[mlir][sparse] Migrate more tests to new syntax (llvm#66309)

CSR:
`lvlTypes = [ "dense", "compressed" ]` to `map = (d0, d1) -> (d0 :
dense, d1 : compressed)`

CSC:
`lvlTypes = [ "dense", "compressed" ], dimToLvl = affine_map<(d0, d1) ->
(d1, d0)>` to `map = (d0, d1) -> (d1 : dense, d0 : compressed)`

This is an ongoing effort: llvm#66146

Author: yinying-lisa-li

mlir/test/Dialect/Bufferization/ops.mlir

@@ -2,7 +2,7 @@
 // RUN: mlir-opt %s --mlir-print-op-generic | mlir-opt | FileCheck %s
 
 #CSR = #sparse_tensor.encoding<{
-  lvlTypes = ["dense", "compressed"]
+  map = (d0, d1) -> (d0 : dense, d1 : compressed)
 }>
 
 // CHECK-LABEL: func @test_clone

mlir/test/Dialect/Linalg/drop-unit-extent-dims.mlir

@@ -854,7 +854,7 @@ func.func @input_stays_same(%arg0 : memref<?x1x?xf32, strided<[?, 1, 1]>>, %arg1
   iterator_types = ["parallel", "reduction"]
 }
 
-#CSR = #sparse_tensor.encoding<{ lvlTypes = ["dense", "compressed"] }>
+#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
 
 func.func @sparse_case(%arg0: tensor<8x8xf32, #CSR>, %arg1: tensor<8xf32>) -> tensor<8xf32> {
     %0 = tensor.empty() : tensor<8xf32>

mlir/test/Dialect/SparseTensor/GPU/gpu_combi.mlir

@@ -3,7 +3,7 @@
 // RUN:             --sparsification="parallelization-strategy=dense-outer-loop" \
 // RUN:             --sparse-gpu-codegen | FileCheck %s
 
-#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
+#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
 
 //
 // CHECK-LABEL: gpu.module @sparse_kernels

mlir/test/Dialect/SparseTensor/GPU/gpu_matmul.mlir

@@ -3,7 +3,7 @@
 // RUN:             --sparsification="parallelization-strategy=dense-outer-loop" \
 // RUN:             --sparse-gpu-codegen | FileCheck %s
 
-#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
+#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
 
 //
 // Compute matrix matrix C = AB

mlir/test/Dialect/SparseTensor/GPU/gpu_matmul_lib.mlir

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --linalg-generalize-named-ops \
 // RUN:             --sparsification="enable-gpu-libgen" | FileCheck %s
 
-#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
+#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
 
 //
 // Compute matrix matrix C = AB

mlir/test/Dialect/SparseTensor/GPU/gpu_matvec.mlir

@@ -3,7 +3,7 @@
 // RUN:             --sparsification="parallelization-strategy=dense-outer-loop" \
 // RUN:             --sparse-gpu-codegen | FileCheck %s
 
-#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
+#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
 
 //
 // Compute matrix vector y = Ax

mlir/test/Dialect/SparseTensor/GPU/gpu_sampled_matmul_lib.mlir

@@ -19,7 +19,7 @@
   iterator_types = ["parallel", "parallel"]
 }
 
-#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
+#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
 
 // CHECK-LABEL:   func.func @sparse_sampled_dd(
 // CHECK-SAME:                                 %[[VAL_0:.*]]: tensor<8x8xf64, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>>,

mlir/test/Dialect/SparseTensor/GPU/gpu_spgemm_lib.mlir

@@ -1,7 +1,7 @@
 // RUN: mlir-opt %s --linalg-generalize-named-ops \
 // RUN:             --sparsification="enable-gpu-libgen" | FileCheck %s
 
-#CSR = #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>
+#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
 
 // CHECK-LABEL: func.func @matmulCSR(
 // CHECK-SAME:      %[[VAL_0:.*0]]: tensor<8x8xf32, #{{.*}}>,

mlir/test/Dialect/SparseTensor/codegen.mlir

@@ -21,7 +21,7 @@
 }>
 
 #CSR = #sparse_tensor.encoding<{
-  lvlTypes = [ "dense", "compressed" ],
+  map = (d0, d1) -> (d0 : dense, d1 : compressed),
   crdWidth = 64,
   posWidth = 32
 }>
@@ -31,8 +31,7 @@
 }>
 
 #CSC = #sparse_tensor.encoding<{
-  lvlTypes = [ "dense", "compressed" ],
-  dimToLvl = affine_map<(i, j) -> (j, i)>
+  map = (d0, d1) -> (d1 : dense, d0 : compressed)
 }>
 
 #DCSR = #sparse_tensor.encoding<{

mlir/test/Dialect/SparseTensor/codegen_sparse_alloc.mlir

@@ -1,6 +1,6 @@
 // RUN: mlir-opt %s --sparse-tensor-codegen --canonicalize --cse | FileCheck %s
 
-#CSR = #sparse_tensor.encoding<{ lvlTypes = ["dense", "compressed"]}>
+#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed)}>
 #COO = #sparse_tensor.encoding<{ lvlTypes = ["compressed_nu", "singleton"]}>
 
 // CHECK-LABEL:   func.func @sparse_alloc_copy_CSR(