[Mlir-commits] [mlir] c5a67e1 - [mlir][sparse] Use variable instead of inlining sparse encoding (#72561)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Thu Nov 16 16:30:25 PST 2023
Author: Yinying Li
Date: 2023-11-16T19:30:21-05:00
New Revision: c5a67e16b6117d0c37d004dd5467b56be006ad8f
URL: https://github.com/llvm/llvm-project/commit/c5a67e16b6117d0c37d004dd5467b56be006ad8f
DIFF: https://github.com/llvm/llvm-project/commit/c5a67e16b6117d0c37d004dd5467b56be006ad8f.diff
LOG: [mlir][sparse] Use variable instead of inlining sparse encoding (#72561)
Example:
#CSR = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : dense, d1 : compressed),
}>
// CHECK: #[[$CSR.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0
: dense, d1 : compressed) }>
// CHECK-LABEL: func private @sparse_csr(
// CHECK-SAME: tensor<?x?xf32, **#[[$CSR]]**>)
func.func private @sparse_csr(tensor<?x?xf32, #CSR>)
Added:
Modified:
mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
mlir/test/Dialect/SparseTensor/GPU/gpu_matmul_lib.mlir
mlir/test/Dialect/SparseTensor/GPU/gpu_matvec_lib.mlir
mlir/test/Dialect/SparseTensor/GPU/gpu_sampled_matmul_lib.mlir
mlir/test/Dialect/SparseTensor/GPU/gpu_sddmm_lib.mlir
mlir/test/Dialect/SparseTensor/codegen.mlir
mlir/test/Dialect/SparseTensor/dense.mlir
mlir/test/Dialect/SparseTensor/fold.mlir
mlir/test/Dialect/SparseTensor/one_trip.mlir
mlir/test/Dialect/SparseTensor/pre_rewriting.mlir
mlir/test/Dialect/SparseTensor/rejected.mlir
mlir/test/Dialect/SparseTensor/rewriting_for_codegen.mlir
mlir/test/Dialect/SparseTensor/roundtrip.mlir
mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir
mlir/test/Dialect/SparseTensor/semi_ring.mlir
mlir/test/Dialect/SparseTensor/sorted_coo.mlir
mlir/test/Dialect/SparseTensor/sparse_1d.mlir
mlir/test/Dialect/SparseTensor/sparse_2d.mlir
mlir/test/Dialect/SparseTensor/sparse_3d.mlir
mlir/test/Dialect/SparseTensor/sparse_affine.mlir
mlir/test/Dialect/SparseTensor/sparse_concat.mlir
mlir/test/Dialect/SparseTensor/sparse_conv_2d_slice_based.mlir
mlir/test/Dialect/SparseTensor/sparse_extract_slice.mlir
mlir/test/Dialect/SparseTensor/sparse_foreach.mlir
mlir/test/Dialect/SparseTensor/sparse_fp_ops.mlir
mlir/test/Dialect/SparseTensor/sparse_index.mlir
mlir/test/Dialect/SparseTensor/sparse_int_ops.mlir
mlir/test/Dialect/SparseTensor/sparse_kernels.mlir
mlir/test/Dialect/SparseTensor/sparse_lower.mlir
mlir/test/Dialect/SparseTensor/sparse_lower_col.mlir
mlir/test/Dialect/SparseTensor/sparse_lower_inplace.mlir
mlir/test/Dialect/SparseTensor/sparse_nd.mlir
mlir/test/Dialect/SparseTensor/sparse_out.mlir
mlir/test/Dialect/SparseTensor/sparse_pack.mlir
mlir/test/Dialect/SparseTensor/sparse_parallel_reduce.mlir
mlir/test/Dialect/SparseTensor/sparse_perm.mlir
mlir/test/Dialect/SparseTensor/sparse_perm_lower.mlir
mlir/test/Dialect/SparseTensor/sparse_reinterpret_map.mlir
mlir/test/Dialect/SparseTensor/sparse_reshape.mlir
mlir/test/Dialect/SparseTensor/sparse_scalars.mlir
mlir/test/Dialect/SparseTensor/sparse_sddmm.mlir
mlir/test/Dialect/SparseTensor/sparse_sddmm_org.mlir
mlir/test/Dialect/SparseTensor/sparse_tensor_reshape.mlir
mlir/test/Dialect/SparseTensor/sparse_transpose.mlir
mlir/test/Dialect/SparseTensor/sparse_vector_chain.mlir
mlir/test/Dialect/SparseTensor/sparse_vector_index.mlir
mlir/test/Dialect/SparseTensor/spy_sddmm.mlir
mlir/test/Dialect/SparseTensor/unused-tensor.mlir
mlir/test/Dialect/SparseTensor/vectorize_reduction.mlir
Removed:
################################################################################
diff --git a/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp b/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
index 53a0c2428842f59..28445ce2a8bc243 100644
--- a/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
+++ b/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
@@ -1797,7 +1797,22 @@ Operation *SparseTensorDialect::materializeConstant(OpBuilder &builder,
return nullptr;
}
+namespace {
+struct SparseTensorAsmDialectInterface : public OpAsmDialectInterface {
+ using OpAsmDialectInterface::OpAsmDialectInterface;
+
+ AliasResult getAlias(Attribute attr, raw_ostream &os) const override {
+ if (attr.isa<SparseTensorEncodingAttr>()) {
+ os << "sparse";
+ return AliasResult::OverridableAlias;
+ }
+ return AliasResult::NoAlias;
+ }
+};
+} // namespace
+
void SparseTensorDialect::initialize() {
+ addInterface<SparseTensorAsmDialectInterface>();
addAttributes<
#define GET_ATTRDEF_LIST
#include "mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.cpp.inc"
diff --git a/mlir/test/Dialect/SparseTensor/GPU/gpu_matmul_lib.mlir b/mlir/test/Dialect/SparseTensor/GPU/gpu_matmul_lib.mlir
index 34189d329cc41ee..699508acf13cf75 100644
--- a/mlir/test/Dialect/SparseTensor/GPU/gpu_matmul_lib.mlir
+++ b/mlir/test/Dialect/SparseTensor/GPU/gpu_matmul_lib.mlir
@@ -6,18 +6,18 @@
// Compute matrix matrix C = AB
//
// CHECK-LABEL: func.func @matmul(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<?x?xf64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<?x?xf64>) -> tensor<?x?xf64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.number_of_entries %[[VAL_0]] : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_6:.*]] = tensor.dim %[[VAL_0]], %[[VAL_3]] : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_7:.*]] = tensor.dim %[[VAL_0]], %[[VAL_4]] : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.number_of_entries %[[VAL_0]] : tensor<?x?xf64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_6:.*]] = tensor.dim %[[VAL_0]], %[[VAL_3]] : tensor<?x?xf64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_7:.*]] = tensor.dim %[[VAL_0]], %[[VAL_4]] : tensor<?x?xf64, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_8:.*]] = tensor.dim %[[VAL_1]], %[[VAL_4]] : tensor<?x?xf64>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_12:.*]] = gpu.wait async
// CHECK: %[[VAL_13:.*]] = memref.dim %[[VAL_9]], %[[VAL_3]] : memref<?xindex>
// CHECK: %[[VAL_14:.*]], %[[VAL_15:.*]] = gpu.alloc async {{\[}}%[[VAL_12]]] (%[[VAL_13]]) : memref<?xindex>
diff --git a/mlir/test/Dialect/SparseTensor/GPU/gpu_matvec_lib.mlir b/mlir/test/Dialect/SparseTensor/GPU/gpu_matvec_lib.mlir
index bd0bf6927b0da4c..14a0e9c30b20167 100644
--- a/mlir/test/Dialect/SparseTensor/GPU/gpu_matvec_lib.mlir
+++ b/mlir/test/Dialect/SparseTensor/GPU/gpu_matvec_lib.mlir
@@ -7,17 +7,17 @@
module {
// CHECK-LABEL: func.func @matvec(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<?xf64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<?xf64>) -> tensor<?xf64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.number_of_entries %[[VAL_0]] : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_6:.*]] = tensor.dim %[[VAL_0]], %[[VAL_3]] : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_7:.*]] = tensor.dim %[[VAL_0]], %[[VAL_4]] : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex, strided<[?], offset: ?>>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex, strided<[?], offset: ?>>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.number_of_entries %[[VAL_0]] : tensor<?x?xf64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_6:.*]] = tensor.dim %[[VAL_0]], %[[VAL_3]] : tensor<?x?xf64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_7:.*]] = tensor.dim %[[VAL_0]], %[[VAL_4]] : tensor<?x?xf64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf64, #sparse{{[0-9]*}}> to memref<?xindex, strided<[?], offset: ?>>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse{{[0-9]*}}> to memref<?xindex, strided<[?], offset: ?>>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_11:.*]] = gpu.wait async
// CHECK: %[[VAL_12:.*]] = memref.dim %[[VAL_8]], %[[VAL_3]] : memref<?xindex, strided<[?], offset: ?>>
// CHECK: %[[VAL_13:.*]], %[[VAL_14:.*]] = gpu.alloc async {{\[}}%[[VAL_11]]] (%[[VAL_12]]) : memref<?xindex>
diff --git a/mlir/test/Dialect/SparseTensor/GPU/gpu_sampled_matmul_lib.mlir b/mlir/test/Dialect/SparseTensor/GPU/gpu_sampled_matmul_lib.mlir
index ce7af53bb346278..97f36d49927bf9b 100644
--- a/mlir/test/Dialect/SparseTensor/GPU/gpu_sampled_matmul_lib.mlir
+++ b/mlir/test/Dialect/SparseTensor/GPU/gpu_sampled_matmul_lib.mlir
@@ -22,12 +22,12 @@
#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<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<8x8xf64>,
-// CHECK-SAME: %[[VAL_2:.*]]: tensor<8x8xf64>) -> tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_2:.*]]: tensor<8x8xf64>) -> tensor<8x8xf64, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.number_of_entries %[[VAL_0]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.number_of_entries %[[VAL_0]] : tensor<8x8xf64, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_1]] : memref<8x8xf64>
// CHECK: %[[VAL_7:.*]] = gpu.wait async
// CHECK: %[[VAL_8:.*]], %[[VAL_9:.*]] = gpu.alloc async {{\[}}%[[VAL_7]]] () : memref<8x8xf64>
@@ -36,9 +36,9 @@
// CHECK: %[[VAL_12:.*]] = gpu.wait async
// CHECK: %[[VAL_13:.*]], %[[VAL_14:.*]] = gpu.alloc async {{\[}}%[[VAL_12]]] () : memref<8x8xf64>
// CHECK: %[[VAL_15:.*]] = gpu.memcpy async {{\[}}%[[VAL_14]]] %[[VAL_13]], %[[VAL_11]] : memref<8x8xf64>, memref<8x8xf64>
-// CHECK: %[[VAL_16:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_17:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_18:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK: %[[VAL_16:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_17:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_18:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_19:.*]] = gpu.wait async
// CHECK: %[[VAL_20:.*]] = memref.dim %[[VAL_16]], %[[VAL_4]] : memref<?xindex>
// CHECK: %[[VAL_21:.*]], %[[VAL_22:.*]] = gpu.alloc async {{\[}}%[[VAL_19]]] (%[[VAL_20]]) : memref<?xindex>
@@ -70,8 +70,8 @@
// CHECK: %[[VAL_57:.*]] = gpu.memcpy async {{\[}}%[[VAL_56]]] %[[VAL_18]], %[[VAL_31]] : memref<?xf64>, memref<?xf64>
// CHECK: %[[VAL_58:.*]] = gpu.dealloc async {{\[}}%[[VAL_57]]] %[[VAL_31]] : memref<?xf64>
// CHECK: gpu.wait {{\[}}%[[VAL_58]]]
-// CHECK: %[[VAL_59:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_59]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_59:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<8x8xf64, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_59]] : tensor<8x8xf64, #sparse{{[0-9]*}}>
// CHECK: }
//
// A kernel that computes a direct sampled matrix matrix multiplication
diff --git a/mlir/test/Dialect/SparseTensor/GPU/gpu_sddmm_lib.mlir b/mlir/test/Dialect/SparseTensor/GPU/gpu_sddmm_lib.mlir
index dd79a9017f7f4cb..93f49002a47d2db 100644
--- a/mlir/test/Dialect/SparseTensor/GPU/gpu_sddmm_lib.mlir
+++ b/mlir/test/Dialect/SparseTensor/GPU/gpu_sddmm_lib.mlir
@@ -19,14 +19,14 @@
}
// CHECK-LABEL: func.func @SDDMM_block(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<?x?xf32>,
-// CHECK-SAME: %[[VAL_2:.*]]: tensor<?x?xf32>) -> tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_2:.*]]: tensor<?x?xf32>) -> tensor<?x?xf32, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 4 : index
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.number_of_entries %[[VAL_0]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.number_of_entries %[[VAL_0]] : tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_8:.*]] = tensor.dim %[[VAL_1]], %[[VAL_3]] : tensor<?x?xf32>
// CHECK: %[[VAL_9:.*]] = tensor.dim %[[VAL_1]], %[[VAL_4]] : tensor<?x?xf32>
// CHECK: %[[VAL_10:.*]] = tensor.dim %[[VAL_2]], %[[VAL_4]] : tensor<?x?xf32>
@@ -79,8 +79,8 @@
// CHECK: %[[VAL_66:.*]] = gpu.memcpy async {{\[}}%[[VAL_65]]] %[[VAL_27]], %[[VAL_40]] : memref<?xf32>, memref<?xf32>
// CHECK: %[[VAL_67:.*]] = gpu.dealloc async {{\[}}%[[VAL_66]]] %[[VAL_40]] : memref<?xf32>
// CHECK: gpu.wait {{\[}}%[[VAL_67]]]
-// CHECK: %[[VAL_68:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_68]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_68:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<?x?xf32, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_68]] : tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: }
func.func @SDDMM_block(%args: tensor<?x?xf32, #BSR>,
%arga: tensor<?x?xf32>,
diff --git a/mlir/test/Dialect/SparseTensor/codegen.mlir b/mlir/test/Dialect/SparseTensor/codegen.mlir
index 5876eef6f193272..12d77ecfecc6ac9 100644
--- a/mlir/test/Dialect/SparseTensor/codegen.mlir
+++ b/mlir/test/Dialect/SparseTensor/codegen.mlir
@@ -664,7 +664,7 @@ func.func @sparse_convert_element_type(%arg0: tensor<32xf32, #SparseVector>) ->
}
// CHECK-LABEL: func.func @sparse_new_coo(
-// CHECK-SAME: %[[A0:.*]]: !llvm.ptr) -> (memref<?xindex>, memref<?xindex>, memref<?xf32>, !sparse_tensor.storage_specifier<#sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK-SAME: %[[A0:.*]]: !llvm.ptr) -> (memref<?xindex>, memref<?xindex>, memref<?xf32>, !sparse_tensor.storage_specifier<#sparse{{[0-9]*}}>) {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant false
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2 : i32
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
@@ -712,7 +712,7 @@ func.func @sparse_new_coo(%arg0: !llvm.ptr) -> tensor<?x?xf32, #Coo> {
}
// CHECK-LABEL: func.func @sparse_new_coo_permute_no(
-// CHECK-SAME: %[[A0:.*]]: !llvm.ptr) -> (memref<?xindex>, memref<?xindex>, memref<?xf32>, !sparse_tensor.storage_specifier<#sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK-SAME: %[[A0:.*]]: !llvm.ptr) -> (memref<?xindex>, memref<?xindex>, memref<?xf32>, !sparse_tensor.storage_specifier<#sparse{{[0-9]*}}>) {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 2 : i32
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
diff --git a/mlir/test/Dialect/SparseTensor/dense.mlir b/mlir/test/Dialect/SparseTensor/dense.mlir
index 52db814572a15fb..2d8dcfea9adc194 100644
--- a/mlir/test/Dialect/SparseTensor/dense.mlir
+++ b/mlir/test/Dialect/SparseTensor/dense.mlir
@@ -32,14 +32,14 @@
// a non-annotated dense matrix as output.
