/concatenate.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/concatenate.mlir
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/concatenate.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/concatenate.mlir
@@ -2,13 +2,13 @@
 // DEFINE: %{command} = mlir-opt %s --sparse-compiler=%{option} | \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{command}
 //
 // Do the same run, but now with direct IR generation.
-// REDEFINE: %{option} = enable-runtime-library=false
+// REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{command}
 
 #MAT_C_C = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}>
@@ -35,6 +35,9 @@
 }>
 
 module {
+  func.func private @printMemrefF64(%ptr : tensor<*xf64>)
+  func.func private @printMemref1dF64(%ptr : memref<?xf64>) attributes { llvm.emit_c_interface }
+
   //
   // Tests without permutation.
   //
@@ -180,125 +183,95 @@
   }
 
   func.func @dump_mat_9x4(%A: tensor<9x4xf64, #MAT_C_C>) {
-    %c0 = arith.constant 0 : index
-    %du = arith.constant -1.0 : f64
-
     %c = sparse_tensor.convert %A : tensor<9x4xf64, #MAT_C_C> to tensor<9x4xf64>
-    %v = vector.transfer_read %c[%c0, %c0], %du: tensor<9x4xf64>, vector<9x4xf64>
-    vector.print %v : vector<9x4xf64>
+    %cu = tensor.cast %c : tensor<9x4xf64> to tensor<*xf64>
+    call @printMemrefF64(%cu) : (tensor<*xf64>) -> ()
 
     %n = sparse_tensor.number_of_entries %A : tensor<9x4xf64, #MAT_C_C>
     vector.print %n : index
 
     %1 = sparse_tensor.values %A : tensor<9x4xf64, #MAT_C_C> to memref<?xf64>
-    %2 = vector.transfer_read %1[%c0], %du: memref<?xf64>, vector<18xf64>
-    vector.print %2 : vector<18xf64>
+    call @printMemref1dF64(%1) : (memref<?xf64>) -> ()
 
     return
   }
 
   func.func @dump_mat_perm_9x4(%A: tensor<9x4xf64, #MAT_C_C_P>) {
-    %c0 = arith.constant 0 : index
-    %du = arith.constant -1.0 : f64
-
     %c = sparse_tensor.convert %A : tensor<9x4xf64, #MAT_C_C_P> to tensor<9x4xf64>
-    %v = vector.transfer_read %c[%c0, %c0], %du: tensor<9x4xf64>, vector<9x4xf64>
-    vector.print %v : vector<9x4xf64>
+    %cu = tensor.cast %c : tensor<9x4xf64> to tensor<*xf64>
+    call @printMemrefF64(%cu) : (tensor<*xf64>) -> ()
 
     %n = sparse_tensor.number_of_entries %A : tensor<9x4xf64, #MAT_C_C_P>
     vector.print %n : index
 
     %1 = sparse_tensor.values %A : tensor<9x4xf64, #MAT_C_C_P> to memref<?xf64>
-    %2 = vector.transfer_read %1[%c0], %du: memref<?xf64>, vector<18xf64>
-    vector.print %2 : vector<18xf64>
+    call @printMemref1dF64(%1) : (memref<?xf64>) -> ()
 
     return
   }
 
   func.func @dump_mat_dense_9x4(%A: tensor<9x4xf64>) {
-    %c0 = arith.constant 0 : index
-    %du = arith.constant -1.0 : f64
-
-    %v = vector.transfer_read %A[%c0, %c0], %du: tensor<9x4xf64>, vector<9x4xf64>
-    vector.print %v : vector<9x4xf64>
+    %u = tensor.cast %A : tensor<9x4xf64> to tensor<*xf64>
+    call @printMemrefF64(%u) : (tensor<*xf64>) -> ()
 
     return
   }
 
   func.func @dump_mat_annotated_dense_9x4(%A: tensor<9x4xf64, #MAT_D_D>) {
-    %c0 = arith.constant 0 : index
-    %du = arith.constant -1.0 : f64
-
     %n = sparse_tensor.number_of_entries %A : tensor<9x4xf64, #MAT_D_D>
     vector.print %n : index
 
