[mlir][sparse] Fixing GPU tests (followup to D150330)

The GPU tests weren't updated when rebasing D150330, so this patch fixes that.

Reviewed By: anlunx

Differential Revision: https://reviews.llvm.org/D150822

Author: wrengr

mlir/test/Dialect/SparseTensor/GPU/gpu_matvec_lib.mlir

@@ -2,7 +2,7 @@
 // RUN:             --sparsification="enable-gpu-libgen" | FileCheck %s
 
 #SortedCOO = #sparse_tensor.encoding<{
-  dimLevelType = [ "compressed-nu", "singleton" ]
+  lvlTypes = [ "compressed-nu", "singleton" ]
 }>
 
 module {

mlir/test/Dialect/SparseTensor/sparse_tensor_reshape.mlir

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --post-sparsification-rewrite="enable-runtime-library=false enable-convert=false" \
 // RUN: --cse --canonicalize  | FileCheck %s
 
-#SparseMatrix = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }>
+#SparseMatrix = #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "compressed" ] }>
 
 // CHECK:         func.func @sparse_reshape(
 // CHECK-SAME:    %[[S:.*]]:
@@ -35,11 +35,11 @@
 // CHECK:            scf.yield %[[RET_1]]
 // CHECK:         }
 // CHECK:        %[[NT1:.*]] = sparse_tensor.load %[[RET]] hasInserts
-// CHECK:        return %[[NT1]] : tensor<10x10xf64, #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }>>
+// CHECK:        return %[[NT1]] : tensor<10x10xf64, #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "compressed" ] }>>
 //
 func.func @sparse_reshape(%arg0: tensor<4x25xf64, #SparseMatrix>) -> tensor<10x10xf64, #SparseMatrix> {
   %shape = arith.constant dense <[ 10, 10 ]> : tensor<2xi32>
   %0 = tensor.reshape %arg0(%shape) :
     (tensor<4x25xf64, #SparseMatrix>, tensor<2xi32>) -> tensor<10x10xf64, #SparseMatrix>
   return %0 : tensor<10x10xf64, #SparseMatrix>
-}
+}

mlir/test/Integration/Dialect/SparseTensor/GPU/CUDA/sparse-matvec-lib.mlir

@@ -14,11 +14,11 @@
 // TODO: without RT lib (AoS COO):
 
 #SortedCOO = #sparse_tensor.encoding<{
-  dimLevelType = [ "compressed-nu", "singleton" ]
+  lvlTypes = [ "compressed-nu", "singleton" ]
 }>
 
 #CSR = #sparse_tensor.encoding<{
-  dimLevelType = [ "dense", "compressed" ],
+  lvlTypes = [ "dense", "compressed" ],
   posWidth = 32,
   crdWidth = 32
 }>