//
// CHECK-LABEL: func @dense1(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 1.000000e+00 : f32
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 16 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xf32>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK: scf.for %[[VAL_9:.*]] = %[[VAL_5]] to %[[VAL_3]] step %[[VAL_6]] {
// CHECK: scf.for %[[VAL_10:.*]] = %[[VAL_5]] to %[[VAL_4]] step %[[VAL_6]] {
@@ -73,14 +73,14 @@ func.func @dense1(%arga: tensor<32x16xf32, #DenseMatrix>,
//
// CHECK-LABEL: func @dense2(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>>) -> tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> {
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>) -> tensor<32x16xf32, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 1.000000e+00 : f32
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 16 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
// CHECK: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_0]] : memref<32x16xf32>
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xf32>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: scf.for %[[VAL_9:.*]] = %[[VAL_5]] to %[[VAL_3]] step %[[VAL_6]] {
// CHECK: scf.for %[[VAL_10:.*]] = %[[VAL_5]] to %[[VAL_4]] step %[[VAL_6]] {
// CHECK: %[[VAL_11:.*]] = arith.muli %[[VAL_9]], %[[VAL_4]] : index
@@ -90,8 +90,8 @@ func.func @dense1(%arga: tensor<32x16xf32, #DenseMatrix>,
// CHECK: memref.store %[[VAL_14]], %[[VAL_8]]{{\[}}%[[VAL_12]]] : memref<?xf32>
// CHECK: }
// CHECK: }
-// CHECK: %[[VAL_15:.*]] = sparse_tensor.load %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>>
-// CHECK: return %[[VAL_15]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>>
+// CHECK: %[[VAL_15:.*]] = sparse_tensor.load %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_15]] : tensor<32x16xf32, #sparse{{[0-9]*}}>
// CHECK: }
func.func @dense2(%arga: tensor<32x16xf32>,
%argx: tensor<32x16xf32, #DenseMatrix>)
@@ -116,14 +116,14 @@ func.func @dense2(%arga: tensor<32x16xf32>,
//
// CHECK-LABEL: func @dense3(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>>) -> tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> {
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>) -> tensor<32x16xf32, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 16 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
// CHECK: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_0]] : memref<32x16x8xf32>
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}}>> to memref<?xf32>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: scf.for %[[VAL_9:.*]] = %[[VAL_5]] to %[[VAL_3]] step %[[VAL_6]] {
// CHECK: scf.for %[[VAL_10:.*]] = %[[VAL_5]] to %[[VAL_4]] step %[[VAL_6]] {
// CHECK: %[[VAL_11:.*]] = arith.muli %[[VAL_9]], %[[VAL_4]] : index
@@ -137,8 +137,8 @@ func.func @dense2(%arga: tensor<32x16xf32>,
// CHECK: memref.store %[[VAL_19:.*]], %[[VAL_8]]{{\[}}%[[VAL_12]]] : memref<?xf32>
// CHECK: }
// CHECK: }
-// CHECK: %[[VAL_20:.*]] = sparse_tensor.load %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>>
-// CHECK: return %[[VAL_20]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>>
+// CHECK: %[[VAL_20:.*]] = sparse_tensor.load %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_20]] : tensor<32x16xf32, #sparse{{[0-9]*}}>
// CHECK: }
func.func @dense3(%arga: tensor<32x16x8xf32>,
%argx: tensor<32x16xf32, #DenseMatrix>)
diff --git a/mlir/test/Dialect/SparseTensor/fold.mlir b/mlir/test/Dialect/SparseTensor/fold.mlir
index 73851c086aa2425..0153d444215e3e9 100644
--- a/mlir/test/Dialect/SparseTensor/fold.mlir
+++ b/mlir/test/Dialect/SparseTensor/fold.mlir
@@ -21,7 +21,7 @@ func.func @sparse_dce_convert(%arg0: tensor<64xf32>) {
}
// CHECK-LABEL: func @sparse_dce_getters(
-// CHECK-SAME: %[[A:.*]]: tensor<64xf32, #sparse_tensor.encoding<{{{.*}}}>>)
+// CHECK-SAME: %[[A:.*]]: tensor<64xf32, #sparse{{[0-9]*}}>)
// CHECK-NOT: sparse_tensor.positions
// CHECK-NOT: sparse_tensor.coordinates
// CHECK-NOT: sparse_tensor.values
@@ -68,7 +68,7 @@ func.func @sparse_get_specifier_dce_fold(%arg0: !sparse_tensor.storage_specifier
#COO = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)}>
// CHECK-LABEL: func @sparse_reorder_coo(
-// CHECK-SAME: %[[A:.*]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-SAME: %[[A:.*]]: tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK-NOT: %[[R:.*]] = sparse_tensor.reorder_coo
// CHECK: return %[[A]]
func.func @sparse_reorder_coo(%arg0 : tensor<?x?xf32, #COO>) -> tensor<?x?xf32, #COO> {
diff --git a/mlir/test/Dialect/SparseTensor/one_trip.mlir b/mlir/test/Dialect/SparseTensor/one_trip.mlir
index b8ab177357492d8..9d2a125dbef171d 100644
--- a/mlir/test/Dialect/SparseTensor/one_trip.mlir
+++ b/mlir/test/Dialect/SparseTensor/one_trip.mlir
@@ -13,15 +13,15 @@
}
// CHECK-LABEL: func.func @sparse_scale(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1xf32, #sparse_tensor.encoding<{{{.*}}}>>)
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1xf32, #sparse{{[0-9]*}}>)
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2.000000e+00 : f32
-// CHECK: %[[VAL_3:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<1x1xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK: %[[VAL_3:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<1x1xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: %[[VAL_4:.*]] = memref.load %[[VAL_3]]{{\[}}%[[VAL_1]]] : memref<?xf32>
// CHECK: %[[VAL_5:.*]] = arith.mulf %[[VAL_4]], %[[VAL_2]] : f32
// CHECK: memref.store %[[VAL_5]], %[[VAL_3]]{{\[}}%[[VAL_1]]] : memref<?xf32>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<1x1xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_6]] : tensor<1x1xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<1x1xf32, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_6]] : tensor<1x1xf32, #sparse{{[0-9]*}}>
func.func @sparse_scale(%argx: tensor<1x1xf32, #Dense>) -> tensor<1x1xf32, #Dense> {
%c = arith.constant 2.0 : f32
%0 = linalg.generic #trait_scale
diff --git a/mlir/test/Dialect/SparseTensor/pre_rewriting.mlir b/mlir/test/Dialect/SparseTensor/pre_rewriting.mlir
index c2cab30edec9180..5fdbb46e3d8b085 100644
--- a/mlir/test/Dialect/SparseTensor/pre_rewriting.mlir
+++ b/mlir/test/Dialect/SparseTensor/pre_rewriting.mlir
@@ -27,8 +27,8 @@
}
// CHECK-LABEL: func @sparse_nop_cast(
-// CHECK-SAME: %[[A:.*]]: tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>>)
-// CHECK: return %[[A]] : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-SAME: %[[A:.*]]: tensor<?xf32, #sparse{{[0-9]*}}>)
+// CHECK: return %[[A]] : tensor<?xf32, #sparse{{[0-9]*}}>
func.func @sparse_nop_cast(%a : tensor<?xf32, #SparseVector>) -> tensor<?xf32, #SparseVector> {
%0 = tensor.cast %a : tensor<?xf32, #SparseVector> to tensor<?xf32, #SparseVector>
%1 = tensor.cast %0 : tensor<?xf32, #SparseVector> to tensor<?xf32, #SparseVector>
@@ -38,18 +38,18 @@ func.func @sparse_nop_cast(%a : tensor<?xf32, #SparseVector>) -> tensor<?xf32, #
// CHECK-LABEL: func @sparse_repair_cast(
// CHECK-SAME: %[[A:.*]]: tensor<?xf32>)
-// CHECK: %[[C:.*]] = sparse_tensor.convert %[[A]] : tensor<?xf32> to tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>
-// CHECK: return %[[C]] : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[C:.*]] = sparse_tensor.convert %[[A]] : tensor<?xf32> to tensor<?xf32, #sparse{{[0-9]*}}>
+// CHECK: return %[[C]] : tensor<?xf32, #sparse{{[0-9]*}}>
func.func @sparse_repair_cast(%a : tensor<?xf32>) -> tensor<?xf32, #SparseVector> {
%0 = tensor.cast %a : tensor<?xf32> to tensor<?xf32, #SparseVector>
return %0 : tensor<?xf32, #SparseVector>
}
// CHECK-LABEL: func @sparse_fuse_slice(
-// CHECK-SAME: %[[A:.*]]: tensor<2x3xi64, #sparse_tensor.encoding<{{{.*}}}>>)
-// CHECK: %[[E:.*]] = tensor.extract_slice %[[A]][1, 0] [1, 3] [1, 1] : tensor<2x3xi64, #sparse_tensor.encoding<{{{.*}}}>> to tensor<1x3xi64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[C:.*]] = sparse_tensor.convert %[[E]] : tensor<1x3xi64, #sparse_tensor.encoding<{{{.*}}}>> to tensor<1x3xi64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[C]] : tensor<1x3xi64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-SAME: %[[A:.*]]: tensor<2x3xi64, #sparse{{[0-9]*}}>)
+// CHECK: %[[E:.*]] = tensor.extract_slice %[[A]][1, 0] [1, 3] [1, 1] : tensor<2x3xi64, #sparse{{[0-9]*}}> to tensor<1x3xi64, #sparse{{[0-9]*}}>
+// CHECK: %[[C:.*]] = sparse_tensor.convert %[[E]] : tensor<1x3xi64, #sparse{{[0-9]*}}> to tensor<1x3xi64, #sparse{{[0-9]*}}>
+// CHECK: return %[[C]] : tensor<1x3xi64, #sparse{{[0-9]*}}>
func.func @sparse_fuse_slice(%a : tensor<2x3xi64, #SortedCOO>) -> tensor<1x3xi64, #SortedCOO> {
%extracted_slice = tensor.extract_slice %a[1, 0] [1, 3] [1, 1] : tensor<2x3xi64, #SortedCOO> to tensor<1x3xi64>
%cast = tensor.cast %extracted_slice : tensor<1x3xi64> to tensor<1x3xi64, #Slice>
@@ -59,10 +59,10 @@ func.func @sparse_fuse_slice(%a : tensor<2x3xi64, #SortedCOO>) -> tensor<1x3xi64
// CHECK-LABEL: func.func @sparse_select(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<4x4xi1>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<4x4xf64, #sparse_tensor.encoding<{{.*}}>>,
-// CHECK-SAME: %[[VAL_2:.*]]: tensor<4x4xf64, #sparse_tensor.encoding<{{.*}}>>) -> tensor<4x4xf64, #sparse_tensor.encoding<{{.*}}>> {
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<4x4xf64, #sparse{{[0-9]*}}>,
+// CHECK-SAME: %[[VAL_2:.*]]: tensor<4x4xf64, #sparse{{[0-9]*}}>) -> tensor<4x4xf64, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0.000000e+00 : f64
-// CHECK-DAG: %[[VAL_4:.*]] = tensor.empty() : tensor<4x4xf64, #sparse_tensor.encoding<{{.*}}>>
+// CHECK-DAG: %[[VAL_4:.*]] = tensor.empty() : tensor<4x4xf64, #sparse{{[0-9]*}}>
// CHECK-NEXT: %[[VAL_5:.*]] = linalg.generic {indexing_maps = [#map, #map, #map, #map], iterator_types = ["parallel", "parallel"]}
// CHECK-SAME: ins(%[[VAL_0]], %[[VAL_1]], %[[VAL_2]]
// CHECK-NEXT: ^bb0(%[[VAL_6:.*]]: i1, %[[VAL_7:.*]]: f64, %[[VAL_8:.*]]: f64, %[[VAL_9:.*]]: f64):
@@ -83,8 +83,8 @@ func.func @sparse_fuse_slice(%a : tensor<2x3xi64, #SortedCOO>) -> tensor<1x3xi64
// CHECK-NEXT: sparse_tensor.yield %[[VAL_17]] : f64
// CHECK-NEXT: }
// CHECK-NEXT: linalg.yield %[[VAL_10]] : f64
-// CHECK-NEXT: } -> tensor<4x4xf64, #sparse_tensor.encoding<{{.*}}>>
-// CHECK-NEXT: return %[[VAL_18:.*]] : tensor<4x4xf64, #sparse_tensor.encoding<{{.*}}>>
+// CHECK-NEXT: } -> tensor<4x4xf64, #sparse{{[0-9]*}}>
+// CHECK-NEXT: return %[[VAL_18:.*]] : tensor<4x4xf64, #sparse{{[0-9]*}}>
// CHECK-NEXT: }
func.func @sparse_select(%cond: tensor<4x4xi1>,
%arga: tensor<4x4xf64, #DCSR>,
diff --git a/mlir/test/Dialect/SparseTensor/rejected.mlir b/mlir/test/Dialect/SparseTensor/rejected.mlir
index c68c576766b8566..c3cbde9703bb1ee 100644
--- a/mlir/test/Dialect/SparseTensor/rejected.mlir
+++ b/mlir/test/Dialect/SparseTensor/rejected.mlir
@@ -15,7 +15,7 @@
// CHECK-LABEL: func.func @sparse_reduction_subi(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<i32>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<i32> {
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse{{[0-9]*}}>) -> tensor<i32> {
// CHECK: %[[VAL_2:.*]] = linalg.generic
// CHECK: ^bb0(%[[VAL_3:.*]]: i32, %[[VAL_4:.*]]: i32):
// CHECK: %[[VAL_5:.*]] = arith.subi %[[VAL_3]], %[[VAL_4]] : i32
diff --git a/mlir/test/Dialect/SparseTensor/rewriting_for_codegen.mlir b/mlir/test/Dialect/SparseTensor/rewriting_for_codegen.mlir
index 579b0f20f5f6842..11fc502822539b0 100644
--- a/mlir/test/Dialect/SparseTensor/rewriting_for_codegen.mlir
+++ b/mlir/test/Dialect/SparseTensor/rewriting_for_codegen.mlir
@@ -14,8 +14,8 @@
}>
// CHECK-LABEL: func.func @sparse_new(
-// CHECK-SAME: %[[A:.*]]: !llvm.ptr) -> tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> {
-// CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr to tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-SAME: %[[A:.*]]: !llvm.ptr) -> tensor<?x?xf32, #sparse{{[0-9]*}}> {
+// CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr to tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: %[[R:.*]] = sparse_tensor.convert %[[COO]]
// CHECK: bufferization.dealloc_tensor %[[COO]]
// CHECK: return %[[R]]
@@ -25,8 +25,8 @@ func.func @sparse_new(%arg0: !llvm.ptr) -> tensor<?x?xf32, #CSR> {
}
// CHECK-LABEL: func.func @sparse_new_csc(
-// CHECK-SAME: %[[A:.*]]: !llvm.ptr) -> tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> {
-// CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr to tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-SAME: %[[A:.*]]: !llvm.ptr) -> tensor<?x?xf32, #sparse{{[0-9]*}}> {
+// CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr to tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: %[[R:.*]] = sparse_tensor.convert %[[COO]]
// CHECK: bufferization.dealloc_tensor %[[COO]]
// CHECK: return %[[R]]
@@ -36,8 +36,8 @@ func.func @sparse_new_csc(%arg0: !llvm.ptr) -> tensor<?x?xf32, #CSC> {
}
// CHECK-LABEL: func.func @sparse_new_coo(
-// CHECK-SAME: %[[A:.*]]: !llvm.ptr) -> tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> {
-// CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr to tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-SAME: %[[A:.*]]: !llvm.ptr) -> tensor<?x?xf32, #sparse{{[0-9]*}}> {
+// CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr to tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: return %[[COO]]
func.func @sparse_new_coo(%arg0: !llvm.ptr) -> tensor<?x?xf32, #COO> {
%0 = sparse_tensor.new %arg0 : !llvm.ptr to tensor<?x?xf32, #COO>
@@ -45,7 +45,7 @@ func.func @sparse_new_coo(%arg0: !llvm.ptr) -> tensor<?x?xf32, #COO> {
}
// CHECK-LABEL: func.func @sparse_out(
-// CHECK-SAME: %[[A:.*]]: tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[A:.*]]: tensor<10x20xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[B:.*]]: !llvm.ptr) {
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
diff --git a/mlir/test/Dialect/SparseTensor/roundtrip.mlir b/mlir/test/Dialect/SparseTensor/roundtrip.mlir
index 5b733ecbe7874db..476fa1b08a39d8d 100644
--- a/mlir/test/Dialect/SparseTensor/roundtrip.mlir
+++ b/mlir/test/Dialect/SparseTensor/roundtrip.mlir
@@ -307,7 +307,7 @@ func.func @sparse_load_ins(%arg0: tensor<16x32xf64, #DenseMatrix>) -> tensor<16x
#SparseVector = #sparse_tensor.encoding<{map = (d0) -> (d0 : compressed)}>
// CHECK-LABEL: func @sparse_insert(
-// CHECK-SAME: %[[A:.*]]: tensor<128xf64, #sparse_tensor.encoding<{{.*}}>>,
+// CHECK-SAME: %[[A:.*]]: tensor<128xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[B:.*]]: index,
// CHECK-SAME: %[[C:.*]]: f64)
// CHECK: %[[T:.*]] = sparse_tensor.insert %[[C]] into %[[A]][%[[B]]] : tensor<128xf64, #{{.*}}>
@@ -362,7 +362,7 @@ func.func @sparse_push_back_n(%arg0: index, %arg1: memref<?xf64>, %arg2: f64, %a
#SparseMatrix = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed, d1 : compressed)}>
// CHECK-LABEL: func @sparse_expansion(
-// CHECK-SAME: %[[A:.*]]: tensor<8x8xf64, #sparse_tensor.encoding<{{.*}}>>)
+// CHECK-SAME: %[[A:.*]]: tensor<8x8xf64, #sparse{{[0-9]*}}>)
// CHECK: %{{.*}}, %{{.*}}, %{{.*}}, %[[T:.*]] = sparse_tensor.expand %[[A]]
// CHECK: return %[[T]] : index
func.func @sparse_expansion(%tensor: tensor<8x8xf64, #SparseMatrix>) -> index {
@@ -380,10 +380,10 @@ func.func @sparse_expansion(%tensor: tensor<8x8xf64, #SparseMatrix>) -> index {
// CHECK-SAME: %[[A1:.*1]]: memref<?xi1>,
// CHECK-SAME: %[[A2:.*2]]: memref<?xindex>,
// CHECK-SAME: %[[A3:.*3]]: index
-// CHECK-SAME: %[[A4:.*4]]: tensor<8x8xf64, #sparse_tensor.encoding<{{.*}}>>,
+// CHECK-SAME: %[[A4:.*4]]: tensor<8x8xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[A5:.*5]]: index)
// CHECK: %[[T:.*]] = sparse_tensor.compress %[[A0]], %[[A1]], %[[A2]], %[[A3]] into %[[A4]][%[[A5]]
-// CHECK: return %[[T]] : tensor<8x8xf64, #sparse_tensor.encoding<{{.*}}>>
+// CHECK: return %[[T]] : tensor<8x8xf64, #sparse{{[0-9]*}}>
func.func @sparse_compression(%values: memref<?xf64>,
%filled: memref<?xi1>,
%added: memref<?xindex>,
@@ -400,9 +400,9 @@ func.func @sparse_compression(%values: memref<?xf64>,
#SparseMatrix = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed, d1 : compressed)}>
// CHECK-LABEL: func @sparse_out(
-// CHECK-SAME: %[[A:.*]]: tensor<?x?xf64, #sparse_tensor.encoding<{{.*}}>>,
+// CHECK-SAME: %[[A:.*]]: tensor<?x?xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[B:.*]]: !llvm.ptr)
-// CHECK: sparse_tensor.out %[[A]], %[[B]] : tensor<?x?xf64, #sparse_tensor.encoding<{{.*}}>>, !llvm.ptr
+// CHECK: sparse_tensor.out %[[A]], %[[B]] : tensor<?x?xf64, #sparse{{[0-9]*}}>, !llvm.ptr
// CHECK: return
func.func @sparse_out(%arg0: tensor<?x?xf64, #SparseMatrix>, %arg1: !llvm.ptr) {
sparse_tensor.out %arg0, %arg1 : tensor<?x?xf64, #SparseMatrix>, !llvm.ptr
@@ -590,7 +590,7 @@ func.func @sparse_tensor_foreach(%arg0: tensor<2x4xf64, #DCSR>) -> () {
#DCSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed, d1 : compressed)}>
// CHECK-LABEL: func @sparse_tensor_foreach(
-// CHECK-SAME: %[[A0:.*]]: tensor<2x4xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[A0:.*]]: tensor<2x4xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[A1:.*]]: f32
// CHECK-NEXT: %[[RET:.*]] = sparse_tensor.foreach in %[[A0]] init(%[[A1]])
// CHECK-NEXT: ^bb0(%[[TMP_1:.*]]: index, %[[TMP_2:.*]]: index, %[[TMP_v:.*]]: f64, %[[TMP_r:.*]]: f32)
@@ -640,7 +640,7 @@ func.func @sparse_sort_coo_stable(%arg0: index, %arg1: memref<?xi64>, %arg2: mem
#OrderedCOO = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)}>
// CHECK-LABEL: func @sparse_reorder_coo(
-// CHECK-SAME: %[[A:.*]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-SAME: %[[A:.*]]: tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: %[[R:.*]] = sparse_tensor.reorder_coo quick_sort %[[A]]
// CHECK: return %[[R]]
func.func @sparse_reorder_coo(%arg0 : tensor<?x?xf32, #UnorderedCOO>) -> tensor<?x?xf32, #OrderedCOO> {
diff --git a/mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir b/mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir
index db844312d02b999..20702bb9850284d 100644
--- a/mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir
+++ b/mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir
@@ -1,8 +1,11 @@
-// RUN: mlir-opt %s -split-input-file | mlir-opt | FileCheck %s
+// RUN: mlir-opt %s -split-input-file | mlir-opt -split-input-file | FileCheck %s
+#SV = #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }>
+
+// CHECK: #[[$SV:.*]] = #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }>
// CHECK-LABEL: func private @sparse_1d_tensor(
-// CHECK-SAME: tensor<32xf64, #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }>>)
-func.func private @sparse_1d_tensor(tensor<32xf64, #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }>>)
+// CHECK-SAME: tensor<32xf64, #[[$SV]]>)
+func.func private @sparse_1d_tensor(tensor<32xf64, #SV>)
// -----
@@ -12,8 +15,9 @@ func.func private @sparse_1d_tensor(tensor<32xf64, #sparse_tensor.encoding<{ map
crdWidth = 64
}>
+// CHECK: #[[$CSR:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed), posWidth = 64, crdWidth = 64 }>
// CHECK-LABEL: func private @sparse_csr(
-// CHECK-SAME: tensor<?x?xf32, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed), posWidth = 64, crdWidth = 64 }>>)
+// CHECK-SAME: tensor<?x?xf32, #[[$CSR]]>)
func.func private @sparse_csr(tensor<?x?xf32, #CSR>)
// -----
@@ -22,8 +26,9 @@ func.func private @sparse_csr(tensor<?x?xf32, #CSR>)
map = {l0, l1} (d0 = l0, d1 = l1) -> (l0 = d0 : dense, l1 = d1 : compressed)
}>
+// CHECK: #[[$CSR_EXPLICIT:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>
// CHECK-LABEL: func private @CSR_explicit(
-// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>>
+// CHECK-SAME: tensor<?x?xf64, #[[$CSR_EXPLICIT]]>
func.func private @CSR_explicit(%arg0: tensor<?x?xf64, #CSR_explicit>) {
return
}