     %1 = sparse_tensor.values %A : tensor<9x4xf64, #MAT_D_D> to memref<?xf64>
-    %2 = vector.transfer_read %1[%c0], %du: memref<?xf64>, vector<36xf64>
-    vector.print %2 : vector<36xf64>
+    call @printMemref1dF64(%1) : (memref<?xf64>) -> ()
 
     return
   }
 
   func.func @dump_mat_4x9(%A: tensor<4x9xf64, #MAT_C_C>) {
-    %c0 = arith.constant 0 : index
-    %du = arith.constant -1.0 : f64
-
     %c = sparse_tensor.convert %A : tensor<4x9xf64, #MAT_C_C> to tensor<4x9xf64>
-    %v = vector.transfer_read %c[%c0, %c0], %du: tensor<4x9xf64>, vector<4x9xf64>
-    vector.print %v : vector<4x9xf64>
+    %cu = tensor.cast %c : tensor<4x9xf64> to tensor<*xf64>
+    call @printMemrefF64(%cu) : (tensor<*xf64>) -> ()
 
     %n = sparse_tensor.number_of_entries %A : tensor<4x9xf64, #MAT_C_C>
     vector.print %n : index
 
     %1 = sparse_tensor.values %A : tensor<4x9xf64, #MAT_C_C> to memref<?xf64>
-    %2 = vector.transfer_read %1[%c0], %du: memref<?xf64>, vector<18xf64>
-    vector.print %2 : vector<18xf64>
+    call @printMemref1dF64(%1) : (memref<?xf64>) -> ()
 
     return
   }
 
   func.func @dump_mat_dyn(%A: tensor<?x?xf64, #MAT_C_C>) {
-    %c0 = arith.constant 0 : index
-    %du = arith.constant -1.0 : f64
-
     %c = sparse_tensor.convert %A : tensor<?x?xf64, #MAT_C_C> to tensor<?x?xf64>
-    %v = vector.transfer_read %c[%c0, %c0], %du: tensor<?x?xf64>, vector<4x9xf64>
-    vector.print %v : vector<4x9xf64>
+    %cu = tensor.cast %c : tensor<?x?xf64> to tensor<*xf64>
+    call @printMemrefF64(%cu) : (tensor<*xf64>) -> ()
 
     %n = sparse_tensor.number_of_entries %A : tensor<?x?xf64, #MAT_C_C>
     vector.print %n : index
 
     %1 = sparse_tensor.values %A : tensor<?x?xf64, #MAT_C_C> to memref<?xf64>
-    %2 = vector.transfer_read %1[%c0], %du: memref<?xf64>, vector<18xf64>
-    vector.print %2 : vector<18xf64>
+    call @printMemref1dF64(%1) : (memref<?xf64>) -> ()
 
     return
   }
 
   func.func @dump_mat_perm_4x9(%A: tensor<4x9xf64, #MAT_C_C_P>) {
-    %c0 = arith.constant 0 : index
-    %du = arith.constant -1.0 : f64
-
     %c = sparse_tensor.convert %A : tensor<4x9xf64, #MAT_C_C_P> to tensor<4x9xf64>
-    %v = vector.transfer_read %c[%c0, %c0], %du: tensor<4x9xf64>, vector<4x9xf64>
-    vector.print %v : vector<4x9xf64>
+    %cu = tensor.cast %c : tensor<4x9xf64> to tensor<*xf64>
+    call @printMemrefF64(%cu) : (tensor<*xf64>) -> ()
 
     %n = sparse_tensor.number_of_entries %A : tensor<4x9xf64, #MAT_C_C_P>
     vector.print %n : index
 
