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

[wrengr]

Summary

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

[wrengr]

Fixing "Dialect/SparseTensor/sparse_tensor_reshape.mlir"

[wrengr]

Note: D150830 should fix what this differential missed

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

 // RUN: mlir-opt %s --linalg-generalize-named-ops \
 // RUN:             --sparsification="enable-gpu-libgen" | FileCheck %s
 
 #SortedCOO = #sparse_tensor.encoding<{
-  dimLevelType = [ "compressed-nu", "singleton" ]
+  lvlTypes = [ "compressed-nu", "singleton" ]
 }>
 
 module {
 
 // CHECK-LABEL:   func.func @matvec(
 // CHECK-SAME:      %[[VAL_0:.*]]: tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>>,
 // CHECK-SAME:      %[[VAL_1:.*]]: tensor<?xf64>,
 // CHECK-SAME:      %[[VAL_2:.*]]: tensor<?xf64>) -> tensor<?xf64> {

mlir/test/Dialect/SparseTensor/sparse_tensor_reshape.mlir

 // 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:.*]]:
 // CHECK-DAG:     %[[C25:.*]] = arith.constant 25 : index
 // CHECK-DAG:     %[[C10:.*]] = arith.constant 10 : index
 // CHECK-DAG:     %[[C0:.*]] = arith.constant 0 : index
 // CHECK-DAG:     %[[C1:.*]] = arith.constant 1 : index
 // CHECK:         %[[B:.*]] = bufferization.alloc_tensor()

 // CHECK:             %[[D:.*]] = arith.divui %[[DI]], %[[C10]] : index
 // CHECK:             %[[R:.*]] = arith.remui %[[DI]], %[[C10]] : index
 // CHECK:             %[[R1:.*]] = sparse_tensor.insert %[[SV]] into %[[A1]]{{\[}}%[[D]], %[[R]]]
 // CHECK:              scf.yield %[[R1]]
 // CHECK:            }
 // 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

 //
 // NOTE: this test requires gpu-sm80
 //
 // with RT lib (SoA COO):
 //
 // RUN: mlir-opt %s \
 // RUN:   --sparse-compiler="enable-runtime-library=true enable-gpu-libgen gpu-triple=nvptx64-nvidia-cuda gpu-chip=sm_80 gpu-features=+ptx71"  \
 // RUN: | mlir-cpu-runner \
 // RUN:   --shared-libs=%mlir_cuda_runtime \
 // RUN:   --shared-libs=%mlir_c_runner_utils \
 // RUN:   --e main --entry-point-result=void \
 // RUN: | FileCheck %s
 //
 // 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
 }>
 
 module {
   // Compute matrix vector y = Ax on COO with default index coordinates.
   func.func @matvecCOO(%A: tensor<?x?xf64, #SortedCOO>, %x: tensor<?xf64>, %y_in: tensor<?xf64>) -> tensor<?xf64> {
     %y_out = linalg.matvec