@@ -36,8 +41,9 @@ func.func private @CSR_explicit(%arg0: tensor<?x?xf64, #CSR_explicit>) {
crdWidth = 0
}>
+// CHECK-DAG: #[[$CSC:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d1 : dense, d0 : compressed) }>
// CHECK-LABEL: func private @sparse_csc(
-// CHECK-SAME: tensor<?x?xf32, #sparse_tensor.encoding<{ map = (d0, d1) -> (d1 : dense, d0 : compressed) }>>)
+// CHECK-SAME: tensor<?x?xf32, #[[$CSC]]>)
func.func private @sparse_csc(tensor<?x?xf32, #CSC>)
// -----
@@ -48,8 +54,9 @@ func.func private @sparse_csc(tensor<?x?xf32, #CSC>)
crdWidth = 64
}>
+// CHECK-DAG: #[[$DCSC:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d1 : compressed, d0 : compressed), crdWidth = 64 }>
// CHECK-LABEL: func private @sparse_dcsc(
-// CHECK-SAME: tensor<?x?xf32, #sparse_tensor.encoding<{ map = (d0, d1) -> (d1 : compressed, d0 : compressed), crdWidth = 64 }>>)
+// CHECK-SAME: tensor<?x?xf32, #[[$DCSC]]>)
func.func private @sparse_dcsc(tensor<?x?xf32, #DCSC>)
// -----
@@ -58,8 +65,9 @@ func.func private @sparse_dcsc(tensor<?x?xf32, #DCSC>)
map = (d0, d1) -> (d0 : compressed(nonunique, nonordered), d1 : singleton(nonordered))
}>
+// CHECK-DAG: #[[$COO:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed(nonunique, nonordered), d1 : singleton(nonordered)) }>
// CHECK-LABEL: func private @sparse_coo(
-// CHECK-SAME: tensor<?x?xf32, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed(nonunique, nonordered), d1 : singleton(nonordered)) }>>)
+// CHECK-SAME: tensor<?x?xf32, #[[$COO]]>)
func.func private @sparse_coo(tensor<?x?xf32, #COO>)
// -----
@@ -68,8 +76,9 @@ func.func private @sparse_coo(tensor<?x?xf32, #COO>)
map = (d0, d1, d2) -> (d0 : dense, d1 : loose_compressed(nonunique), d2 : singleton)
}>
+// CHECK-DAG: #[[$BCOO:.*]] = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : dense, d1 : loose_compressed(nonunique), d2 : singleton) }>
// CHECK-LABEL: func private @sparse_bcoo(
-// CHECK-SAME: tensor<?x?x?xf32, #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : dense, d1 : loose_compressed(nonunique), d2 : singleton) }>>)
+// CHECK-SAME: tensor<?x?x?xf32, #[[$BCOO]]>)
func.func private @sparse_bcoo(tensor<?x?x?xf32, #BCOO>)
// -----
@@ -78,8 +87,9 @@ func.func private @sparse_bcoo(tensor<?x?x?xf32, #BCOO>)
map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)
}>
+// CHECK-DAG: #[[$SortedCOO:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton) }>
// CHECK-LABEL: func private @sparse_sorted_coo(
-// CHECK-SAME: tensor<10x10xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton) }>>)
+// CHECK-SAME: tensor<10x10xf64, #[[$SortedCOO]]>)
func.func private @sparse_sorted_coo(tensor<10x10xf64, #SortedCOO>)
// -----
@@ -93,8 +103,9 @@ func.func private @sparse_sorted_coo(tensor<10x10xf64, #SortedCOO>)
)
}>
+// CHECK-DAG: #[[$BSR:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 floordiv 2 : dense, d1 floordiv 3 : compressed, d0 mod 2 : dense, d1 mod 3 : dense) }>
// CHECK-LABEL: func private @sparse_bsr(
-// CHECK-SAME: tensor<10x60xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 floordiv 2 : dense, d1 floordiv 3 : compressed, d0 mod 2 : dense, d1 mod 3 : dense) }>>
+// CHECK-SAME: tensor<10x60xf64, #[[$BSR]]>
func.func private @sparse_bsr(tensor<10x60xf64, #BSR>)
@@ -104,8 +115,9 @@ func.func private @sparse_bsr(tensor<10x60xf64, #BSR>)
map = [s0](d0, d1) -> (d0 * (s0 * 4) : dense, d0 : dense, d1 : compressed)
}>
+// CHECK-DAG: #[[$ELL:.*]] = #sparse_tensor.encoding<{ map = [s0](d0, d1) -> (d0 * (s0 * 4) : dense, d0 : dense, d1 : compressed) }>
// CHECK-LABEL: func private @sparse_ell(
-// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = [s0](d0, d1) -> (d0 * (s0 * 4) : dense, d0 : dense, d1 : compressed) }>>
+// CHECK-SAME: tensor<?x?xf64, #[[$ELL]]>
func.func private @sparse_ell(tensor<?x?xf64, #ELL>)
// -----
@@ -114,8 +126,9 @@ func.func private @sparse_ell(tensor<?x?xf64, #ELL>)
map = (d0 : #sparse_tensor<slice(1, 4, 1)>, d1 : #sparse_tensor<slice(1, 4, 2)>) -> (d0 : dense, d1 : compressed)
}>
+// CHECK-DAG: #[[$CSR_SLICE:.*]] = #sparse_tensor.encoding<{ map = (d0 : #sparse_tensor<slice(1, 4, 1)>, d1 : #sparse_tensor<slice(1, 4, 2)>) -> (d0 : dense, d1 : compressed) }>
// CHECK-LABEL: func private @sparse_slice(
-// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = (d0 : #sparse_tensor<slice(1, 4, 1)>, d1 : #sparse_tensor<slice(1, 4, 2)>) -> (d0 : dense, d1 : compressed) }>>
+// CHECK-SAME: tensor<?x?xf64, #[[$CSR_SLICE]]>
func.func private @sparse_slice(tensor<?x?xf64, #CSR_SLICE>)
// -----
@@ -124,8 +137,9 @@ func.func private @sparse_slice(tensor<?x?xf64, #CSR_SLICE>)
map = (d0 : #sparse_tensor<slice(1, ?, 1)>, d1 : #sparse_tensor<slice(?, 4, 2)>) -> (d0 : dense, d1 : compressed)
}>
+// CHECK-DAG: #[[$CSR_SLICE:.*]] = #sparse_tensor.encoding<{ map = (d0 : #sparse_tensor<slice(1, ?, 1)>, d1 : #sparse_tensor<slice(?, 4, 2)>) -> (d0 : dense, d1 : compressed) }>
// CHECK-LABEL: func private @sparse_slice(
-// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = (d0 : #sparse_tensor<slice(1, ?, 1)>, d1 : #sparse_tensor<slice(?, 4, 2)>) -> (d0 : dense, d1 : compressed) }>>
+// CHECK-SAME: tensor<?x?xf64, #[[$CSR_SLICE]]>
func.func private @sparse_slice(tensor<?x?xf64, #CSR_SLICE>)
// -----
@@ -139,8 +153,9 @@ func.func private @sparse_slice(tensor<?x?xf64, #CSR_SLICE>)
)
}>
+// CHECK-DAG: #[[$BSR:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 floordiv 2 : dense, d1 floordiv 3 : compressed, d0 mod 2 : dense, d1 mod 3 : dense) }>
// CHECK-LABEL: func private @BSR(
-// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 floordiv 2 : dense, d1 floordiv 3 : compressed, d0 mod 2 : dense, d1 mod 3 : dense) }>>
+// CHECK-SAME: tensor<?x?xf64, #[[$BSR]]>
func.func private @BSR(%arg0: tensor<?x?xf64, #BSR>) {
return
}
@@ -158,8 +173,9 @@ func.func private @BSR(%arg0: tensor<?x?xf64, #BSR>) {
)
}>
+// CHECK-DAG: #[[$BCSR:.*]] = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 floordiv 2 : dense, d1 floordiv 3 : dense, d2 floordiv 4 : compressed, d0 mod 2 : dense, d1 mod 3 : dense, d2 mod 4 : dense) }>
// CHECK-LABEL: func private @BCSR(
-// CHECK-SAME: tensor<?x?x?xf64, #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 floordiv 2 : dense, d1 floordiv 3 : dense, d2 floordiv 4 : compressed, d0 mod 2 : dense, d1 mod 3 : dense, d2 mod 4 : dense) }>>
+// CHECK-SAME: tensor<?x?x?xf64, #[[$BCSR]]>
func.func private @BCSR(%arg0: tensor<?x?x?xf64, #BCSR>) {
return
}
@@ -178,8 +194,9 @@ func.func private @BCSR(%arg0: tensor<?x?x?xf64, #BCSR>) {
)
}>
+// CHECK-DAG: #[[$BSR_explicit:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 floordiv 2 : dense, d1 floordiv 3 : compressed, d0 mod 2 : dense, d1 mod 3 : dense) }>
// CHECK-LABEL: func private @BSR_explicit(
-// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 floordiv 2 : dense, d1 floordiv 3 : compressed, d0 mod 2 : dense, d1 mod 3 : dense) }>>
+// CHECK-SAME: tensor<?x?xf64, #[[$BSR_explicit]]>
func.func private @BSR_explicit(%arg0: tensor<?x?xf64, #BSR_explicit>) {
return
}
@@ -195,8 +212,9 @@ func.func private @BSR_explicit(%arg0: tensor<?x?xf64, #BSR_explicit>) {
crdWidth = 8 // we would even like just 2-bits
}>
+// CHECK-DAG: #[[$NV_24:.*]] = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 floordiv 4 : dense, d1 mod 4 : block2_4), crdWidth = 8 }>
// CHECK-LABEL: func private @NV_24(
-// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 floordiv 4 : dense, d1 mod 4 : block2_4), crdWidth = 8 }>>
+// CHECK-SAME: tensor<?x?xf64, #[[$NV_24]]>
func.func private @NV_24(%arg0: tensor<?x?xf64, #NV_24>) {
return
}
@@ -212,8 +230,9 @@ func.func private @NV_24(%arg0: tensor<?x?xf64, #NV_24>) {
)
}>
+// CHECK-DAG: #[[$NV_24:.*]] = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : dense, d1 : dense, d2 floordiv 4 : dense, d2 mod 4 : block2_4) }>
// CHECK-LABEL: func private @NV_24(
-// CHECK-SAME: tensor<?x?x?xf64, #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : dense, d1 : dense, d2 floordiv 4 : dense, d2 mod 4 : block2_4) }>>
+// CHECK-SAME: tensor<?x?x?xf64, #[[$NV_24]]>
func.func private @NV_24(%arg0: tensor<?x?x?xf64, #NV_24>) {
return
}
@@ -229,8 +248,9 @@ func.func private @NV_24(%arg0: tensor<?x?x?xf64, #NV_24>) {
)
}>
+// CHECK-DAG: #[[$NV_24:.*]] = #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : dense, d2 floordiv 4 : dense, d1 : dense, d2 mod 4 : block2_4) }>
// CHECK-LABEL: func private @NV_24(
-// CHECK-SAME: tensor<?x?x?xf64, #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : dense, d2 floordiv 4 : dense, d1 : dense, d2 mod 4 : block2_4) }>>
+// CHECK-SAME: tensor<?x?x?xf64, #[[$NV_24]]>
func.func private @NV_24(%arg0: tensor<?x?x?xf64, #NV_24>) {
return
}
diff --git a/mlir/test/Dialect/SparseTensor/semi_ring.mlir b/mlir/test/Dialect/SparseTensor/semi_ring.mlir
index 5a936bfa1e597a7..814acd673622847 100644
--- a/mlir/test/Dialect/SparseTensor/semi_ring.mlir
+++ b/mlir/test/Dialect/SparseTensor/semi_ring.mlir
@@ -19,13 +19,13 @@ module {
// operation, and the values can be change "in-place".
//
// CHECK-LABEL: func.func @add_only_where_nonzero(
- // CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> {
+ // CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xf64, #sparse{{[0-9]*}}>) -> tensor<8x8xf64, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 2.000000e+00 : f64
- // CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
- // CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+ // CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+ // CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: scf.for %[[VAL_7:.*]] = %[[VAL_2]] to %[[VAL_1]] step %[[VAL_3]] {
// CHECK: %[[VAL_8:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_7]]] : memref<?xindex>
// CHECK: %[[VAL_9:.*]] = arith.addi %[[VAL_7]], %[[VAL_3]] : index
@@ -36,8 +36,8 @@ module {
// CHECK: memref.store %[[VAL_13]], %[[VAL_6]]{{\[}}%[[VAL_11]]] : memref<?xf64>
// CHECK: } {"Emitted from" = "linalg.generic"}
// CHECK: } {"Emitted from" = "linalg.generic"}
- // CHECK: %[[VAL_14:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
- // CHECK: return %[[VAL_14]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
+ // CHECK: %[[VAL_14:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<8x8xf64, #sparse{{[0-9]*}}>
+ // CHECK: return %[[VAL_14]] : tensor<8x8xf64, #sparse{{[0-9]*}}>
// CHECK: }
func.func @add_only_where_nonzero(%argA: tensor<8x8xf64, #SM>) -> tensor<8x8xf64, #SM> {
%c = arith.constant 2.0 : f64
diff --git a/mlir/test/Dialect/SparseTensor/sorted_coo.mlir b/mlir/test/Dialect/SparseTensor/sorted_coo.mlir
index 1a8af35358bf62c..91e7920b3a9033b 100644
--- a/mlir/test/Dialect/SparseTensor/sorted_coo.mlir
+++ b/mlir/test/Dialect/SparseTensor/sorted_coo.mlir
@@ -37,14 +37,14 @@
//
// CHECK-LABEL: func.func @sparse_scale(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf32, #sparse{{[0-9]*}}>) -> tensor<?x?xf32, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant false
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 2.000000e+00 : f32
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex, strided<[?], offset: ?>>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex, strided<[?], offset: ?>>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_8:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK-DAG: %[[VAL_9:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
// CHECK: %[[VAL_10:.*]] = scf.while (%[[VAL_11:.*]] = %[[VAL_8]]) : (index) -> index {
@@ -75,8 +75,8 @@
// CHECK: } {"Emitted from" = "linalg.generic"}
// CHECK: scf.yield %[[VAL_28:.*]] : index
// CHECK: } attributes {"Emitted from" = "linalg.generic"}
-// CHECK: %[[VAL_29:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_29]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_29:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<?x?xf32, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_29]] : tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: }
func.func @sparse_scale(%argx: tensor<?x?xf32, #SortedCOO>) -> tensor<?x?xf32, #SortedCOO> {
%c = arith.constant 2.0 : f32
@@ -90,16 +90,16 @@ func.func @sparse_scale(%argx: tensor<?x?xf32, #SortedCOO>) -> tensor<?x?xf32, #
}
// CHECK-LABEL: func.func @matvec(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x64xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<64xf64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant false
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex, strided<[?], offset: ?>>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex, strided<[?], offset: ?>>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}> to memref<?xindex, strided<[?], offset: ?>>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}> to memref<?xindex, strided<[?], offset: ?>>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x64xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xf64>
// CHECK: %[[VAL_11:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_5]]] : memref<?xindex>
@@ -155,20 +155,20 @@ func.func @matvec(%arga: tensor<32x64xf64, #SortedCOO>,
}
// CHECK-LABEL: func.func @mateltmul(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x64xf64, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<32x64xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*2]]: tensor<32x64xf64>) -> tensor<32x64xf64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant false
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0.000000e+00 : f64
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex, strided<[?], offset: ?>>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex, strided<[?], offset: ?>>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex, strided<[?], offset: ?>>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex, strided<[?], offset: ?>>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}> to memref<?xindex, strided<[?], offset: ?>>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}> to memref<?xindex, strided<[?], offset: ?>>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x64xf64, #sparse{{[0-9]*}}> to memref<?xf64>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}> to memref<?xindex, strided<[?], offset: ?>>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}> to memref<?xindex, strided<[?], offset: ?>>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x64xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x64xf64>
// CHECK: linalg.fill ins(%[[VAL_4]] : f64) outs(%[[VAL_15]] : memref<32x64xf64>)
// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_5]]] : memref<?xindex>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_1d.mlir b/mlir/test/Dialect/SparseTensor/sparse_1d.mlir
index d29758e4fa97121..8f96f33794879b2 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_1d.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_1d.mlir
@@ -14,13 +14,13 @@
}
// CHECK-LABEL: func @add_d(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: f32,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_2]]
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_8]] : memref<32xf32>)
// CHECK: scf.for %[[VAL_9:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
@@ -43,14 +43,14 @@ func.func @add_d(%arga: tensor<32xf32, #DV>, %argb: f32, %argx: tensor<32xf32>)
}
// CHECK-LABEL: func @add_d_init(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: f32) -> tensor<32xf32> {
// CHECK: %[[VAL_2:.*]] = arith.constant 32 : index
// CHECK: %[[VAL_3:.*]] = arith.constant 0.000000e+00 : f32
// CHECK: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK: %[[VAL_5:.*]] = arith.constant 1 : index
// CHECK: %[[VAL_INITTENSOR:.*]] = tensor.empty() : tensor<32xf32>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_INITTENSOR]] : memref<32xf32>
// CHECK: linalg.fill ins(%[[VAL_3]] : f32) outs(%[[VAL_7]] : memref<32xf32>)
// CHECK: scf.for %[[VAL_8:.*]] = %[[VAL_4]] to %[[VAL_2]] step %[[VAL_5]] {
@@ -74,13 +74,13 @@ func.func @add_d_init(%arga: tensor<32xf32, #DV>, %argb: f32) -> tensor<32xf32>
}
// CHECK-LABEL: func @mul_d(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: f32,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_2]]
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_8]] : memref<32xf32>)
// CHECK: scf.for %[[VAL_9:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
@@ -103,16 +103,16 @@ func.func @mul_d(%arga: tensor<32xf32, #DV>, %argb: f32, %argx: tensor<32xf32>)
}
// CHECK-LABEL: func @add_s(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: f32,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_12:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_4]]] : memref<?xindex>
// CHECK-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_6]]] : memref<?xindex>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]]
@@ -158,13 +158,13 @@ func.func @add_s(%arga: tensor<32xf32, #SV>, %argb: f32, %argx: tensor<32xf32>)
}
// CHECK-LABEL: func @repeated_add_s(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]]
// CHECK-DAG: %[[VAL_9:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK-DAG: %[[VAL_10:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -197,14 +197,14 @@ func.func @repeated_add_s(%arga: tensor<32xf32, #SV>, %argx: tensor<32xf32>) ->
}
// CHECK-LABEL: func @mul_s(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: f32,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_2]]
// CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_9]] : memref<32xf32>)
// CHECK-DAG: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -240,13 +240,13 @@ func.func @mul_s(%arga: tensor<32xf32, #SV>, %argb: f32, %argx: tensor<32xf32>)
}
// CHECK-LABEL: func @add_dd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf32>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_2]]
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_9]] : memref<32xf32>)
@@ -271,13 +271,13 @@ func.func @add_dd(%arga: tensor<32xf32, #DV>, %argb: tensor<32xf32>, %argx: tens
}
// CHECK-LABEL: func @mul_dd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf32>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_2]]
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_9]] : memref<32xf32>)
@@ -303,16 +303,16 @@ func.func @mul_dd(%arga: tensor<32xf32, #DV>, %argb: tensor<32xf32>, %argx: tens
// CHECK-LABEL: func @add_ds(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_0]] : memref<32xf32>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]]
// CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_12]] : memref<32xf32>)
// CHECK-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -362,14 +362,14 @@ func.func @add_ds(%arga: tensor<32xf32>, %argb: tensor<32xf32, #SV>, %argx: tens
// CHECK-LABEL: func @mul_ds(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_5:.*]] = bufferization.to_memref %[[VAL_0]] : memref<32xf32>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]]
// CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_10]] : memref<32xf32>)
// CHECK-DAG: %[[VAL_11:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -396,16 +396,16 @@ func.func @mul_ds(%arga: tensor<32xf32>, %argb: tensor<32xf32, #SV>, %argx: tens
}
// CHECK-LABEL: func @add_sd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]]
// CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_12]] : memref<32xf32>)
@@ -455,14 +455,14 @@ func.func @add_sd(%arga: tensor<32xf32, #SV>, %argb: tensor<32xf32>, %argx: tens
}
// CHECK-LABEL: func @mul_sd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf32>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]]
// CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_10]] : memref<32xf32>)
@@ -490,16 +490,16 @@ func.func @mul_sd(%arga: tensor<32xf32, #SV>, %argb: tensor<32xf32>, %argx: tens
}
// CHECK-LABEL: func @add_ss(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*2]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]]
// CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_12]] : memref<32xf32>)
// CHECK-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -572,16 +572,16 @@ func.func @add_ss(%arga: tensor<32xf32, #SV>, %argb: tensor<32xf32, #SV>, %argx:
}
// CHECK-LABEL: func @mul_ss(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*2]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]]
// CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_12]] : memref<32xf32>)
// CHECK-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -632,17 +632,17 @@ func.func @mul_ss(%arga: tensor<32xf32, #SV>, %argb: tensor<32xf32, #SV>, %argx:
}
// CHECK-LABEL: func @two_way_inv(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*2]]: f32,
// CHECK-SAME: %[[VAL_3:.*3]]: tensor<16xf32>) -> tensor<16xf32> {
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_3]]
// CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_13]] : memref<16xf32>)
// CHECK-DAG: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -724,17 +724,17 @@ func.func @two_way_inv(%arga: tensor<16xf32, #SV>, %argb: tensor<16xf32, #SV>, %
}
// CHECK-LABEL: func @two_way_inv_alt(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*2]]: f32,
// CHECK-SAME: %[[VAL_3:.*3]]: tensor<16xf32>) -> tensor<16xf32> {
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_3]]
// CHECK-DAG: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_13]] : memref<16xf32>)
// CHECK-DAG: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -824,12 +824,12 @@ func.func @two_way_inv_alt(%arga: tensor<16xf32, #SV>,
}
// CHECK-LABEL: func @sum_reduction(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<?xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<f32>) -> tensor<f32> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_1]] : memref<f32>
// CHECK-DAG: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK-DAG: %[[VAL_9:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -865,16 +865,16 @@ func.func @sum_reduction(%arga: tensor<?xf32, #SV>, %argx: tensor<f32>) -> tenso
}
// CHECK-LABEL: func @sum_reduction_ss(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*2]]: tensor<f32>) -> tensor<f32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<f32>
// CHECK-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_11]][] : memref<f32>
// CHECK-DAG: %[[VAL_14:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -970,17 +970,17 @@ func.func @sum_reduction_ss(%arga: tensor<16xf32, #SV>,
}
// CHECK-LABEL: func @sum_reduction_inv(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<f32>, %[[VAL_2:.*2]]: tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<f32>, %[[VAL_2:.*2]]: tensor<16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_3:.*3]]: tensor<f32>) -> tensor<f32> {
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<f32>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 0 : index} : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 0 : index} : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_3]] : memref<f32>
// CHECK-DAG: %[[VAL_15:.*]] = memref.load %[[VAL_13]][] : memref<f32>
// CHECK-DAG: %[[VAL_16:.*]] = memref.load %[[VAL_9]][] : memref<f32>
@@ -1084,19 +1084,19 @@ func.func @sum_reduction_inv(%arga: tensor<16xf32, #SV>,
// CHECK-LABEL: func @four_tensors_op(
// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?xf64>,
-// CHECK-SAME: %[[VAL_1:.*1]]: tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_2:.*2]]: tensor<?xf64>, %[[VAL_3:.*3]]: tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_1:.*1]]: tensor<?xf64, #sparse{{[0-9]*}}>, %[[VAL_2:.*2]]: tensor<?xf64>, %[[VAL_3:.*3]]: tensor<?xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_4:.*]]: tensor<?xf64>) -> tensor<?xf64> {
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : memref<?xf64>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : memref<?xf64>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.positions %[[VAL_3]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.coordinates %[[VAL_3]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.values %[[VAL_3]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.positions %[[VAL_3]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.coordinates %[[VAL_3]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.values %[[VAL_3]] : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK-DAG: %[[VAL_16:.*]] = tensor.dim %[[VAL_0]], %[[VAL_5]] : tensor<?xf64>
// CHECK-DAG: %[[VAL_18:.*]] = bufferization.to_memref %[[VAL_4]]
// CHECK-DAG: linalg.fill ins(%{{.*}} : f64) outs(%[[VAL_18]] : memref<?xf64>)
@@ -1259,19 +1259,19 @@ func.func @four_tensors_op(%arga: tensor<?xf64>,
}
// CHECK-LABEL: func @red3s(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_2:.*2]]: tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?xf64, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<?xf64, #sparse{{[0-9]*}}>, %[[VAL_2:.*2]]: tensor<?xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_3:.*3]]: tensor<f64>) -> tensor<f64> {
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 0 : index} : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xf64>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xf64>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 0 : index} : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<?xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK-DAG: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_3]] : memref<f64>
// CHECK-DAG: %[[VAL_17:.*]] = memref.load %[[VAL_15]][] : memref<f64>
// CHECK-DAG: %[[VAL_18:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_2d.mlir b/mlir/test/Dialect/SparseTensor/sparse_2d.mlir
index 22681daa94148ef..57ae18391daf8ad 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_2d.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_2d.mlir
@@ -17,14 +17,14 @@
}
// CHECK-LABEL: func @add_dd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 16 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32>
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_10]] : memref<32x16xf32>)
@@ -53,7 +53,7 @@ func.func @add_dd(%arga: tensor<32x16xf32, #Tdd>, %argb: tensor<32x16xf32>, %arg
}
// CHECK-LABEL: func.func @cmp_dd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xi1>) -> tensor<32x16xi1> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
@@ -61,7 +61,7 @@ func.func @add_dd(%arga: tensor<32x16xf32, #Tdd>, %argb: tensor<32x16xf32>, %arg
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant false
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xi1>
// CHECK: linalg.fill ins(%[[VAL_5]] : i1) outs(%[[VAL_10]] : memref<32x16xi1>)
@@ -90,14 +90,14 @@ func.func @cmp_dd(%arga: tensor<32x16xf32, #Tdd>, %argb: tensor<32x16xf32>, %arg
}
// CHECK-LABEL: func @mul_dd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 16 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32>
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_10]] : memref<32x16xf32>)
@@ -126,7 +126,7 @@ func.func @mul_dd(%arga: tensor<32x16xf32, #Tdd>, %argb: tensor<32x16xf32>, %arg
}
// CHECK-LABEL: func @add_ds(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
@@ -134,9 +134,9 @@ func.func @mul_dd(%arga: tensor<32x16xf32, #Tdd>, %argb: tensor<32x16xf32>, %arg
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32>
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_13]] : memref<32x16xf32>)
@@ -189,7 +189,7 @@ func.func @add_ds(%arga: tensor<32x16xf32, #Tds>, %argb: tensor<32x16xf32>, %arg
}
// CHECK-LABEL: func.func @cmp_ds(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xi1>) -> tensor<32x16xi1> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
@@ -199,9 +199,9 @@ func.func @add_ds(%arga: tensor<32x16xf32, #Tds>, %argb: tensor<32x16xf32>, %arg
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_9:.*]] = arith.constant 0.000000e+00 : f32
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK-DAG: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xi1>
// CHECK: linalg.fill ins(%[[VAL_5]] : i1) outs(%[[VAL_14]] : memref<32x16xi1>)
@@ -256,15 +256,15 @@ func.func @cmp_ds(%arga: tensor<32x16xf32, #Tds>, %argb: tensor<32x16xf32>, %arg
}
// CHECK-LABEL: func @mul_ds(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32>
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_11]] : memref<32x16xf32>)
@@ -295,7 +295,7 @@ func.func @mul_ds(%arga: tensor<32x16xf32, #Tds>, %argb: tensor<32x16xf32>, %arg
}
// CHECK-LABEL: func @add_sd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
@@ -303,9 +303,9 @@ func.func @mul_ds(%arga: tensor<32x16xf32, #Tds>, %argb: tensor<32x16xf32>, %arg
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32>
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_13]] : memref<32x16xf32>)
@@ -363,7 +363,7 @@ func.func @add_sd(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32>, %arg
}
// CHECK-LABEL: func.func @cmp_sd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xi1>) -> tensor<32x16xi1> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 16 : index
@@ -373,9 +373,9 @@ func.func @add_sd(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32>, %arg
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_9:.*]] = arith.constant 0.000000e+00 : f32
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xi1>
// CHECK: linalg.fill ins(%[[VAL_5]] : i1) outs(%[[VAL_14]] : memref<32x16xi1>)
@@ -435,15 +435,15 @@ func.func @cmp_sd(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32>, %arg
}
// CHECK-LABEL: func @mul_sd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 16 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32>
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_11]] : memref<32x16xf32>)
@@ -475,7 +475,7 @@ func.func @mul_sd(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32>, %arg
}
// CHECK-LABEL: func @add_ss(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
@@ -483,11 +483,11 @@ func.func @mul_sd(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32>, %arg
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK-DAG: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32>
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_15]] : memref<32x16xf32>)
@@ -569,7 +569,7 @@ func.func @add_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32>, %arg
}
// CHECK-LABEL: func.func @cmp_ss(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xi1>) -> tensor<32x16xi1> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
@@ -579,11 +579,11 @@ func.func @add_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32>, %arg
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_9:.*]] = arith.constant 0.000000e+00 : f32
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK: %[[VAL_16:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xi1>
// CHECK: linalg.fill ins(%[[VAL_5]] : i1) outs(%[[VAL_16]] : memref<32x16xi1>)
@@ -669,16 +669,16 @@ func.func @cmp_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32>, %arg
}
// CHECK-LABEL: func @mul_ss(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32>
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_12]] : memref<32x16xf32>)
@@ -712,20 +712,20 @@ func.func @mul_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32>, %arg
}
// CHECK-LABEL: func @add_ss_ss(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*2]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_16:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32>
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_16]] : memref<32x16xf32>)
// CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -875,22 +875,22 @@ func.func @add_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T
}
// CHECK-LABEL: func.func @cmp_ss_ss(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xi1>) -> tensor<32x16xi1> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant false
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0.000000e+00 : f32
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_17:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xi1>
// CHECK: linalg.fill ins(%[[VAL_3]] : i1) outs(%[[VAL_17]] : memref<32x16xi1>)
// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -1051,19 +1051,19 @@ func.func @cmp_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T
map = (d0, d1) -> (d0 : dense, d1 : loose_compressed)
}>
// CHECK-LABEL: func.func @sub_ss_batched(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<2x3xf64, #{{.*}}>>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<2x3xf64, #{{.*}}>>) -> tensor<2x3xf64, #{{.*}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<2x3xf64, #sparse{{[0-9]*}}>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<2x3xf64, #sparse{{[0-9]*}}>) -> tensor<2x3xf64, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = tensor.empty() : tensor<2x3xf64, #{{.*}}>>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<2x3xf64, #{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<2x3xf64, #{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<2x3xf64, #{{.*}}>> to memref<?xf64>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<2x3xf64, #{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<2x3xf64, #{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<2x3xf64, #{{.*}}>> to memref<?xf64>
-// CHECK: %[[VAL_12:.*]] = scf.for %[[VAL_13:.*]] = %[[VAL_3]] to %[[VAL_2]] step %[[VAL_4]] iter_args(%[[VAL_14:.*]] = %[[VAL_5]]) -> (tensor<2x3xf64, #{{.*}}>>) {
+// CHECK-DAG: %[[VAL_5:.*]] = tensor.empty() : tensor<2x3xf64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<2x3xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<2x3xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<2x3xf64, #sparse{{[0-9]*}}> to memref<?xf64>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<2x3xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<2x3xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<2x3xf64, #sparse{{[0-9]*}}> to memref<?xf64>
+// CHECK: %[[VAL_12:.*]] = scf.for %[[VAL_13:.*]] = %[[VAL_3]] to %[[VAL_2]] step %[[VAL_4]] iter_args(%[[VAL_14:.*]] = %[[VAL_5]]) -> (tensor<2x3xf64, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_15:.*]] = arith.muli %[[VAL_13]], %[[VAL_2]] : index
// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_15]]] : memref<?xindex>
// CHECK: %[[VAL_17:.*]] = arith.addi %[[VAL_15]], %[[VAL_4]] : index
@@ -1076,9 +1076,9 @@ func.func @cmp_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T
// CHECK: %[[VAL_27:.*]] = arith.cmpi ult, %[[VAL_24]], %[[VAL_18]] : index
// CHECK: %[[VAL_28:.*]] = arith.cmpi ult, %[[VAL_25]], %[[VAL_22]] : index
// CHECK: %[[VAL_29:.*]] = arith.andi %[[VAL_27]], %[[VAL_28]] : i1
-// CHECK: scf.condition(%[[VAL_29]]) %[[VAL_24]], %[[VAL_25]], %[[VAL_26]] : index, index, tensor<2x3xf64, #{{.*}}>>
+// CHECK: scf.condition(%[[VAL_29]]) %[[VAL_24]], %[[VAL_25]], %[[VAL_26]] : index, index, tensor<2x3xf64, #sparse{{[0-9]*}}>
// CHECK: } do {
-// CHECK: ^bb0(%[[VAL_30:.*]]: index, %[[VAL_31:.*]]: index, %[[VAL_32:.*]]: tensor<2x3xf64, #{{.*}}>>):
+// CHECK: ^bb0(%[[VAL_30:.*]]: index, %[[VAL_31:.*]]: index, %[[VAL_32:.*]]: tensor<2x3xf64, #sparse{{[0-9]*}}>):
// CHECK: %[[VAL_33:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_30]]] : memref<?xindex>
// CHECK: %[[VAL_34:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_31]]] : memref<?xindex>
// CHECK: %[[VAL_35:.*]] = arith.cmpi ult, %[[VAL_34]], %[[VAL_33]] : index
@@ -1086,31 +1086,31 @@ func.func @cmp_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T
// CHECK: %[[VAL_37:.*]] = arith.cmpi eq, %[[VAL_33]], %[[VAL_36]] : index
// CHECK: %[[VAL_38:.*]] = arith.cmpi eq, %[[VAL_34]], %[[VAL_36]] : index
// CHECK: %[[VAL_39:.*]] = arith.andi %[[VAL_37]], %[[VAL_38]] : i1
-// CHECK: %[[VAL_40:.*]] = scf.if %[[VAL_39]] -> (tensor<2x3xf64, #{{.*}}>>) {
+// CHECK: %[[VAL_40:.*]] = scf.if %[[VAL_39]] -> (tensor<2x3xf64, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_41:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_30]]] : memref<?xf64>
// CHECK: %[[VAL_42:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_31]]] : memref<?xf64>
// CHECK: %[[VAL_43:.*]] = arith.subf %[[VAL_41]], %[[VAL_42]] : f64
-// CHECK: %[[VAL_44:.*]] = sparse_tensor.insert %[[VAL_43]] into %[[VAL_32]]{{\[}}%[[VAL_13]], %[[VAL_36]]] : tensor<2x3xf64, #{{.*}}>>
-// CHECK: scf.yield %[[VAL_44]] : tensor<2x3xf64, #{{.*}}>>
+// CHECK: %[[VAL_44:.*]] = sparse_tensor.insert %[[VAL_43]] into %[[VAL_32]]{{\[}}%[[VAL_13]], %[[VAL_36]]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_44]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
// CHECK: } else {
// CHECK: %[[VAL_45:.*]] = arith.cmpi eq, %[[VAL_33]], %[[VAL_36]] : index
-// CHECK: %[[VAL_46:.*]] = scf.if %[[VAL_45]] -> (tensor<2x3xf64, #{{.*}}>>) {
+// CHECK: %[[VAL_46:.*]] = scf.if %[[VAL_45]] -> (tensor<2x3xf64, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_47:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_30]]] : memref<?xf64>
-// CHECK: %[[VAL_48:.*]] = sparse_tensor.insert %[[VAL_47]] into %[[VAL_32]]{{\[}}%[[VAL_13]], %[[VAL_36]]] : tensor<2x3xf64, #{{.*}}>>
-// CHECK: scf.yield %[[VAL_48]] : tensor<2x3xf64, #{{.*}}>>
+// CHECK: %[[VAL_48:.*]] = sparse_tensor.insert %[[VAL_47]] into %[[VAL_32]]{{\[}}%[[VAL_13]], %[[VAL_36]]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_48]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
// CHECK: } else {
// CHECK: %[[VAL_49:.*]] = arith.cmpi eq, %[[VAL_34]], %[[VAL_36]] : index
-// CHECK: %[[VAL_50:.*]] = scf.if %[[VAL_49]] -> (tensor<2x3xf64, #{{.*}}>>) {
+// CHECK: %[[VAL_50:.*]] = scf.if %[[VAL_49]] -> (tensor<2x3xf64, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_51:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_31]]] : memref<?xf64>
// CHECK: %[[VAL_52:.*]] = arith.negf %[[VAL_51]] : f64
-// CHECK: %[[VAL_53:.*]] = sparse_tensor.insert %[[VAL_52]] into %[[VAL_32]]{{\[}}%[[VAL_13]], %[[VAL_36]]] : tensor<2x3xf64, #{{.*}}>>
-// CHECK: scf.yield %[[VAL_53]] : tensor<2x3xf64, #{{.*}}>>
+// CHECK: %[[VAL_53:.*]] = sparse_tensor.insert %[[VAL_52]] into %[[VAL_32]]{{\[}}%[[VAL_13]], %[[VAL_36]]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_53]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
// CHECK: } else {
-// CHECK: scf.yield %[[VAL_32]] : tensor<2x3xf64, #{{.*}}>>
+// CHECK: scf.yield %[[VAL_32]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: scf.yield %[[VAL_54:.*]] : tensor<2x3xf64, #{{.*}}>>
+// CHECK: scf.yield %[[VAL_54:.*]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: scf.yield %[[VAL_55:.*]] : tensor<2x3xf64, #{{.*}}>>
+// CHECK: scf.yield %[[VAL_55:.*]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
// CHECK: }
// CHECK: %[[VAL_56:.*]] = arith.cmpi eq, %[[VAL_33]], %[[VAL_36]] : index
// CHECK: %[[VAL_57:.*]] = arith.addi %[[VAL_30]], %[[VAL_4]] : index
@@ -1118,25 +1118,25 @@ func.func @cmp_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T
// CHECK: %[[VAL_59:.*]] = arith.cmpi eq, %[[VAL_34]], %[[VAL_36]] : index
// CHECK: %[[VAL_60:.*]] = arith.addi %[[VAL_31]], %[[VAL_4]] : index
// CHECK: %[[VAL_61:.*]] = arith.select %[[VAL_59]], %[[VAL_60]], %[[VAL_31]] : index
-// CHECK: scf.yield %[[VAL_58]], %[[VAL_61]], %[[VAL_62:.*]] : index, index, tensor<2x3xf64, #{{.*}}>>
+// CHECK: scf.yield %[[VAL_58]], %[[VAL_61]], %[[VAL_62:.*]] : index, index, tensor<2x3xf64, #sparse{{[0-9]*}}>
// CHECK: } attributes
// CHECK: %[[VAL_63:.*]] = scf.for %[[VAL_64:.*]] = %[[VAL_65:.*]]#0 to %[[VAL_18]] step %[[VAL_4]] iter_args(%[[VAL_66:.*]] = %[[VAL_65]]#2)
// CHECK: %[[VAL_67:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_64]]] : memref<?xindex>
// CHECK: %[[VAL_68:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_64]]] : memref<?xf64>
-// CHECK: %[[VAL_69:.*]] = sparse_tensor.insert %[[VAL_68]] into %[[VAL_66]]{{\[}}%[[VAL_13]], %[[VAL_67]]] : tensor<2x3xf64, #{{.*}}>>