     %1 = sparse_tensor.values %A : tensor<4x9xf64, #MAT_C_C_P> to memref<?xf64>
-    %2 = vector.transfer_read %1[%c0], %du: memref<?xf64>, vector<18xf64>
-    vector.print %2 : vector<18xf64>
+    call @printMemref1dF64(%1) : (memref<?xf64>) -> ()
 
     return
   }
 
   func.func @dump_mat_dense_4x9(%A: tensor<4x9xf64>) {
-    %c0 = arith.constant 0 : index
-    %du = arith.constant -1.0 : f64
-
-    %v = vector.transfer_read %A[%c0, %c0], %du: tensor<4x9xf64>, vector<4x9xf64>
-    vector.print %v : vector<4x9xf64>
+    %1 = tensor.cast %A : tensor<4x9xf64> to tensor<*xf64>
+    call @printMemrefF64(%1) : (tensor<*xf64>) -> ()
 
     return
   }
@@ -343,111 +316,202 @@
     %sm43cd_dyn = sparse_tensor.convert %m43 : tensor<4x3xf64> to tensor<?x?xf64, #MAT_C_D>
     %sm44dc_dyn = sparse_tensor.convert %m44 : tensor<4x4xf64> to tensor<?x?xf64, #MAT_D_C>
 
-    // CHECK:    ( ( 1, 0, 3, 0 ), ( 0, 2, 0, 0 ), ( 1, 0, 1, 1 ), ( 0, 0.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 0, 0, 1.5, 1 ), ( 0, 3.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   3,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0],
+    // CHECK-NEXT:  [1,   0,   1,   1],
+    // CHECK-NEXT:  [0,   0.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   1.5,   1],
+    // CHECK-NEXT:  [0,   3.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [1,   0.5,   0,   0]]
     // CHECK-NEXT: 18
-    // CHECK-NEXT: ( 1, 3, 2, 1, 1, 1, 0.5, 1, 5, 2, 1.5, 1, 3.5, 1, 5, 2, 1, 0.5 )
+    // CHECK:      [1,  3,  2,  1,  1,  1,  0.5,  1,  5,  2,  1.5,  1,  3.5,  1,  5,  2,  1,  0.5
     %0 = call @concat_sparse_sparse(%sm24cc, %sm34cd, %sm44dc)
                : (tensor<2x4xf64, #MAT_C_C>, tensor<3x4xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C>) -> tensor<9x4xf64, #MAT_C_C>
     call @dump_mat_9x4(%0) : (tensor<9x4xf64, #MAT_C_C>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 3, 0 ), ( 0, 2, 0, 0 ), ( 1, 0, 1, 1 ), ( 0, 0.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 0, 0, 1.5, 1 ), ( 0, 3.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   3,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0],
+    // CHECK-NEXT:  [1,   0,   1,   1],
+    // CHECK-NEXT:  [0,   0.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   1.5,   1],
+    // CHECK-NEXT:  [0,   3.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [1,   0.5,   0,   0]]
     %1 = call @concat_sparse_dense(%sm24cc, %sm34cd, %sm44dc)
                : (tensor<2x4xf64, #MAT_C_C>, tensor<3x4xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C>) -> tensor<9x4xf64>
     call @dump_mat_dense_9x4(%1) : (tensor<9x4xf64>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 3, 0 ), ( 0, 2, 0, 0 ), ( 1, 0, 1, 1 ), ( 0, 0.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 0, 0, 1.5, 1 ), ( 0, 3.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   3,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0],
+    // CHECK-NEXT:  [1,   0,   1,   1],
+    // CHECK-NEXT:  [0,   0.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   1.5,   1],
+    // CHECK-NEXT:  [0,   3.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [1,   0.5,   0,   0]]
     // CHECK-NEXT: 18
-    // CHECK-NEXT: ( 1, 3, 2, 1, 1, 1, 0.5, 1, 5, 2, 1.5, 1, 3.5, 1, 5, 2, 1, 0.5 )
+    // CHECK:      [1,  3,  2,  1,  1,  1,  0.5,  1,  5,  2,  1.5,  1,  3.5,  1,  5,  2,  1,  0.5
     %2 = call @concat_mix_sparse(%m24, %sm34cd, %sm44dc)
                : (tensor<2x4xf64>, tensor<3x4xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C>) -> tensor<9x4xf64, #MAT_C_C>