-// CHECK: scf.yield %[[VAL_69]] : tensor<2x3xf64, #{{.*}}>>
+// CHECK: %[[VAL_69:.*]] = sparse_tensor.insert %[[VAL_68]] into %[[VAL_66]]{{\[}}%[[VAL_13]], %[[VAL_67]]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_69]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
// CHECK: }
// CHECK: %[[VAL_70:.*]] = scf.for %[[VAL_71:.*]] = %[[VAL_72:.*]]#1 to %[[VAL_22]] step %[[VAL_4]] iter_args(%[[VAL_73:.*]] = %[[VAL_74:.*]])
// CHECK: %[[VAL_75:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_71]]] : memref<?xindex>
// CHECK: %[[VAL_76:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_71]]] : memref<?xf64>
// CHECK: %[[VAL_77:.*]] = arith.negf %[[VAL_76]] : f64
-// CHECK: %[[VAL_78:.*]] = sparse_tensor.insert %[[VAL_77]] into %[[VAL_73]]{{\[}}%[[VAL_13]], %[[VAL_75]]] : tensor<2x3xf64, #{{.*}}>>
-// CHECK: scf.yield %[[VAL_78]] : tensor<2x3xf64, #{{.*}}>>
+// CHECK: %[[VAL_78:.*]] = sparse_tensor.insert %[[VAL_77]] into %[[VAL_73]]{{\[}}%[[VAL_13]], %[[VAL_75]]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_78]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: scf.yield %[[VAL_79:.*]] : tensor<2x3xf64, #{{.*}}>>
+// CHECK: scf.yield %[[VAL_79:.*]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: %[[VAL_80:.*]] = sparse_tensor.load %[[VAL_81:.*]] hasInserts : tensor<2x3xf64, #{{.*}}>>
-// CHECK: return %[[VAL_80]] : tensor<2x3xf64, #{{.*}}>>
+// CHECK: %[[VAL_80:.*]] = sparse_tensor.load %[[VAL_81:.*]] hasInserts : tensor<2x3xf64, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_80]] : tensor<2x3xf64, #sparse{{[0-9]*}}>
// CHECK: }
func.func @sub_ss_batched(%0: tensor<2x3xf64, #BatchedVector>, %1: tensor<2x3xf64, #BatchedVector>)
-> tensor<2x3xf64, #BatchedVector> {
@@ -1152,20 +1152,20 @@ func.func @sub_ss_batched(%0: tensor<2x3xf64, #BatchedVector>, %1: tensor<2x3xf6
}
// CHECK-LABEL: func @mul_ss_ss(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*2]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_16:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32>
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_16]] : memref<32x16xf32>)
// CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -1247,19 +1247,19 @@ func.func @mul_ss_ss(%arga: tensor<32x16xf32, #Tss>, %argb: tensor<32x16xf32, #T
}
// CHECK-LABEL: func @add_sd_ds(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 16 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32>
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_15]] : memref<32x16xf32>)
// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_5]]] : memref<?xindex>
@@ -1352,17 +1352,17 @@ func.func @add_sd_ds(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32, #T
}
// CHECK-LABEL: func @mul_sd_ds(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf32>) -> tensor<32x16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 16 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf32>
// CHECK: linalg.fill ins(%{{.*}} : f32) outs(%[[VAL_13]] : memref<32x16xf32>)
// CHECK: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -1407,15 +1407,15 @@ func.func @mul_sd_ds(%arga: tensor<32x16xf32, #Tsd>, %argb: tensor<32x16xf32, #T
}
// CHECK-LABEL: func @matvec(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<16x32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<16x32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<16xf32>) -> tensor<16xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 16 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<16x32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<16x32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16x32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<16x32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<16x32xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<16x32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<16xf32>
// CHECK: scf.for %[[VAL_12:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
@@ -1458,13 +1458,13 @@ func.func @matvec(%argA: tensor<16x32xf32, #Tds>, %argb: tensor<32xf32>, %argx:
}
// CHECK-LABEL: func @sum_reduction(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<f32>) -> tensor<f32> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 10 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<f32>
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<f32>
// CHECK: %[[VAL_10:.*]] = scf.for %[[VAL_11:.*]] = %[[VAL_4]] to %[[VAL_2]] step %[[VAL_3]] iter_args(%[[VAL_12:.*]] = %[[VAL_9]]) -> (f32) {
@@ -1503,15 +1503,15 @@ func.func @sum_reduction(%arga: tensor<10x20xf32, #Tds>, %argx: tensor<f32>) ->
}
// CHECK-LABEL: func @scale(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<?x?xf64>) -> tensor<?x?xf64> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2.000000e+00 : f64
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_3]] : tensor<?x?xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf64, #sparse{{[0-9]*}}> to memref<?xf64>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_3]] : tensor<?x?xf64, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<?x?xf64>
// CHECK: linalg.fill ins(%{{.*}} : f64) outs(%[[VAL_11]] : memref<?x?xf64>)
// CHECK: scf.for %[[VAL_12:.*]] = %[[VAL_3]] to %[[VAL_8]] step %[[VAL_4]] {
@@ -1552,17 +1552,17 @@ func.func @scale(%arga: tensor<?x?xf64, #Tds>, %argx: tensor<?x?xf64>) -> tensor
}
// CHECK-LABEL: func.func @sampled_dense_dense(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?x?xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*1]]: tensor<?x?xf32>,
// CHECK-SAME: %[[VAL_2:.*2]]: tensor<?x?xf32>,
// CHECK-SAME: %[[VAL_3:.*3]]: tensor<?x?xf32>) -> tensor<?x?xf32> {
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_11:.*]] = tensor.dim %[[VAL_1]], %[[VAL_4]] : tensor<?x?xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_1]] : memref<?x?xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_2]] : memref<?x?xf32>
@@ -1621,24 +1621,24 @@ func.func @sampled_dense_dense(%args: tensor<?x?xf32, #Tss>,
}
// CHECK-LABEL: func @sum_kernel_with_inv(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_2:.*2]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?x?xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<?x?xf32, #sparse{{[0-9]*}}>, %[[VAL_2:.*2]]: tensor<?x?xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_3:.*3]]: tensor<?xf32>,
// CHECK-SAME: %[[VAL_4:.*4]]: tensor<f32>,
// CHECK-SAME: %[[VAL_5:.*5]]: tensor<?xf32>) -> tensor<?xf32> {
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant true
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_17:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_18:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_19:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_17:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_18:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_19:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_20:.*]] = bufferization.to_memref %[[VAL_3]] : memref<?xf32>
// CHECK-DAG: %[[VAL_21:.*]] = bufferization.to_memref %[[VAL_4]] : memref<f32>
// CHECK-DAG: %[[VAL_22:.*]] = sparse_tensor.lvl %[[VAL_2]], %[[VAL_6]] : tensor<?x?xf32,
diff --git a/mlir/test/Dialect/SparseTensor/sparse_3d.mlir b/mlir/test/Dialect/SparseTensor/sparse_3d.mlir
index f2daa77a0c24c8a..4911c78bcff3416 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_3d.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_3d.mlir
@@ -23,7 +23,7 @@
}
// CHECK-LABEL: func @add_ddd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
@@ -32,7 +32,7 @@
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_11]] : memref<32x16x8xf32>)
@@ -65,7 +65,7 @@ func.func @add_ddd(%arga: tensor<32x16x8xf32, #Tddd>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @mul_ddd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
@@ -74,7 +74,7 @@ func.func @add_ddd(%arga: tensor<32x16x8xf32, #Tddd>, %argb: tensor<32x16x8xf32>
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_11]] : memref<32x16x8xf32>)
@@ -107,7 +107,7 @@ func.func @mul_ddd(%arga: tensor<32x16x8xf32, #Tddd>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @add_dds(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
@@ -117,9 +117,9 @@ func.func @mul_ddd(%arga: tensor<32x16x8xf32, #Tddd>, %argb: tensor<32x16x8xf32>
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_9:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_15]] : memref<32x16x8xf32>)
@@ -176,7 +176,7 @@ func.func @add_dds(%arga: tensor<32x16x8xf32, #Tdds>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @mul_dds(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
@@ -184,9 +184,9 @@ func.func @add_dds(%arga: tensor<32x16x8xf32, #Tdds>, %argb: tensor<32x16x8xf32>
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 16 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_13]] : memref<32x16x8xf32>)
@@ -221,7 +221,7 @@ func.func @mul_dds(%arga: tensor<32x16x8xf32, #Tdds>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @add_dsd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
@@ -231,9 +231,9 @@ func.func @mul_dds(%arga: tensor<32x16x8xf32, #Tdds>, %argb: tensor<32x16x8xf32>
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_14]] : memref<32x16x8xf32>)
@@ -294,7 +294,7 @@ func.func @add_dsd(%arga: tensor<32x16x8xf32, #Tdsd>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @mul_dsd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
@@ -302,9 +302,9 @@ func.func @add_dsd(%arga: tensor<32x16x8xf32, #Tdsd>, %argb: tensor<32x16x8xf32>
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_12]] : memref<32x16x8xf32>)
@@ -339,7 +339,7 @@ func.func @mul_dsd(%arga: tensor<32x16x8xf32, #Tdsd>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @add_dss(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
@@ -349,11 +349,11 @@ func.func @mul_dsd(%arga: tensor<32x16x8xf32, #Tdsd>, %argb: tensor<32x16x8xf32>
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_9:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_17:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_17]] : memref<32x16x8xf32>)
@@ -438,18 +438,18 @@ func.func @add_dss(%arga: tensor<32x16x8xf32, #Tdss>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @mul_dss(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_14]] : memref<32x16x8xf32>)
@@ -486,7 +486,7 @@ func.func @mul_dss(%arga: tensor<32x16x8xf32, #Tdss>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @add_sdd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
@@ -496,9 +496,9 @@ func.func @mul_dss(%arga: tensor<32x16x8xf32, #Tdss>, %argb: tensor<32x16x8xf32>
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_14]] : memref<32x16x8xf32>)
@@ -564,7 +564,7 @@ func.func @add_sdd(%arga: tensor<32x16x8xf32, #Tsdd>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @mul_sdd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
@@ -572,9 +572,9 @@ func.func @add_sdd(%arga: tensor<32x16x8xf32, #Tsdd>, %argb: tensor<32x16x8xf32>
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_12]] : memref<32x16x8xf32>)
@@ -610,7 +610,7 @@ func.func @mul_sdd(%arga: tensor<32x16x8xf32, #Tsdd>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @add_sds(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
@@ -620,11 +620,11 @@ func.func @mul_sdd(%arga: tensor<32x16x8xf32, #Tsdd>, %argb: tensor<32x16x8xf32>
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_9:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_17:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_17]] : memref<32x16x8xf32>)
@@ -714,18 +714,18 @@ func.func @add_sds(%arga: tensor<32x16x8xf32, #Tsds>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @mul_sds(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 16 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_14]] : memref<32x16x8xf32>)
@@ -763,7 +763,7 @@ func.func @mul_sds(%arga: tensor<32x16x8xf32, #Tsds>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @add_ssd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
@@ -773,11 +773,11 @@ func.func @mul_sds(%arga: tensor<32x16x8xf32, #Tsds>, %argb: tensor<32x16x8xf32>
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_16:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_16]] : memref<32x16x8xf32>)
@@ -871,18 +871,18 @@ func.func @add_ssd(%arga: tensor<32x16x8xf32, #Tssd>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @mul_ssd(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_13]] : memref<32x16x8xf32>)
@@ -920,7 +920,7 @@ func.func @mul_ssd(%arga: tensor<32x16x8xf32, #Tssd>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @add_sss(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
@@ -930,13 +930,13 @@ func.func @mul_ssd(%arga: tensor<32x16x8xf32, #Tssd>, %argb: tensor<32x16x8xf32>
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_9:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_17:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_19:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_19]] : memref<32x16x8xf32>)
@@ -1054,19 +1054,19 @@ func.func @add_sss(%arga: tensor<32x16x8xf32, #Tsss>, %argb: tensor<32x16x8xf32>
}
// CHECK-LABEL: func @mul_sss(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16x8xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16x8xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16x8xf32>) -> tensor<32x16x8xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16x8xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32x16x8xf32>
// CHECK-DAG: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16x8xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_15]] : memref<32x16x8xf32>)
@@ -1118,18 +1118,18 @@ func.func @mul_sss(%arga: tensor<32x16x8xf32, #Tsss>, %argb: tensor<32x16x8xf32>
// CHECK-LABEL: func @kernel_3d(
// CHECK-SAME: %[[VAL_0:.*0]]: tensor<?x?xf32>,
-// CHECK-SAME: %[[VAL_1:.*1]]: tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_1:.*1]]: tensor<?x?x?xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*2]]: tensor<?x?xf32>,
// CHECK-SAME: %[[VAL_3:.*3]]: tensor<?x?xf32>) -> tensor<?x?xf32> {
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 2 : index} : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 2 : index} : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.lvl %[[VAL_1]], %[[VAL_6]] : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 2 : index} : tensor<?x?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 2 : index} : tensor<?x?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?x?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.lvl %[[VAL_1]], %[[VAL_6]] : tensor<?x?x?xf32, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<?x?xf32>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_3]] : memref<?x?xf32>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.lvl %[[VAL_1]], %[[VAL_5]] : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.lvl %[[VAL_1]], %[[VAL_5]] : tensor<?x?x?xf32, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_14:.*]] = tensor.dim %[[VAL_2]], %[[VAL_6]] : tensor<?x?xf32>
// CHECK-DAG: %[[VAL_16:.*]] = bufferization.to_memref %[[VAL_0]] : memref<?x?xf32>
// CHECK: scf.for %[[VAL_17:.*]] = %[[VAL_5]] to %[[VAL_13]] step %[[VAL_6]] {
@@ -1183,14 +1183,14 @@ func.func @kernel_3d(%arga: tensor<?x?xf32>,
}
// CHECK-LABEL: func @sum_reduction(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20x30xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20x30xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<f32>) -> tensor<f32> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<10x20x30xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<10x20x30xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<10x20x30xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10x20x30xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<10x20x30xf32, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<10x20x30xf32, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<10x20x30xf32, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10x20x30xf32, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<f32>
// CHECK: %[[VAL_11:.*]] = memref.load %[[VAL_10]][] : memref<f32>
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_2]]] : memref<?xindex>
@@ -1239,7 +1239,7 @@ func.func @sum_reduction(%arga: tensor<10x20x30xf32, #Tsss>, %argx: tensor<f32>)
// CHECK-LABEL: func @sum_reduction_inv(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?x?xf32>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<?xf32, #sparse{{[0-9]*}}>
// CHECK-SAME: %[[VAL_2:.*]]: tensor<f32>) -> tensor<f32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 2 : index
@@ -1248,7 +1248,7 @@ func.func @sum_reduction(%arga: tensor<10x20x30xf32, #Tsss>, %argx: tensor<f32>)
// CHECK-DAG: %[[VAL_7:.*]] = tensor.dim %[[VAL_0]], %[[VAL_4]] : tensor<?x?x?xf32>
// CHECK-DAG: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : memref<?x?x?xf32>
// CHECK-DAG: %[[VAL_9:.*]] = tensor.dim %[[VAL_0]], %[[VAL_5]] : tensor<?x?x?xf32>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf32, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : memref<f32>
// CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_12]][] : memref<f32>
// CHECK: %[[VAL_14:.*]] = scf.for %[[VAL_15:.*]] = %[[VAL_5]] to %[[VAL_9]] step %[[VAL_3]] iter_args(%[[VAL_16:.*]] = %[[VAL_13]]) -> (f32) {
@@ -1294,7 +1294,7 @@ func.func @sum_reduction_inv(%arga: tensor<?x?x?xf32>,
}
// CHECK-LABEL: func @invariants(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<10xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<10xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<20xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<30xf32>,
// CHECK-SAME: %[[VAL_3:.*]]: tensor<10x20x30xf32>) -> tensor<10x20x30xf32> {
@@ -1304,7 +1304,7 @@ func.func @sum_reduction_inv(%arga: tensor<?x?x?xf32>,
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 30 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<20xf32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<30xf32>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_3]] : memref<10x20x30xf32>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_affine.mlir b/mlir/test/Dialect/SparseTensor/sparse_affine.mlir
index ca55d2eb0177819..aa75e20460f51f3 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_affine.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_affine.mlir
@@ -16,15 +16,15 @@
}
// CHECK-LABEL: func @mul_inv_dense1d(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<4xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf32>) -> tensor<32xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 3 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf32, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<4xf32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xf32>
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_4]]] : memref<4xf32>
@@ -56,16 +56,16 @@ func.func @mul_inv_dense1d(%arga: tensor<32xf32, #SpVec>,
}
// CHECK-LABEL: func.func @mul_inv_enc_dense1d(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<4xf32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf32, #sparse{{[0-9]*}}>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<4xf32, #sparse{{[0-9]*}}>) -> tensor<32xf32, #sparse{{[0-9]*}}> {
// CHECK: %[[VAL_2:.*]] = arith.constant 32 : index
// CHECK: %[[VAL_3:.*]] = arith.constant 3 : index
// CHECK: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_6:.*]] = tensor.empty() : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<4xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_6]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK: %[[VAL_6:.*]] = tensor.empty() : tensor<32xf32, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<4xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_6]] : tensor<32xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_3]]] : memref<?xf32>
// CHECK: scf.for %[[VAL_11:.*]] = %[[VAL_4]] to %[[VAL_2]] step %[[VAL_5]] {
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_11]]] : memref<?xf32>
@@ -74,8 +74,8 @@ func.func @mul_inv_dense1d(%arga: tensor<32xf32, #SpVec>,
// CHECK: %[[VAL_15:.*]] = arith.addf %[[VAL_12]], %[[VAL_14]] : f32
// CHECK: memref.store %[[VAL_15]], %[[VAL_9]]{{\[}}%[[VAL_11]]] : memref<?xf32>
// CHECK: }
-// CHECK: %[[VAL_16:.*]] = sparse_tensor.load %[[VAL_6]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_16]] : tensor<32xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_16:.*]] = sparse_tensor.load %[[VAL_6]] : tensor<32xf32, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_16]] : tensor<32xf32, #sparse{{[0-9]*}}>
// CHECK: }
func.func @mul_inv_enc_dense1d(%arga: tensor<32xf32, #EncDenseVec>,
%argb: tensor<4xf32, #EncDenseVec>) -> tensor<32xf32, #EncDenseVec> {
@@ -102,16 +102,16 @@ func.func @mul_inv_enc_dense1d(%arga: tensor<32xf32, #EncDenseVec>,
}
// CHECK-LABEL: func @and_affine_dense1d(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<34xi32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xi32>) -> tensor<32xi32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0 : i32
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 2 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi32, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi32, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi32, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<34xi32>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xi32>
// CHECK: linalg.fill ins(%[[ZERO]] : i32) outs(%[[VAL_11]] : memref<32xi32>)
@@ -152,7 +152,7 @@ func.func @and_affine_dense1d(%arga: tensor<32xi32, #SpVec>,
}
// CHECK-LABEL: func @mul_affine_dense2d(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<34x19xf64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf64>) -> tensor<32x16xf64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
@@ -160,9 +160,9 @@ func.func @and_affine_dense1d(%arga: tensor<32xi32, #SpVec>,
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 3 : index
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf64, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<34x19xf64>
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf64>
// CHECK: scf.for %[[VAL_14:.*]] = %[[VAL_5]] to %[[VAL_4]] step %[[VAL_3]] {
@@ -209,20 +209,20 @@ func.func @mul_affine_dense2d(%arga: tensor<32x16xf64, #CSR>,
}
// CHECK-LABEL: func.func @mul_affine_dense_dim_2d(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<34x16xf64, #sparse_tensor.encoding
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x19xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<34x16xf64, #sparse{{[0-9]*}}>
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x19xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf64>) -> tensor<32x16xf64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 19 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 3 : index
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<34x16xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<34x16xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<34x16xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
-// CHECK: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x19xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x19xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x19xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<34x16xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<34x16xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<34x16xf64, #sparse{{[0-9]*}}> to memref<?xf64>
+// CHECK: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x19xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x19xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x19xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf64>
// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_4]]] : memref<?xindex>
// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_5]]] : memref<?xindex>
@@ -274,19 +274,19 @@ func.func @mul_affine_dense_dim_2d(%arga: tensor<34x16xf64, #CSR>,
// CHECK-LABEL: func.func @mul_const_affine_dense_dim_2d(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<34x16xf64,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x19xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x19xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32x16xf64>) -> tensor<32x16xf64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 19 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 3 : index
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<34x16xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<34x16xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<34x16xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
-// CHECK: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x19xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x19xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x19xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<34x16xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<34x16xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<34x16xf64, #sparse{{[0-9]*}}> to memref<?xf64>
+// CHECK: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<32x19xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<32x19xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x19xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32x16xf64>
// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_5]]] : memref<?xindex>
// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_6]]] : memref<?xindex>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_concat.mlir b/mlir/test/Dialect/SparseTensor/sparse_concat.mlir
index 86dc9a117507135..a323fa85d2fd174 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_concat.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_concat.mlir
@@ -7,19 +7,19 @@
#DCSR = #sparse_tensor.encoding<{map = (d0, d1) -> (d0 : compressed, d1 : compressed)}>
// CHECK-LABEL: @concat_sparse_sparse(
-// CHECK-SAME: %[[TMP_arg0:.*]]: tensor<2x4xf64, #sparse_tensor
-// CHECK-SAME: %[[TMP_arg1:.*]]: tensor<3x4xf64, #sparse_tensor
-// CHECK-SAME: %[[TMP_arg2:.*]]: tensor<4x4xf64, #sparse_tensor
+// CHECK-SAME: %[[TMP_arg0:.*]]: tensor<2x4xf64, #sparse>
+// CHECK-SAME: %[[TMP_arg1:.*]]: tensor<3x4xf64, #sparse>
+// CHECK-SAME: %[[TMP_arg2:.*]]: tensor<4x4xf64, #sparse>
// CHECK: %[[TMP_c0:.*]] = arith.constant 0 : index
// CHECK: %[[TMP_c1:.*]] = arith.constant 1 : index
// CHECK: %[[TMP_c5:.*]] = arith.constant 5 : index
// CHECK: %[[TMP_c2:.*]] = arith.constant 2 : index
-// CHECK: %[[TMP_0:.*]] = bufferization.alloc_tensor() : tensor<9x4xf64, #sparse_tensor
-// CHECK: %[[TMP_1:.*]] = sparse_tensor.positions %[[TMP_arg0]] {level = 0 : index} : tensor<2x4xf64, #sparse_tensor
-// CHECK: %[[TMP_2:.*]] = sparse_tensor.coordinates %[[TMP_arg0]] {level = 0 : index} : tensor<2x4xf64, #sparse_tensor
-// CHECK: %[[TMP_3:.*]] = sparse_tensor.positions %[[TMP_arg0]] {level = 1 : index} : tensor<2x4xf64, #sparse_tensor
-// CHECK: %[[TMP_4:.*]] = sparse_tensor.coordinates %[[TMP_arg0]] {level = 1 : index} : tensor<2x4xf64, #sparse_tensor
-// CHECK: %[[TMP_5:.*]] = sparse_tensor.values %[[TMP_arg0]] : tensor<2x4xf64, #sparse_tensor
+// CHECK: %[[TMP_0:.*]] = bufferization.alloc_tensor() : tensor<9x4xf64, #sparse>
+// CHECK: %[[TMP_1:.*]] = sparse_tensor.positions %[[TMP_arg0]] {level = 0 : index} : tensor<2x4xf64, #sparse>
+// CHECK: %[[TMP_2:.*]] = sparse_tensor.coordinates %[[TMP_arg0]] {level = 0 : index} : tensor<2x4xf64, #sparse>
+// CHECK: %[[TMP_3:.*]] = sparse_tensor.positions %[[TMP_arg0]] {level = 1 : index} : tensor<2x4xf64, #sparse>
+// CHECK: %[[TMP_4:.*]] = sparse_tensor.coordinates %[[TMP_arg0]] {level = 1 : index} : tensor<2x4xf64, #sparse>
+// CHECK: %[[TMP_5:.*]] = sparse_tensor.values %[[TMP_arg0]] : tensor<2x4xf64, #sparse>
// CHECK: %[[TMP_6:.*]] = memref.load %[[TMP_1]][%[[TMP_c0]]] : memref<?xindex>
// CHECK: %[[TMP_7:.*]] = memref.load %[[TMP_1]][%[[TMP_c1]]] : memref<?xindex>
// CHECK: %[[RET_1:.*]] = scf.for %[[TMP_arg3:.*]] = %[[TMP_6]] to %[[TMP_7]] step %[[TMP_c1]] iter_args(%[[A0:.*]] = %[[TMP_0]])
@@ -30,16 +30,16 @@
// CHECK: %[[RET_4:.*]] = scf.for %[[TMP_arg4:.*]] = %[[TMP_25]] to %[[TMP_26]] step %[[TMP_c1]] iter_args(%[[A1:.*]] = %[[A0]])
// CHECK: %[[TMP_27:.*]] = memref.load %[[TMP_4]][%[[TMP_arg4]]] : memref<?xindex>
// CHECK: %[[TMP_28:.*]] = memref.load %[[TMP_5]][%[[TMP_arg4]]] : memref<?xf64>
-// CHECK: %[[NEW_1:.*]] = tensor.insert %[[TMP_28]] into %[[A1]][%[[TMP_23]], %[[TMP_27]]] : tensor<9x4xf64, #sparse_tensor
+// CHECK: %[[NEW_1:.*]] = tensor.insert %[[TMP_28]] into %[[A1]][%[[TMP_23]], %[[TMP_27]]] : tensor<9x4xf64, #sparse>
// CHECK: scf.yield %[[NEW_1]]
// CHECK: }
// CHECK: scf.yield %[[RET_4]]
// CHECK: }
-// CHECK: %[[TMP_8:.*]] = sparse_tensor.positions %[[TMP_arg1]] {level = 0 : index} : tensor<3x4xf64, #sparse_tensor
-// CHECK: %[[TMP_9:.*]] = sparse_tensor.coordinates %[[TMP_arg1]] {level = 0 : index} : tensor<3x4xf64, #sparse_tensor
-// CHECK: %[[TMP_10:.*]] = sparse_tensor.positions %[[TMP_arg1]] {level = 1 : index} : tensor<3x4xf64, #sparse_tensor
-// CHECK: %[[TMP_11:.*]] = sparse_tensor.coordinates %[[TMP_arg1]] {level = 1 : index} : tensor<3x4xf64, #sparse_tensor
-// CHECK: %[[TMP_12:.*]] = sparse_tensor.values %[[TMP_arg1]] : tensor<3x4xf64, #sparse_tensor
+// CHECK: %[[TMP_8:.*]] = sparse_tensor.positions %[[TMP_arg1]] {level = 0 : index} : tensor<3x4xf64, #sparse>
+// CHECK: %[[TMP_9:.*]] = sparse_tensor.coordinates %[[TMP_arg1]] {level = 0 : index} : tensor<3x4xf64, #sparse>
+// CHECK: %[[TMP_10:.*]] = sparse_tensor.positions %[[TMP_arg1]] {level = 1 : index} : tensor<3x4xf64, #sparse>
+// CHECK: %[[TMP_11:.*]] = sparse_tensor.coordinates %[[TMP_arg1]] {level = 1 : index} : tensor<3x4xf64, #sparse>
+// CHECK: %[[TMP_12:.*]] = sparse_tensor.values %[[TMP_arg1]] : tensor<3x4xf64, #sparse>
// CHECK: %[[TMP_13:.*]] = memref.load %[[TMP_8]][%[[TMP_c0]]] : memref<?xindex>
// CHECK: %[[TMP_14:.*]] = memref.load %[[TMP_8]][%[[TMP_c1]]] : memref<?xindex>
// CHECK: %[[RET_2:.*]] = scf.for %[[TMP_arg3:.*]] = %[[TMP_13]] to %[[TMP_14]] step %[[TMP_c1]] iter_args(%[[A2:.*]] = %[[RET_1]])
@@ -51,16 +51,16 @@
// CHECK: %[[TMP_27:.*]] = memref.load %[[TMP_11]][%[[TMP_arg4]]] : memref<?xindex>
// CHECK: %[[TMP_28:.*]] = memref.load %[[TMP_12]][%[[TMP_arg4]]] : memref<?xf64>
// CHECK: %[[TMP_29:.*]] = arith.addi %[[TMP_23]], %[[TMP_c2]] : index
-// CHECK: %[[NEW_2:.*]] = tensor.insert %[[TMP_28]] into %[[A3]][%[[TMP_29]], %[[TMP_27]]] : tensor<9x4xf64, #sparse_tensor
+// CHECK: %[[NEW_2:.*]] = tensor.insert %[[TMP_28]] into %[[A3]][%[[TMP_29]], %[[TMP_27]]] : tensor<9x4xf64, #sparse>
// CHECK: scf.yield %[[NEW_2]]
// CHECK: }
// CHECK: scf.yield %[[RET_5]]
// CHECK: }
-// CHECK: %[[TMP_15:.*]] = sparse_tensor.positions %[[TMP_arg2]] {level = 0 : index} : tensor<4x4xf64, #sparse_tensor
-// CHECK: %[[TMP_16:.*]] = sparse_tensor.coordinates %[[TMP_arg2]] {level = 0 : index} : tensor<4x4xf64, #sparse_tensor
-// CHECK: %[[TMP_17:.*]] = sparse_tensor.positions %[[TMP_arg2]] {level = 1 : index} : tensor<4x4xf64, #sparse_tensor
-// CHECK: %[[TMP_18:.*]] = sparse_tensor.coordinates %[[TMP_arg2]] {level = 1 : index} : tensor<4x4xf64, #sparse_tensor
-// CHECK: %[[TMP_19:.*]] = sparse_tensor.values %[[TMP_arg2]] : tensor<4x4xf64, #sparse_tensor
+// CHECK: %[[TMP_15:.*]] = sparse_tensor.positions %[[TMP_arg2]] {level = 0 : index} : tensor<4x4xf64, #sparse>
+// CHECK: %[[TMP_16:.*]] = sparse_tensor.coordinates %[[TMP_arg2]] {level = 0 : index} : tensor<4x4xf64, #sparse>
+// CHECK: %[[TMP_17:.*]] = sparse_tensor.positions %[[TMP_arg2]] {level = 1 : index} : tensor<4x4xf64, #sparse>
+// CHECK: %[[TMP_18:.*]] = sparse_tensor.coordinates %[[TMP_arg2]] {level = 1 : index} : tensor<4x4xf64, #sparse>
+// CHECK: %[[TMP_19:.*]] = sparse_tensor.values %[[TMP_arg2]] : tensor<4x4xf64, #sparse>
// CHECK: %[[TMP_20:.*]] = memref.load %[[TMP_15]][%[[TMP_c0]]] : memref<?xindex>
// CHECK: %[[TMP_21:.*]] = memref.load %[[TMP_15]][%[[TMP_c1]]] : memref<?xindex>
// CHECK: %[[RET_3:.*]] = scf.for %[[TMP_arg3:.*]] = %[[TMP_20]] to %[[TMP_21]] step %[[TMP_c1]] iter_args(%[[A4:.*]] = %[[RET_2]])
@@ -72,13 +72,13 @@
// CHECK: %[[TMP_27:.*]] = memref.load %[[TMP_18]][%[[TMP_arg4]]] : memref<?xindex>
// CHECK: %[[TMP_28:.*]] = memref.load %[[TMP_19]][%[[TMP_arg4]]] : memref<?xf64>
// CHECK: %[[TMP_29:.*]] = arith.addi %[[TMP_23]], %[[TMP_c5]] : index
-// CHECK: %[[NEW_3:.*]] = tensor.insert %[[TMP_28]] into %[[A5]][%[[TMP_29]], %[[TMP_27]]] : tensor<9x4xf64, #sparse_tensor
+// CHECK: %[[NEW_3:.*]] = tensor.insert %[[TMP_28]] into %[[A5]][%[[TMP_29]], %[[TMP_27]]] : tensor<9x4xf64, #sparse>
// CHECK: scf.yield %[[NEW_3]]
// CHECK: }
// CHECK: scf.yield %[[RET_6]]
// CHECK: }
// CHECK: %[[TMP_23:.*]] = sparse_tensor.load %[[RET_3]] hasInserts
-// CHECK: return %[[TMP_23]] : tensor<9x4xf64, #sparse_tensor
+// CHECK: return %[[TMP_23]] : tensor<9x4xf64, #sparse>
func.func @concat_sparse_sparse(%arg0: tensor<2x4xf64, #DCSR>,
%arg1: tensor<3x4xf64, #DCSR>,
%arg2: tensor<4x4xf64, #DCSR>)
@@ -91,21 +91,21 @@ func.func @concat_sparse_sparse(%arg0: tensor<2x4xf64, #DCSR>,
}
// CHECK-LABEL: @concat_sparse_sparse_dynamic(
-// CHECK-SAME: %[[TMP_arg0:.*]]: tensor<2x4xf64, #sparse_tensor
-// CHECK-SAME: %[[TMP_arg1:.*]]: tensor<3x4xf64, #sparse_tensor
-// CHECK-SAME: %[[TMP_arg2:.*]]: tensor<4x4xf64, #sparse_tensor
+// CHECK-SAME: %[[TMP_arg0:.*]]: tensor<2x4xf64, #sparse>
+// CHECK-SAME: %[[TMP_arg1:.*]]: tensor<3x4xf64, #sparse>
+// CHECK-SAME: %[[TMP_arg2:.*]]: tensor<4x4xf64, #sparse>
// CHECK-DAG: %[[TMP_c0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[TMP_c1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[TMP_c5:.*]] = arith.constant 5 : index
// CHECK-DAG: %[[TMP_c2:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[TMP_c9:.*]] = arith.constant 9 : index
// CHECK-DAG: %[[TMP_c4:.*]] = arith.constant 4 : index
-// CHECK: %[[TMP_0:.*]] = bufferization.alloc_tensor(%[[TMP_c9]], %[[TMP_c4]]) : tensor<?x?xf64, #sparse_tensor
-// CHECK: %[[TMP_1:.*]] = sparse_tensor.positions %[[TMP_arg0]] {level = 0 : index} : tensor<2x4xf64, #sparse_tensor
-// CHECK: %[[TMP_2:.*]] = sparse_tensor.coordinates %[[TMP_arg0]] {level = 0 : index} : tensor<2x4xf64, #sparse_tensor
-// CHECK: %[[TMP_3:.*]] = sparse_tensor.positions %[[TMP_arg0]] {level = 1 : index} : tensor<2x4xf64, #sparse_tensor
-// CHECK: %[[TMP_4:.*]] = sparse_tensor.coordinates %[[TMP_arg0]] {level = 1 : index} : tensor<2x4xf64, #sparse_tensor
-// CHECK: %[[TMP_5:.*]] = sparse_tensor.values %[[TMP_arg0]] : tensor<2x4xf64, #sparse_tensor
+// CHECK: %[[TMP_0:.*]] = bufferization.alloc_tensor(%[[TMP_c9]], %[[TMP_c4]]) : tensor<?x?xf64, #sparse>
+// CHECK: %[[TMP_1:.*]] = sparse_tensor.positions %[[TMP_arg0]] {level = 0 : index} : tensor<2x4xf64, #sparse>
+// CHECK: %[[TMP_2:.*]] = sparse_tensor.coordinates %[[TMP_arg0]] {level = 0 : index} : tensor<2x4xf64, #sparse>
+// CHECK: %[[TMP_3:.*]] = sparse_tensor.positions %[[TMP_arg0]] {level = 1 : index} : tensor<2x4xf64, #sparse>
+// CHECK: %[[TMP_4:.*]] = sparse_tensor.coordinates %[[TMP_arg0]] {level = 1 : index} : tensor<2x4xf64, #sparse>
+// CHECK: %[[TMP_5:.*]] = sparse_tensor.values %[[TMP_arg0]] : tensor<2x4xf64, #sparse>
// CHECK: %[[TMP_6:.*]] = memref.load %[[TMP_1]][%[[TMP_c0]]] : memref<?xindex>
// CHECK: %[[TMP_7:.*]] = memref.load %[[TMP_1]][%[[TMP_c1]]] : memref<?xindex>
// CHECK: %[[RET_1:.*]] = scf.for %[[TMP_arg3:.*]] = %[[TMP_6]] to %[[TMP_7]] step %[[TMP_c1]] iter_args(%[[A0:.*]] = %[[TMP_0]])
@@ -116,16 +116,16 @@ func.func @concat_sparse_sparse(%arg0: tensor<2x4xf64, #DCSR>,
// CHECK: %[[RET_4:.*]] = scf.for %[[TMP_arg4:.*]] = %[[TMP_25]] to %[[TMP_26]] step %[[TMP_c1]] iter_args(%[[A1:.*]] = %[[A0]])
// CHECK: %[[TMP_27:.*]] = memref.load %[[TMP_4]][%[[TMP_arg4]]] : memref<?xindex>
// CHECK: %[[TMP_28:.*]] = memref.load %[[TMP_5]][%[[TMP_arg4]]] : memref<?xf64>
-// CHECK: %[[NEW_1:.*]] = tensor.insert %[[TMP_28]] into %[[A1]][%[[TMP_23]], %[[TMP_27]]] : tensor<?x?xf64, #sparse_tensor
+// CHECK: %[[NEW_1:.*]] = tensor.insert %[[TMP_28]] into %[[A1]][%[[TMP_23]], %[[TMP_27]]] : tensor<?x?xf64, #sparse>
// CHECK: scf.yield %[[NEW_1]]
// CHECK: }
// CHECK: scf.yield %[[RET_4]]
// CHECK: }
-// CHECK: %[[TMP_8:.*]] = sparse_tensor.positions %[[TMP_arg1]] {level = 0 : index} : tensor<3x4xf64, #sparse_tensor
-// CHECK: %[[TMP_9:.*]] = sparse_tensor.coordinates %[[TMP_arg1]] {level = 0 : index} : tensor<3x4xf64, #sparse_tensor
-// CHECK: %[[TMP_10:.*]] = sparse_tensor.positions %[[TMP_arg1]] {level = 1 : index} : tensor<3x4xf64, #sparse_tensor
-// CHECK: %[[TMP_11:.*]] = sparse_tensor.coordinates %[[TMP_arg1]] {level = 1 : index} : tensor<3x4xf64, #sparse_tensor
-// CHECK: %[[TMP_12:.*]] = sparse_tensor.values %[[TMP_arg1]] : tensor<3x4xf64, #sparse_tensor
+// CHECK: %[[TMP_8:.*]] = sparse_tensor.positions %[[TMP_arg1]] {level = 0 : index} : tensor<3x4xf64, #sparse>
+// CHECK: %[[TMP_9:.*]] = sparse_tensor.coordinates %[[TMP_arg1]] {level = 0 : index} : tensor<3x4xf64, #sparse>
+// CHECK: %[[TMP_10:.*]] = sparse_tensor.positions %[[TMP_arg1]] {level = 1 : index} : tensor<3x4xf64, #sparse>
+// CHECK: %[[TMP_11:.*]] = sparse_tensor.coordinates %[[TMP_arg1]] {level = 1 : index} : tensor<3x4xf64, #sparse>
+// CHECK: %[[TMP_12:.*]] = sparse_tensor.values %[[TMP_arg1]] : tensor<3x4xf64, #sparse>
// CHECK: %[[TMP_13:.*]] = memref.load %[[TMP_8]][%[[TMP_c0]]] : memref<?xindex>
// CHECK: %[[TMP_14:.*]] = memref.load %[[TMP_8]][%[[TMP_c1]]] : memref<?xindex>
// CHECK: %[[RET_2:.*]] = scf.for %[[TMP_arg3:.*]] = %[[TMP_13]] to %[[TMP_14]] step %[[TMP_c1]] iter_args(%[[A2:.*]] = %[[RET_1]])
@@ -137,16 +137,16 @@ func.func @concat_sparse_sparse(%arg0: tensor<2x4xf64, #DCSR>,
// CHECK: %[[TMP_27:.*]] = memref.load %[[TMP_11]][%[[TMP_arg4]]] : memref<?xindex>
// CHECK: %[[TMP_28:.*]] = memref.load %[[TMP_12]][%[[TMP_arg4]]] : memref<?xf64>
// CHECK: %[[TMP_29:.*]] = arith.addi %[[TMP_23]], %[[TMP_c2]] : index
-// CHECK: %[[NEW_2:.*]] = tensor.insert %[[TMP_28]] into %[[A3]][%[[TMP_29]], %[[TMP_27]]] : tensor<?x?xf64, #sparse_tensor
+// CHECK: %[[NEW_2:.*]] = tensor.insert %[[TMP_28]] into %[[A3]][%[[TMP_29]], %[[TMP_27]]] : tensor<?x?xf64, #sparse>
// CHECK: scf.yield %[[NEW_2]]
// CHECK: }
// CHECK: scf.yield %[[RET_5]]
// CHECK: }
-// CHECK: %[[TMP_15:.*]] = sparse_tensor.positions %[[TMP_arg2]] {level = 0 : index} : tensor<4x4xf64, #sparse_tensor
-// CHECK: %[[TMP_16:.*]] = sparse_tensor.coordinates %[[TMP_arg2]] {level = 0 : index} : tensor<4x4xf64, #sparse_tensor
-// CHECK: %[[TMP_17:.*]] = sparse_tensor.positions %[[TMP_arg2]] {level = 1 : index} : tensor<4x4xf64, #sparse_tensor
-// CHECK: %[[TMP_18:.*]] = sparse_tensor.coordinates %[[TMP_arg2]] {level = 1 : index} : tensor<4x4xf64, #sparse_tensor
-// CHECK: %[[TMP_19:.*]] = sparse_tensor.values %[[TMP_arg2]] : tensor<4x4xf64, #sparse_tensor
+// CHECK: %[[TMP_15:.*]] = sparse_tensor.positions %[[TMP_arg2]] {level = 0 : index} : tensor<4x4xf64, #sparse>
+// CHECK: %[[TMP_16:.*]] = sparse_tensor.coordinates %[[TMP_arg2]] {level = 0 : index} : tensor<4x4xf64, #sparse>
+// CHECK: %[[TMP_17:.*]] = sparse_tensor.positions %[[TMP_arg2]] {level = 1 : index} : tensor<4x4xf64, #sparse>
+// CHECK: %[[TMP_18:.*]] = sparse_tensor.coordinates %[[TMP_arg2]] {level = 1 : index} : tensor<4x4xf64, #sparse>
+// CHECK: %[[TMP_19:.*]] = sparse_tensor.values %[[TMP_arg2]] : tensor<4x4xf64, #sparse>
// CHECK: %[[TMP_20:.*]] = memref.load %[[TMP_15]][%[[TMP_c0]]] : memref<?xindex>
// CHECK: %[[TMP_21:.*]] = memref.load %[[TMP_15]][%[[TMP_c1]]] : memref<?xindex>