     call @dump_mat_9x4(%2) : (tensor<9x4xf64, #MAT_C_C>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 3, 0 ), ( 0, 2, 0, 0 ), ( 1, 0, 1, 1 ), ( 0, 0.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 0, 0, 1.5, 1 ), ( 0, 3.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   3,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0],
+    // CHECK-NEXT:  [1,   0,   1,   1],
+    // CHECK-NEXT:  [0,   0.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   1.5,   1],
+    // CHECK-NEXT:  [0,   3.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [1,   0.5,   0,   0]]
     %3 = call @concat_mix_dense(%m24, %sm34cd, %sm44dc)
                : (tensor<2x4xf64>, tensor<3x4xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C>) -> tensor<9x4xf64>
     call @dump_mat_dense_9x4(%3) : (tensor<9x4xf64>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 3, 0 ), ( 0, 2, 0, 0 ), ( 1, 0, 1, 1 ), ( 0, 0.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 0, 0, 1.5, 1 ), ( 0, 3.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   3,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0],
+    // CHECK-NEXT:  [1,   0,   1,   1],
+    // CHECK-NEXT:  [0,   0.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   1.5,   1],
+    // CHECK-NEXT:  [0,   3.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [1,   0.5,   0,   0]]
     // CHECK-NEXT: 18
-    // CHECK-NEXT: ( 1, 1, 1, 1, 1, 2, 0.5, 5, 3.5, 5, 0.5, 3, 1, 2, 1.5, 2, 1, 1 )
+    // CHECK:      [1,  1,  1,  1,  1,  2,  0.5,  5,  3.5,  5,  0.5,  3,  1,  2,  1.5,  2,  1,  1
     %4 = call @concat_sparse_sparse_perm(%sm24ccp, %sm34cd, %sm44dc)
                : (tensor<2x4xf64, #MAT_C_C_P>, tensor<3x4xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C>) -> tensor<9x4xf64, #MAT_C_C_P>
     call @dump_mat_perm_9x4(%4) : (tensor<9x4xf64, #MAT_C_C_P>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 3, 0 ), ( 0, 2, 0, 0 ), ( 1, 0, 1, 1 ), ( 0, 0.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 0, 0, 1.5, 1 ), ( 0, 3.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   3,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0],
+    // CHECK-NEXT:  [1,   0,   1,   1],
+    // CHECK-NEXT:  [0,   0.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   1.5,   1],
+    // CHECK-NEXT:  [0,   3.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [1,   0.5,   0,   0]]
     %5 = call @concat_sparse_dense_perm(%sm24ccp, %sm34cdp, %sm44dc)
                : (tensor<2x4xf64, #MAT_C_C_P>, tensor<3x4xf64, #MAT_C_D_P>, tensor<4x4xf64, #MAT_D_C>) -> tensor<9x4xf64>
     call @dump_mat_dense_9x4(%5) : (tensor<9x4xf64>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 3, 0 ), ( 0, 2, 0, 0 ), ( 1, 0, 1, 1 ), ( 0, 0.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 0, 0, 1.5, 1 ), ( 0, 3.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   3,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0],
+    // CHECK-NEXT:  [1,   0,   1,   1],
+    // CHECK-NEXT:  [0,   0.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   1.5,   1],
+    // CHECK-NEXT:  [0,   3.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [1,   0.5,   0,   0]]
     // CHECK-NEXT: 18
-    // CHECK-NEXT: ( 1, 3, 2, 1, 1, 1, 0.5, 1, 5, 2, 1.5, 1, 3.5, 1, 5, 2, 1, 0.5 )
+    // CHECK:      [1,  3,  2,  1,  1,  1,  0.5,  1,  5,  2,  1.5,  1,  3.5,  1,  5,  2,  1,  0.5
     %6 = call @concat_mix_sparse_perm(%m24, %sm34cdp, %sm44dc)
                : (tensor<2x4xf64>, tensor<3x4xf64, #MAT_C_D_P>, tensor<4x4xf64, #MAT_D_C>) -> tensor<9x4xf64, #MAT_C_C>
     call @dump_mat_9x4(%6) : (tensor<9x4xf64, #MAT_C_C>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 3, 0 ), ( 0, 2, 0, 0 ), ( 1, 0, 1, 1 ), ( 0, 0.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 0, 0, 1.5, 1 ), ( 0, 3.5, 0, 0 ), ( 1, 5, 2, 0 ), ( 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   3,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0],
+    // CHECK-NEXT:  [1,   0,   1,   1],
+    // CHECK-NEXT:  [0,   0.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   1.5,   1],
+    // CHECK-NEXT:  [0,   3.5,   0,   0],
+    // CHECK-NEXT:  [1,   5,   2,   0],
+    // CHECK-NEXT:  [1,   0.5,   0,   0]]
     %7 = call @concat_mix_dense_perm(%m24, %sm34cd, %sm44dcp)
                : (tensor<2x4xf64>, tensor<3x4xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C_P>) -> tensor<9x4xf64>
     call @dump_mat_dense_9x4(%7) : (tensor<9x4xf64>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 1, 0, 1, 0, 0, 1.5, 1 ), ( 3.1, 0, 1, 0, 0.5, 0, 3.5, 0, 0 ), ( 0, 2, 0, 0, 1, 1, 5, 2, 0 ), ( 0, 0, 5, 2, 0, 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   1,   0,   1,   0,   0,   1.5,   1],
+    // CHECK-NEXT:  [3.1,   0,   1,   0,   0.5,   0,   3.5,   0,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0,   1,   1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   5,   2,   0,   1,   0.5,   0,   0]]
     // CHECK-NEXT: 18
-    // CHECK-NEXT: ( 1, 1, 1, 1.5, 1, 3.1, 1, 0.5, 3.5, 2, 1, 1, 5, 2, 5, 2, 1, 0.5 )
+    // CHECK:      [1,  1,  1,  1.5,  1,  3.1,  1,  0.5,  3.5,  2,  1,  1,  5,  2,  5,  2,  1,  0.5
     %8 = call @concat_sparse_sparse_dim1(%sm42cc, %sm43cd, %sm44dc)
                : (tensor<4x2xf64, #MAT_C_C>, tensor<4x3xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C>) -> tensor<4x9xf64, #MAT_C_C>
     call @dump_mat_4x9(%8) : (tensor<4x9xf64, #MAT_C_C>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 1, 0, 1, 0, 0, 1.5, 1 ), ( 3.1, 0, 1, 0, 0.5, 0, 3.5, 0, 0 ), ( 0, 2, 0, 0, 1, 1, 5, 2, 0 ), ( 0, 0, 5, 2, 0, 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   1,   0,   1,   0,   0,   1.5,   1],
+    // CHECK-NEXT:  [3.1,   0,   1,   0,   0.5,   0,   3.5,   0,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0,   1,   1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   5,   2,   0,   1,   0.5,   0,   0]]
     %9 = call @concat_sparse_dense_dim1(%sm42cc, %sm43cd, %sm44dc)
                : (tensor<4x2xf64, #MAT_C_C>, tensor<4x3xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C>) -> tensor<4x9xf64>
     call @dump_mat_dense_4x9(%9) : (tensor<4x9xf64>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 1, 0, 1, 0, 0, 1.5, 1 ), ( 3.1, 0, 1, 0, 0.5, 0, 3.5, 0, 0 ), ( 0, 2, 0, 0, 1, 1, 5, 2, 0 ), ( 0, 0, 5, 2, 0, 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   1,   0,   1,   0,   0,   1.5,   1],
+    // CHECK-NEXT:  [3.1,   0,   1,   0,   0.5,   0,   3.5,   0,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0,   1,   1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   5,   2,   0,   1,   0.5,   0,   0]]
     // CHECK-NEXT: 18
-    // CHECK-NEXT: ( 1, 1, 1, 1.5, 1, 3.1, 1, 0.5, 3.5, 2, 1, 1, 5, 2, 5, 2, 1, 0.5 )
+    // CHECK:      [1,  1,  1,  1.5,  1,  3.1,  1,  0.5,  3.5,  2,  1,  1,  5,  2,  5,  2,  1,  0.5
     %10 = call @concat_mix_sparse_dim1(%m42, %sm43cd, %sm44dc)
                : (tensor<4x2xf64>, tensor<4x3xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C>) -> tensor<4x9xf64, #MAT_C_C>
     call @dump_mat_4x9(%10) : (tensor<4x9xf64, #MAT_C_C>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 1, 0, 1, 0, 0, 1.5, 1 ), ( 3.1, 0, 1, 0, 0.5, 0, 3.5, 0, 0 ), ( 0, 2, 0, 0, 1, 1, 5, 2, 0 ), ( 0, 0, 5, 2, 0, 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   1,   0,   1,   0,   0,   1.5,   1],
+    // CHECK-NEXT:  [3.1,   0,   1,   0,   0.5,   0,   3.5,   0,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0,   1,   1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   5,   2,   0,   1,   0.5,   0,   0]]