// CHECK: %[[RET_3:.*]] = scf.for %[[TMP_arg3:.*]] = %[[TMP_20]] to %[[TMP_21]] step %[[TMP_c1]] iter_args(%[[A4:.*]] = %[[RET_2]])
@@ -158,13 +158,13 @@ func.func @concat_sparse_sparse(%arg0: tensor<2x4xf64, #DCSR>,
// CHECK: %[[TMP_27:.*]] = memref.load %[[TMP_18]][%[[TMP_arg4]]] : memref<?xindex>
// CHECK: %[[TMP_28:.*]] = memref.load %[[TMP_19]][%[[TMP_arg4]]] : memref<?xf64>
// CHECK: %[[TMP_29:.*]] = arith.addi %[[TMP_23]], %[[TMP_c5]] : index
-// CHECK: %[[NEW_3:.*]] = tensor.insert %[[TMP_28]] into %[[A5]][%[[TMP_29]], %[[TMP_27]]] : tensor<?x?xf64, #sparse_tensor
+// CHECK: %[[NEW_3:.*]] = tensor.insert %[[TMP_28]] into %[[A5]][%[[TMP_29]], %[[TMP_27]]] : tensor<?x?xf64, #sparse>
// CHECK: scf.yield %[[NEW_3]]
// CHECK: }
// CHECK: scf.yield %[[RET_6]]
// CHECK: }
// CHECK: %[[TMP_23:.*]] = sparse_tensor.load %[[RET_3]] hasInserts
-// CHECK: return %[[TMP_23]] : tensor<?x?xf64, #sparse_tensor
+// CHECK: return %[[TMP_23]] : tensor<?x?xf64, #sparse>
func.func @concat_sparse_sparse_dynamic(%arg0: tensor<2x4xf64, #DCSR>,
%arg1: tensor<3x4xf64, #DCSR>,
%arg2: tensor<4x4xf64, #DCSR>)
@@ -177,9 +177,9 @@ func.func @concat_sparse_sparse_dynamic(%arg0: tensor<2x4xf64, #DCSR>,
}
// CHECK-LABEL: func.func @concat_sparse_sparse_dense(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<2x4xf64, #sparse_tensor
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<3x4xf64, #sparse_tensor
-// CHECK-SAME: %[[VAL_2:.*]]: tensor<4x4xf64, #sparse_tensor
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<2x4xf64, #sparse>
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<3x4xf64, #sparse>
+// CHECK-SAME: %[[VAL_2:.*]]: tensor<4x4xf64, #sparse>
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 4 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 9 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 5 : index
@@ -189,11 +189,11 @@ func.func @concat_sparse_sparse_dynamic(%arg0: tensor<2x4xf64, #DCSR>,
// CHECK-DAG: %[[VAL_9:.*]] = arith.constant 2 : index
// CHECK: %[[VAL_10:.*]] = bufferization.alloc_tensor(%[[VAL_4]], %[[VAL_3]]) : tensor<?x?xf64>
// CHECK: %[[VAL_11:.*]] = linalg.fill ins(%[[VAL_6]] : f64) outs(%[[VAL_10]] : tensor<?x?xf64>) -> tensor<?x?xf64>
-// CHECK: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<2x4xf64, #sparse_tensor
-// CHECK: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<2x4xf64, #sparse_tensor
-// CHECK: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<2x4xf64, #sparse_tensor
-// CHECK: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<2x4xf64, #sparse_tensor
-// CHECK: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<2x4xf64, #sparse_tensor
+// CHECK: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<2x4xf64, #sparse>
+// CHECK: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<2x4xf64, #sparse>
+// CHECK: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<2x4xf64, #sparse>
+// CHECK: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<2x4xf64, #sparse>
+// CHECK: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<2x4xf64, #sparse>
// CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_7]]] : memref<?xindex>
// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_8]]] : memref<?xindex>
// CHECK: %[[VAL_19:.*]] = scf.for %[[VAL_20:.*]] = %[[VAL_17]] to %[[VAL_18]] step %[[VAL_8]] iter_args(%[[VAL_21:.*]] = %[[VAL_11]]) -> (tensor<?x?xf64>) {
@@ -209,11 +209,11 @@ func.func @concat_sparse_sparse_dynamic(%arg0: tensor<2x4xf64, #DCSR>,
// CHECK: }
// CHECK: scf.yield %[[VAL_26]] : tensor<?x?xf64>
// CHECK: }
-// CHECK: %[[VAL_32:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<3x4xf64, #sparse_tensor
-// CHECK: %[[VAL_33:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<3x4xf64, #sparse_tensor
-// CHECK: %[[VAL_34:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<3x4xf64, #sparse_tensor
-// CHECK: %[[VAL_35:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<3x4xf64, #sparse_tensor
-// CHECK: %[[VAL_36:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<3x4xf64, #sparse_tensor
+// CHECK: %[[VAL_32:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<3x4xf64, #sparse>
+// CHECK: %[[VAL_33:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<3x4xf64, #sparse>
+// CHECK: %[[VAL_34:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<3x4xf64, #sparse>
+// CHECK: %[[VAL_35:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<3x4xf64, #sparse>
+// CHECK: %[[VAL_36:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<3x4xf64, #sparse>
// CHECK: %[[VAL_37:.*]] = memref.load %[[VAL_32]]{{\[}}%[[VAL_7]]] : memref<?xindex>
// CHECK: %[[VAL_38:.*]] = memref.load %[[VAL_32]]{{\[}}%[[VAL_8]]] : memref<?xindex>
// CHECK: %[[VAL_39:.*]] = scf.for %[[VAL_40:.*]] = %[[VAL_37]] to %[[VAL_38]] step %[[VAL_8]] iter_args(%[[VAL_41:.*]] = %[[VAL_19]]) -> (tensor<?x?xf64>) {
@@ -230,11 +230,11 @@ func.func @concat_sparse_sparse_dynamic(%arg0: tensor<2x4xf64, #DCSR>,
// CHECK: }
// CHECK: scf.yield %[[VAL_46]] : tensor<?x?xf64>
// CHECK: }
-// CHECK: %[[VAL_53:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 0 : index} : tensor<4x4xf64, #sparse_tensor
-// CHECK: %[[VAL_54:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 0 : index} : tensor<4x4xf64, #sparse_tensor
-// CHECK: %[[VAL_55:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 1 : index} : tensor<4x4xf64, #sparse_tensor
-// CHECK: %[[VAL_56:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 1 : index} : tensor<4x4xf64, #sparse_tensor
-// CHECK: %[[VAL_57:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<4x4xf64, #sparse_tensor
+// CHECK: %[[VAL_53:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 0 : index} : tensor<4x4xf64, #sparse>
+// CHECK: %[[VAL_54:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 0 : index} : tensor<4x4xf64, #sparse>
+// CHECK: %[[VAL_55:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 1 : index} : tensor<4x4xf64, #sparse>
+// CHECK: %[[VAL_56:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 1 : index} : tensor<4x4xf64, #sparse>
+// CHECK: %[[VAL_57:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<4x4xf64, #sparse>
// CHECK: %[[VAL_58:.*]] = memref.load %[[VAL_53]]{{\[}}%[[VAL_7]]] : memref<?xindex>
// CHECK: %[[VAL_59:.*]] = memref.load %[[VAL_53]]{{\[}}%[[VAL_8]]] : memref<?xindex>
// CHECK: %[[VAL_60:.*]] = scf.for %[[VAL_61:.*]] = %[[VAL_58]] to %[[VAL_59]] step %[[VAL_8]] iter_args(%[[VAL_62:.*]] = %[[VAL_39]]) -> (tensor<?x?xf64>) {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_conv_2d_slice_based.mlir b/mlir/test/Dialect/SparseTensor/sparse_conv_2d_slice_based.mlir
index de0582e5c688575..0cd57ac64b50012 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_conv_2d_slice_based.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_conv_2d_slice_based.mlir
@@ -7,8 +7,8 @@
#DCSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed, d1 : compressed) }>
// CHECK-LABEL: func.func @conv2d_all_sparse_CSR(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xi32, #sparse_tensor.encoding<{{.*}}>>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<3x3xi32>) -> tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xi32, #sparse{{[0-9]*}}>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<3x3xi32>) -> tensor<6x6xi32, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant -2 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 8 : index
@@ -19,12 +19,12 @@
// CHECK-DAG: %[[VAL_9:.*]] = arith.constant 4 : index
// CHECK-DAG: %[[VAL_10:.*]] = arith.constant 0 : i32
// CHECK-DAG: %[[VAL_11:.*]] = arith.constant false
-// CHECK-DAG: %[[VAL_12:.*]] = tensor.empty() : tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<8x8xi32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<8x8xi32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xi32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<8x8xi32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_17:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xi32, #sparse_tensor.encoding<{{.*}}>> to memref<?xi32>
+// CHECK-DAG: %[[VAL_12:.*]] = tensor.empty() : tensor<6x6xi32, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<8x8xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<8x8xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<8x8xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_17:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xi32, #sparse{{[0-9]*}}> to memref<?xi32>
// CHECK-DAG: %[[VAL_18:.*]] = memref.alloca() : memref<11xindex>
// CHECK-DAG: %[[VAL_19:.*]] = memref.alloca() : memref<5xindex>
// CHECK-DAG: %[[VAL_20:.*]] = memref.load %[[VAL_13]]{{\[}}%[[VAL_7]]] : memref<?xindex>
@@ -38,10 +38,10 @@
// CHECK: %[[VAL_24:.*]] = arith.andi %[[VAL_21]], %[[VAL_23]] : i1
// CHECK: %[[VAL_25:.*]] = arith.addi %[[VAL_22]], %[[VAL_3]] : index
// CHECK: %[[VAL_26:.*]] = arith.select %[[VAL_24]], %[[VAL_25]], %[[VAL_6]] : index
-// CHECK: %[[VAL_27:.*]]:3 = scf.while (%[[VAL_28:.*]] = %[[VAL_21]], %[[VAL_29:.*]] = %[[VAL_22]], %[[VAL_30:.*]] = %[[VAL_26]], %[[VAL_31:.*]] = %[[VAL_12]]) : (i1, index, index, tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>) -> (index, index, tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>) {
-// CHECK: scf.condition(%[[VAL_28]]) %[[VAL_29]], %[[VAL_30]], %[[VAL_31]] : index, index, tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>
+// CHECK: %[[VAL_27:.*]]:3 = scf.while (%[[VAL_28:.*]] = %[[VAL_21]], %[[VAL_29:.*]] = %[[VAL_22]], %[[VAL_30:.*]] = %[[VAL_26]], %[[VAL_31:.*]] = %[[VAL_12]]) : (i1, index, index, tensor<6x6xi32, #sparse{{[0-9]*}}>) -> (index, index, tensor<6x6xi32, #sparse{{[0-9]*}}>) {
+// CHECK: scf.condition(%[[VAL_28]]) %[[VAL_29]], %[[VAL_30]], %[[VAL_31]] : index, index, tensor<6x6xi32, #sparse{{[0-9]*}}>
// CHECK: } do {
-// CHECK: ^bb0(%[[VAL_32:.*]]: index, %[[VAL_33:.*]]: index, %[[VAL_34:.*]]: tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>):
+// CHECK: ^bb0(%[[VAL_32:.*]]: index, %[[VAL_33:.*]]: index, %[[VAL_34:.*]]: tensor<6x6xi32, #sparse{{[0-9]*}}>):
// CHECK: %[[VAL_35:.*]] = memref.load %[[VAL_19]]{{\[}}%[[VAL_6]]] : memref<5xindex>
// CHECK: %[[VAL_36:.*]]:4 = scf.for %[[VAL_37:.*]] = %[[VAL_8]] to %[[VAL_35]] step %[[VAL_5]] iter_args(%[[VAL_38:.*]] = %[[VAL_11]], %[[VAL_39:.*]] = %[[VAL_4]], %[[VAL_40:.*]] = %[[VAL_8]], %[[VAL_41:.*]] = %[[VAL_6]]) -> (i1, index, index, index) {
// CHECK: %[[VAL_42:.*]] = memref.load %[[VAL_19]]{{\[}}%[[VAL_37]]] : memref<5xindex>
@@ -90,10 +90,10 @@
// CHECK: %[[VAL_79:.*]] = arith.andi %[[VAL_77]]#0, %[[VAL_78]] : i1
// CHECK: %[[VAL_80:.*]] = arith.addi %[[VAL_77]]#1, %[[VAL_3]] : index
// CHECK: %[[VAL_81:.*]] = arith.select %[[VAL_79]], %[[VAL_80]], %[[VAL_6]] : index
-// CHECK: %[[VAL_82:.*]]:3 = scf.while (%[[VAL_83:.*]] = %[[VAL_77]]#0, %[[VAL_84:.*]] = %[[VAL_77]]#1, %[[VAL_85:.*]] = %[[VAL_81]], %[[VAL_86:.*]] = %[[VAL_34]]) : (i1, index, index, tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>) -> (index, index, tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>) {
-// CHECK: scf.condition(%[[VAL_83]]) %[[VAL_84]], %[[VAL_85]], %[[VAL_86]] : index, index, tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>
+// CHECK: %[[VAL_82:.*]]:3 = scf.while (%[[VAL_83:.*]] = %[[VAL_77]]#0, %[[VAL_84:.*]] = %[[VAL_77]]#1, %[[VAL_85:.*]] = %[[VAL_81]], %[[VAL_86:.*]] = %[[VAL_34]]) : (i1, index, index, tensor<6x6xi32, #sparse{{[0-9]*}}>) -> (index, index, tensor<6x6xi32, #sparse{{[0-9]*}}>) {
+// CHECK: scf.condition(%[[VAL_83]]) %[[VAL_84]], %[[VAL_85]], %[[VAL_86]] : index, index, tensor<6x6xi32, #sparse{{[0-9]*}}>
// CHECK: } do {
-// CHECK: ^bb0(%[[VAL_87:.*]]: index, %[[VAL_88:.*]]: index, %[[VAL_89:.*]]: tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>):
+// CHECK: ^bb0(%[[VAL_87:.*]]: index, %[[VAL_88:.*]]: index, %[[VAL_89:.*]]: tensor<6x6xi32, #sparse{{[0-9]*}}>):
// CHECK: %[[VAL_90:.*]] = memref.load %[[VAL_19]]{{\[}}%[[VAL_7]]] : memref<5xindex>
// CHECK: %[[VAL_91:.*]] = arith.addi %[[VAL_90]], %[[VAL_8]] : index
// CHECK: %[[VAL_92:.*]] = arith.addi %[[VAL_90]], %[[VAL_5]] : index
@@ -145,11 +145,11 @@
// CHECK: memref.store %[[VAL_112]], %[[VAL_18]]{{\[}}%[[VAL_7]]] : memref<11xindex>
// CHECK: scf.yield %[[VAL_133]], %[[VAL_136:.*]]#1, %[[VAL_2]] : index, i32, i1
// CHECK: }
-// CHECK: %[[VAL_137:.*]] = scf.if %[[VAL_138:.*]]#2 -> (tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>) {
-// CHECK: %[[VAL_139:.*]] = sparse_tensor.insert %[[VAL_138]]#1 into %[[VAL_89]]{{\[}}%[[VAL_33]], %[[VAL_88]]] : tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>
-// CHECK: scf.yield %[[VAL_139]] : tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>
+// CHECK: %[[VAL_137:.*]] = scf.if %[[VAL_138:.*]]#2 -> (tensor<6x6xi32, #sparse{{[0-9]*}}>) {
+// CHECK: %[[VAL_139:.*]] = sparse_tensor.insert %[[VAL_138]]#1 into %[[VAL_89]]{{\[}}%[[VAL_33]], %[[VAL_88]]] : tensor<6x6xi32, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_139]] : tensor<6x6xi32, #sparse{{[0-9]*}}>
// CHECK: } else {
-// CHECK: scf.yield %[[VAL_89]] : tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>
+// CHECK: scf.yield %[[VAL_89]] : tensor<6x6xi32, #sparse{{[0-9]*}}>
// CHECK: }
// CHECK: memref.store %[[VAL_6]], %[[VAL_19]]{{\[}}%[[VAL_7]]] : memref<5xindex>
// CHECK: memref.store %[[VAL_6]], %[[VAL_18]]{{\[}}%[[VAL_7]]] : memref<11xindex>
@@ -202,7 +202,7 @@
// CHECK: %[[VAL_175:.*]] = arith.addi %[[VAL_174]], %[[VAL_5]] : index
// CHECK: %[[VAL_176:.*]] = arith.cmpi ule, %[[VAL_175]], %[[VAL_4]] : index
// CHECK: %[[VAL_177:.*]] = arith.andi %[[VAL_173]]#1, %[[VAL_176]] : i1
-// CHECK: scf.yield %[[VAL_177]], %[[VAL_173]]#0, %[[VAL_174]], %[[VAL_178:.*]] : i1, index, index, tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>
+// CHECK: scf.yield %[[VAL_177]], %[[VAL_173]]#0, %[[VAL_174]], %[[VAL_178:.*]] : i1, index, index, tensor<6x6xi32, #sparse{{[0-9]*}}>
// CHECK: }
// CHECK: memref.store %[[VAL_6]], %[[VAL_19]]{{\[}}%[[VAL_7]]] : memref<5xindex>
// CHECK: %[[VAL_179:.*]] = arith.cmpi ugt, %[[VAL_32]], %[[VAL_33]] : index
@@ -254,10 +254,10 @@
// CHECK: %[[VAL_214:.*]] = arith.addi %[[VAL_213]], %[[VAL_5]] : index
// CHECK: %[[VAL_215:.*]] = arith.cmpi ule, %[[VAL_214]], %[[VAL_4]] : index
// CHECK: %[[VAL_216:.*]] = arith.andi %[[VAL_212]]#1, %[[VAL_215]] : i1
-// CHECK: scf.yield %[[VAL_216]], %[[VAL_212]]#0, %[[VAL_213]], %[[VAL_217:.*]]#2 : i1, index, index, tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>
+// CHECK: scf.yield %[[VAL_216]], %[[VAL_212]]#0, %[[VAL_213]], %[[VAL_217:.*]]#2 : i1, index, index, tensor<6x6xi32, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: %[[VAL_218:.*]] = sparse_tensor.load %[[VAL_219:.*]]#2 hasInserts : tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>
-// CHECK: return %[[VAL_218]] : tensor<6x6xi32, #sparse_tensor.encoding<{{.*}}>>
+// CHECK: %[[VAL_218:.*]] = sparse_tensor.load %[[VAL_219:.*]]#2 hasInserts : tensor<6x6xi32, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_218]] : tensor<6x6xi32, #sparse{{[0-9]*}}>
// CHECK: }
func.func @conv2d_all_sparse_CSR(%arg0: tensor<8x8xi32, #DCSR>,
%arg1: tensor<3x3xi32>) -> tensor<6x6xi32, #DCSR> {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_extract_slice.mlir b/mlir/test/Dialect/SparseTensor/sparse_extract_slice.mlir
index ae53f4d854e2b13..c501a09baa6eb88 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_extract_slice.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_extract_slice.mlir
@@ -12,7 +12,7 @@
// CHECK-SAME: %[[VAL_0:.*0]]: memref<?xindex>,
// CHECK-SAME: %[[VAL_1:.*1]]: memref<?xindex>,
// CHECK-SAME: %[[VAL_2:.*2]]: memref<?xf64>,
-// CHECK-SAME: %[[VAL_3:.*3]]: !sparse_tensor.storage_specifier<#sparse_tensor.encoding<{{{.*}}}>>)
+// CHECK-SAME: %[[VAL_3:.*3]]: !sparse_tensor.storage_specifier<#sparse{{[0-9]*}}>)
// CHECK: %[[VAL_4:.*]] = sparse_tensor.storage_specifier.init with %[[VAL_3]]
// CHECK: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK: %[[VAL_6:.*]] = arith.constant 4 : index
diff --git a/mlir/test/Dialect/SparseTensor/sparse_foreach.mlir b/mlir/test/Dialect/SparseTensor/sparse_foreach.mlir
index 5983289c752efc1..eb611156722a82c 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_foreach.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_foreach.mlir
@@ -143,13 +143,13 @@ func.func @foreach_print_slice(%A: tensor<4x4xf64, #CSR_SLICE>) {
}>
// CHECK-LABEL: func.func @foreach_bcoo(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<4x4x4xf64, #{{.*}}>>) {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<4x4x4xf64, #sparse{{[0-9]*}}>) {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 4 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 2 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<4x4x4xf64, #{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<4x4x4xf64, #{{.*}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<4x4x4xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<4x4x4xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: scf.for %[[VAL_7:.*]] = %[[VAL_2]] to %[[VAL_1]] step %[[VAL_3]] {
// CHECK: %[[VAL_8:.*]] = arith.muli %[[VAL_7]], %[[VAL_4]] : index
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_8]]] : memref<?xindex>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_fp_ops.mlir b/mlir/test/Dialect/SparseTensor/sparse_fp_ops.mlir
index f25a56469d7e742..8c09523174bd76e 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_fp_ops.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_fp_ops.mlir
@@ -31,13 +31,13 @@
}
// CHECK-LABEL: func @abs(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf64>
// CHECK: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -63,13 +63,13 @@ func.func @abs(%arga: tensor<32xf64, #SV>,
}
// CHECK-LABEL: func @ceil(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf64>
// CHECK: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -95,13 +95,13 @@ func.func @ceil(%arga: tensor<32xf64, #SV>,
}
// CHECK-LABEL: func @floor(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf64>
// CHECK: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -127,13 +127,13 @@ func.func @floor(%arga: tensor<32xf64, #SV>,
}
// CHECK-LABEL: func @neg(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf64>
// CHECK: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -159,16 +159,16 @@ func.func @neg(%arga: tensor<32xf64, #SV>,
}
// CHECK-LABEL: func @add(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf64>
// CHECK: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xf64>
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -219,16 +219,16 @@ func.func @add(%arga: tensor<32xf64, #SV>,
}
// CHECK-LABEL: func @sub(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf64>
// CHECK: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xf64>
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -281,14 +281,14 @@ func.func @sub(%arga: tensor<32xf64, #SV>,
}
// CHECK-LABEL: func @mul(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf64>
// CHECK: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xf64>
// CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -317,14 +317,14 @@ func.func @mul(%arga: tensor<32xf64, #SV>,
}
// CHECK-LABEL: func @divbyc(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2.000000e+00 : f64
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xf64>
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
// CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -351,13 +351,13 @@ func.func @divbyc(%arga: tensor<32xf64, #SV>,
}
// CHECK-LABEL: func.func @zero_preserving_math(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xf64, #sparse{{[0-9]*}}>) -> tensor<32xf64, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_3:.*]] = tensor.empty() : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK: %[[VAL_3:.*]] = tensor.empty() : tensor<32xf64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_7:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_1]]] : memref<?xindex>