     %11 = call @concat_mix_dense_dim1(%m42, %sm43cd, %sm44dc)
                : (tensor<4x2xf64>, tensor<4x3xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C>) -> tensor<4x9xf64>
     call @dump_mat_dense_4x9(%11) : (tensor<4x9xf64>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 1, 0, 1, 0, 0, 1.5, 1 ), ( 3.1, 0, 1, 0, 0.5, 0, 3.5, 0, 0 ), ( 0, 2, 0, 0, 1, 1, 5, 2, 0 ), ( 0, 0, 5, 2, 0, 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   1,   0,   1,   0,   0,   1.5,   1],
+    // CHECK-NEXT:  [3.1,   0,   1,   0,   0.5,   0,   3.5,   0,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0,   1,   1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   5,   2,   0,   1,   0.5,   0,   0]]
     // CHECK-NEXT: 18
-    // CHECK-NEXT: ( 1, 3.1, 2, 1, 1, 5, 2, 1, 0.5, 1, 1, 1, 3.5, 5, 0.5, 1.5, 2, 1 )
+    // CHECK:      [1,  3.1,  2,  1,  1,  5,  2,  1,  0.5,  1,  1,  1,  3.5,  5,  0.5,  1.5,  2,  1
     %12 = call @concat_sparse_sparse_perm_dim1(%sm42ccp, %sm43cd, %sm44dc)
                : (tensor<4x2xf64, #MAT_C_C_P>, tensor<4x3xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C>) -> tensor<4x9xf64, #MAT_C_C_P>
     call @dump_mat_perm_4x9(%12) : (tensor<4x9xf64, #MAT_C_C_P>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 1, 0, 1, 0, 0, 1.5, 1 ), ( 3.1, 0, 1, 0, 0.5, 0, 3.5, 0, 0 ), ( 0, 2, 0, 0, 1, 1, 5, 2, 0 ), ( 0, 0, 5, 2, 0, 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   1,   0,   1,   0,   0,   1.5,   1],
+    // CHECK-NEXT:  [3.1,   0,   1,   0,   0.5,   0,   3.5,   0,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0,   1,   1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   5,   2,   0,   1,   0.5,   0,   0]]
     %13 = call @concat_sparse_dense_perm_dim1(%sm42ccp, %sm43cdp, %sm44dc)
                : (tensor<4x2xf64, #MAT_C_C_P>, tensor<4x3xf64, #MAT_C_D_P>, tensor<4x4xf64, #MAT_D_C>) -> tensor<4x9xf64>
     call @dump_mat_dense_4x9(%13) : (tensor<4x9xf64>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 1, 0, 1, 0, 0, 1.5, 1 ), ( 3.1, 0, 1, 0, 0.5, 0, 3.5, 0, 0 ), ( 0, 2, 0, 0, 1, 1, 5, 2, 0 ), ( 0, 0, 5, 2, 0, 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   1,   0,   1,   0,   0,   1.5,   1],
+    // CHECK-NEXT:  [3.1,   0,   1,   0,   0.5,   0,   3.5,   0,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0,   1,   1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   5,   2,   0,   1,   0.5,   0,   0]]
     // CHECK-NEXT: 18
-    // CHECK-NEXT: ( 1, 1, 1, 1.5, 1, 3.1, 1, 0.5, 3.5, 2, 1, 1, 5, 2, 5, 2, 1, 0.5 )
+    // CHECK:      [1,  1,  1,  1.5,  1,  3.1,  1,  0.5,  3.5,  2,  1,  1,  5,  2,  5,  2,  1,  0.5
     %14 = call @concat_mix_sparse_perm_dim1(%m42, %sm43cdp, %sm44dc)
                : (tensor<4x2xf64>, tensor<4x3xf64, #MAT_C_D_P>, tensor<4x4xf64, #MAT_D_C>) -> tensor<4x9xf64, #MAT_C_C>
     call @dump_mat_4x9(%14) : (tensor<4x9xf64, #MAT_C_C>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 1, 0, 1, 0, 0, 1.5, 1 ), ( 3.1, 0, 1, 0, 0.5, 0, 3.5, 0, 0 ), ( 0, 2, 0, 0, 1, 1, 5, 2, 0 ), ( 0, 0, 5, 2, 0, 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   1,   0,   1,   0,   0,   1.5,   1],
+    // CHECK-NEXT:  [3.1,   0,   1,   0,   0.5,   0,   3.5,   0,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0,   1,   1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   5,   2,   0,   1,   0.5,   0,   0]]
     %15 = call @concat_mix_dense_perm_dim1(%m42, %sm43cd, %sm44dcp)
                : (tensor<4x2xf64>, tensor<4x3xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C_P>) -> tensor<4x9xf64>
     call @dump_mat_dense_4x9(%15) : (tensor<4x9xf64>) -> ()
 
-    // CHECK-NEXT: ( ( 1, 0, 1, 0, 1, 0, 0, 1.5, 1 ), ( 3.1, 0, 1, 0, 0.5, 0, 3.5, 0, 0 ), ( 0, 2, 0, 0, 1, 1, 5, 2, 0 ), ( 0, 0, 5, 2, 0, 1, 0.5, 0, 0 ) )
+    // CHECK:      {{\[}}[1,   0,   1,   0,   1,   0,   0,   1.5,   1],
+    // CHECK-NEXT:  [3.1,   0,   1,   0,   0.5,   0,   3.5,   0,   0],
+    // CHECK-NEXT:  [0,   2,   0,   0,   1,   1,   5,   2,   0],
+    // CHECK-NEXT:  [0,   0,   5,   2,   0,   1,   0.5,   0,   0]]
     // CHECK-NEXT: 18
-    // CHECK-NEXT: ( 1, 1, 1, 1.5, 1, 3.1, 1, 0.5, 3.5, 2, 1, 1, 5, 2, 5, 2, 1, 0.5 )
+    // CHECK:      [1,  1,  1,  1.5,  1,  3.1,  1,  0.5,  3.5,  2,  1,  1,  5,  2,  5,  2,  1,  0.5
     %16 = call @concat_mix_sparse_dyn(%m42, %sm43cd, %sm44dc)
                : (tensor<4x2xf64>, tensor<4x3xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C>) -> tensor<?x?xf64, #MAT_C_C>
     call @dump_mat_dyn(%16) : (tensor<?x?xf64, #MAT_C_C>) -> ()
 
     // CHECK-NEXT: 36
-    // CHECK-NEXT: ( 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 2, 0, 0.5, 5, 0, 3.5, 5, 0.5, 3, 0, 1, 0, 2, 1.5, 0, 2, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0 )
+    // CHECK:      [1,  0,  1,  0,  1,  0,  0,  1,  1,  0,  2,  0,  0.5,  5,  0,  3.5,  5,  0.5,  3,  0,  1,  0,  2,  1.5,  0,  2,  0,  0,  0,  1,  0,  0,  1,  0,  0,  0
     %17 = call @concat_sparse_annotated_dense(%sm24cc, %sm34cd, %sm44dc)
                : (tensor<2x4xf64, #MAT_C_C>, tensor<3x4xf64, #MAT_C_D>, tensor<4x4xf64, #MAT_D_C>) -> tensor<9x4xf64, #MAT_D_D>
     call @dump_mat_annotated_dense_9x4(%17) : (tensor<9x4xf64, #MAT_D_D>) -> ()