// CHECK: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[T:.*]] = scf.for %[[VAL_9:.*]] = %[[VAL_7]] to %[[VAL_8]] step %[[VAL_2]] {{.*}} {
@@ -371,11 +371,11 @@ func.func @divbyc(%arga: tensor<32xf64, #SV>,
// CHECK: %[[VAL_17:.*]] = math.log1p %[[VAL_16]] : f64
// CHECK: %[[VAL_18:.*]] = math.sin %[[VAL_17]] : f64
// CHECK: %[[VAL_19:.*]] = math.tanh %[[VAL_18]] : f64
-// CHECK: %[[Y:.*]] = sparse_tensor.insert %[[VAL_19]] into %{{.*}}[%[[VAL_10]]] : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[Y:.*]] = sparse_tensor.insert %[[VAL_19]] into %{{.*}}[%[[VAL_10]]] : tensor<32xf64, #sparse{{[0-9]*}}>
// CHECK: scf.yield %[[Y]]
// CHECK: }
-// CHECK: %[[VAL_20:.*]] = sparse_tensor.load %[[T]] hasInserts : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_20]] : tensor<32xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_20:.*]] = sparse_tensor.load %[[T]] hasInserts : tensor<32xf64, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_20]] : tensor<32xf64, #sparse{{[0-9]*}}>
// CHECK: }
func.func @zero_preserving_math(%arga: tensor<32xf64, #SV>) -> tensor<32xf64, #SV> {
%c32 = arith.constant 32 : index
@@ -398,25 +398,25 @@ func.func @zero_preserving_math(%arga: tensor<32xf64, #SV>) -> tensor<32xf64, #S
}
// CHECK-LABEL: func.func @complex_divbyc(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xcomplex<f64>, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xcomplex<f64>, #sparse{{.*}}> {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 1 : index
// CHECK: %[[VAL_3:.*]] = complex.constant [0.000000e+00, 1.000000e+00] : complex<f64>
-// CHECK: %[[VAL_4:.*]] = tensor.empty() : tensor<32xcomplex<f64>, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xcomplex<f64>, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xcomplex<f64>, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xcomplex<f64>, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xcomplex<f64>>
+// CHECK: %[[VAL_4:.*]] = tensor.empty() : tensor<32xcomplex<f64>, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xcomplex<f64>, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xcomplex<f64>, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xcomplex<f64>, #sparse{{[0-9]*}}> to memref<?xcomplex<f64>>
// CHECK: %[[VAL_8:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_1]]] : memref<?xindex>
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[T:.*]] = scf.for %[[VAL_10:.*]] = %[[VAL_8]] to %[[VAL_9]] step %[[VAL_2]] {{.*}} {
// CHECK: %[[VAL_11:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_10]]] : memref<?xindex>
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_10]]] : memref<?xcomplex<f64>>
// CHECK: %[[VAL_13:.*]] = complex.div %[[VAL_12]], %[[VAL_3]] : complex<f64>
-// CHECK: %[[Y:.*]] = sparse_tensor.insert %[[VAL_13]] into %{{.*}}[%[[VAL_11]]] : tensor<32xcomplex<f64>, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[Y:.*]] = sparse_tensor.insert %[[VAL_13]] into %{{.*}}[%[[VAL_11]]] : tensor<32xcomplex<f64>, #sparse{{[0-9]*}}>
// CHECK: scf.yield %[[Y]]
// CHECK: }
-// CHECK: %[[VAL_14:.*]] = sparse_tensor.load %[[T]] hasInserts : tensor<32xcomplex<f64>, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_14]] : tensor<32xcomplex<f64>, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_14:.*]] = sparse_tensor.load %[[T]] hasInserts : tensor<32xcomplex<f64>, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_14]] : tensor<32xcomplex<f64>, #sparse{{[0-9]*}}>
// CHECK: }
func.func @complex_divbyc(%arg0: tensor<32xcomplex<f64>, #SV>) -> tensor<32xcomplex<f64>, #SV> {
%c = complex.constant [0.0, 1.0] : complex<f64>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_index.mlir b/mlir/test/Dialect/SparseTensor/sparse_index.mlir
index e49c89e01790c08..b09bd0a7400941e 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_index.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_index.mlir
@@ -18,17 +18,17 @@
}
// CHECK-LABEL: func.func @dense_index(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xi64, #sparse_tensor.encoding
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xi64, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_3:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_1]] : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_1]] : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_5:.*]] = tensor.empty(%[[VAL_3]], %[[VAL_4]]) : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_1]] : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_2]] : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_24:.*]] = sparse_tensor.lvl %[[VAL_5]], %[[VAL_2]] : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_5]] : tensor<?x?xi64, #sparse_tensor.encoding
+// CHECK-DAG: %[[VAL_3:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_1]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_1]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_5:.*]] = tensor.empty(%[[VAL_3]], %[[VAL_4]]) : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_1]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_2]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_24:.*]] = sparse_tensor.lvl %[[VAL_5]], %[[VAL_2]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_5]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
// CHECK: scf.for %[[VAL_10:.*]] = %[[VAL_1]] to %[[VAL_7]] step %[[VAL_2]] {
// CHECK: scf.for %[[VAL_11:.*]] = %[[VAL_1]] to %[[VAL_8]] step %[[VAL_2]] {
// CHECK: %[[VAL_12:.*]] = arith.muli %[[VAL_8]], %[[VAL_10]] : index
@@ -43,8 +43,8 @@
// CHECK: memref.store %[[VAL_20]], %[[VAL_9]]{{\[}}%[[VAL_15]]] : memref<?xi64>
// CHECK: }
// CHECK: }
-// CHECK: %[[VAL_21:.*]] = sparse_tensor.load %[[VAL_5]] : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK: return %[[VAL_21]] : tensor<?x?xi64, #sparse_tensor.encoding
+// CHECK: %[[VAL_21:.*]] = sparse_tensor.load %[[VAL_5]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_21]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
// CHECK: }
func.func @dense_index(%arga: tensor<?x?xi64, #DenseMatrix>)
-> tensor<?x?xi64, #DenseMatrix> {
@@ -70,17 +70,17 @@ func.func @dense_index(%arga: tensor<?x?xi64, #DenseMatrix>)
// CHECK-LABEL: func.func @sparse_index(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xi64, #sparse_tensor.encoding
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xi64, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_3:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_1]] : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_1]] : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_5:.*]] = tensor.empty(%[[VAL_3]], %[[VAL_4]]) : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xi64, #sparse_tensor.encoding
+// CHECK-DAG: %[[VAL_3:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_1]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.lvl %[[VAL_0]], %[[VAL_1]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_5:.*]] = tensor.empty(%[[VAL_3]], %[[VAL_4]]) : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_11:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_1]]] : memref<?xindex>
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[T:.*]] = scf.for %[[VAL_13:.*]] = %[[VAL_11]] to %[[VAL_12]] step %[[VAL_2]] {{.*}} {
@@ -95,13 +95,13 @@ func.func @dense_index(%arga: tensor<?x?xi64, #DenseMatrix>)
// CHECK: %[[VAL_22:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_18]]] : memref<?xi64>
// CHECK: %[[VAL_23:.*]] = arith.muli %[[VAL_21]], %[[VAL_22]] : i64
// CHECK: %[[VAL_24:.*]] = arith.muli %[[VAL_20]], %[[VAL_23]] : i64
-// CHECK: %[[Y:.*]] = sparse_tensor.insert %[[VAL_24]] into %{{.*}}[%[[VAL_14]], %[[VAL_19]]] : tensor<?x?xi64, #sparse_tensor.encoding
+// CHECK: %[[Y:.*]] = sparse_tensor.insert %[[VAL_24]] into %{{.*}}[%[[VAL_14]], %[[VAL_19]]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
// CHECK: scf.yield %[[Y]]
// CHECK: }
// CHECK: scf.yield %[[L]]
// CHECK: }
-// CHECK: %[[VAL_25:.*]] = sparse_tensor.load %[[T]] hasInserts : tensor<?x?xi64, #sparse_tensor.encoding
-// CHECK: return %[[VAL_25]] : tensor<?x?xi64, #sparse_tensor.encoding
+// CHECK: %[[VAL_25:.*]] = sparse_tensor.load %[[T]] hasInserts : tensor<?x?xi64, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_25]] : tensor<?x?xi64, #sparse{{[0-9]*}}>
// CHECK: }
func.func @sparse_index(%arga: tensor<?x?xi64, #SparseMatrix>)
-> tensor<?x?xi64, #SparseMatrix> {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_int_ops.mlir b/mlir/test/Dialect/SparseTensor/sparse_int_ops.mlir
index da7d45bd63e17d4..868b11c91fe3509 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_int_ops.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_int_ops.mlir
@@ -23,16 +23,16 @@
}
// CHECK-LABEL: func @add(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xi64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xi64>) -> tensor<32xi64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xi64>
// CHECK: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xi64>
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -83,7 +83,7 @@ func.func @add(%arga: tensor<32xi64, #SV>,
}
// CHECK-LABEL: func @sub(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xi64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xi64>) -> tensor<32xi64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
@@ -91,9 +91,9 @@ func.func @add(%arga: tensor<32xi64, #SV>,
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 0 : i64
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xi64>
// CHECK: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xi64>
// CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -146,14 +146,14 @@ func.func @sub(%arga: tensor<32xi64, #SV>,
}
// CHECK-LABEL: func @mul(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xi64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xi64>) -> tensor<32xi64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xi64>
// CHECK: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xi64>
// CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -182,14 +182,14 @@ func.func @mul(%arga: tensor<32xi64, #SV>,
}
// CHECK-LABEL: func @divsbyc(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xi64>) -> tensor<32xi64> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2 : i64
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xi64>
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
// CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -216,14 +216,14 @@ func.func @divsbyc(%arga: tensor<32xi64, #SV>,
}
// CHECK-LABEL: func @divubyc(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xi64>) -> tensor<32xi64> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2 : i64
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{.*}}}>>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xi64>
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
// CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -250,14 +250,14 @@ func.func @divubyc(%arga: tensor<32xi64, #SV>,
}
// CHECK-LABEL: func @and(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xi64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xi64>) -> tensor<32xi64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi64>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xi64>
// CHECK: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xi64>
// CHECK: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xi64>
// CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -286,16 +286,16 @@ func.func @and(%arga: tensor<32xi64, #SV>,
}
// CHECK-LABEL: func @or(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xi64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xi64>) -> tensor<32xi64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi64>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xi64>
// CHECK: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xi64>
// CHECK: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xi64>
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -346,16 +346,16 @@ func.func @or(%arga: tensor<32xi64, #SV>,
}
// CHECK-LABEL: func @xor(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xi64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<32xi64>) -> tensor<32xi64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi64>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xi64>
// CHECK: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xi64>
// CHECK: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xi64>
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -406,14 +406,14 @@ func.func @xor(%arga: tensor<32xi64, #SV>,
}
// CHECK-LABEL: func @ashrbyc(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xi64>) -> tensor<32xi64> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2 : i64
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi64>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xi64>
// CHECK: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xi64>
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
// CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -440,14 +440,14 @@ func.func @ashrbyc(%arga: tensor<32xi64, #SV>,
}
// CHECK-LABEL: func @lsrbyc(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xi64>) -> tensor<32xi64> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2 : i64
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi64>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xi64>
// CHECK: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xi64>
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
// CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -474,14 +474,14 @@ func.func @lsrbyc(%arga: tensor<32xi64, #SV>,
}
// CHECK-LABEL: func @lslbyc(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32xi64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<32xi64>) -> tensor<32xi64> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2 : i64
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi64>
+// CHECK: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32xi64, #sparse{{[0-9]*}}> to memref<?xi64>
// CHECK: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_1]] : memref<32xi64>
// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
// CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_4]]] : memref<?xindex>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_kernels.mlir b/mlir/test/Dialect/SparseTensor/sparse_kernels.mlir
index 276a864327daa9c..912d8bf5145e6c6 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_kernels.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_kernels.mlir
@@ -7,17 +7,17 @@
#DCSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed, d1 : compressed) }>
// CHECK-LABEL: func.func @matmul1(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<20x30xf32>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<10x30xf32>) -> tensor<10x30xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 30 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<20x30xf32>
// CHECK: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : memref<10x30xf32>
// CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -53,7 +53,7 @@ func.func @matmul1(%a: tensor<10x20xf32, #DCSR>,
// CHECK-LABEL: func.func @matmul_sparse_rhs(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20xf32>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<20x30xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<20x30xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<10x30xf32>) -> tensor<10x30xf32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 10 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
@@ -102,40 +102,40 @@ func.func @matmul_sparse_rhs(%a: tensor<10x20xf32>,
// Computes C = A x B with all matrices sparse (SpMSpM) in DCSR.
//
// CHECK-LABEL: func.func @matmul2(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<4x8xf64, #sparse_tensor.encoding<{{{.*}}}>>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<8x4xf64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<4x8xf64, #sparse{{[0-9]*}}>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<8x4xf64, #sparse{{[0-9]*}}>) -> tensor<4x4xf64, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant false
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
-// CHECK-DAG: %[[VAL_6:.*]] = tensor.empty() : tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<4x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<4x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<4x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<4x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<4x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<8x4xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<8x4xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<8x4xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<8x4xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<8x4xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_6:.*]] = tensor.empty() : tensor<4x4xf64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<4x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<4x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<4x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<4x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<4x8xf64, #sparse{{[0-9]*}}> to memref<?xf64>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<8x4xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<8x4xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<8x4xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<8x4xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<8x4xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_3]]] : memref<?xindex>
-// CHECK: %[[VAL_19:.*]] = scf.for %[[VAL_20:.*]] = %[[VAL_17]] to %[[VAL_18]] step %[[VAL_3]] iter_args(%[[VAL_21:.*]] = %[[VAL_6]]) -> (tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_19:.*]] = scf.for %[[VAL_20:.*]] = %[[VAL_17]] to %[[VAL_18]] step %[[VAL_3]] iter_args(%[[VAL_21:.*]] = %[[VAL_6]]) -> (tensor<4x4xf64, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_22:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_20]]] : memref<?xindex>
-// CHECK: %[[VAL_23:.*]], %[[VAL_24:.*]], %[[VAL_25:.*]], %[[VAL_26:.*]] = sparse_tensor.expand %[[VAL_6]] : tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>, memref<?xi1>, memref<?xindex>
+// CHECK: %[[VAL_23:.*]], %[[VAL_24:.*]], %[[VAL_25:.*]], %[[VAL_26:.*]] = sparse_tensor.expand %[[VAL_6]] : tensor<4x4xf64, #sparse{{[0-9]*}}> to memref<?xf64>, memref<?xi1>, memref<?xindex>
// CHECK: %[[VAL_27:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_20]]] : memref<?xindex>
// CHECK: %[[VAL_28:.*]] = arith.addi %[[VAL_20]], %[[VAL_3]] : index
// CHECK: %[[VAL_29:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_28]]] : memref<?xindex>
// CHECK: %[[VAL_30:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[VAL_31:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_3]]] : memref<?xindex>
-// CHECK: %[[VAL_32:.*]]:4 = scf.while (%[[VAL_33:.*]] = %[[VAL_27]], %[[VAL_34:.*]] = %[[VAL_30]], %[[VAL_35:.*]] = %[[VAL_26]], %[[VAL_36:.*]] = %[[VAL_21]]) : (index, index, index, tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>) -> (index, index, index, tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_32:.*]]:4 = scf.while (%[[VAL_33:.*]] = %[[VAL_27]], %[[VAL_34:.*]] = %[[VAL_30]], %[[VAL_35:.*]] = %[[VAL_26]], %[[VAL_36:.*]] = %[[VAL_21]]) : (index, index, index, tensor<4x4xf64, #sparse{{[0-9]*}}>) -> (index, index, index, tensor<4x4xf64, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_37:.*]] = arith.cmpi ult, %[[VAL_33]], %[[VAL_29]] : index
// CHECK: %[[VAL_38:.*]] = arith.cmpi ult, %[[VAL_34]], %[[VAL_31]] : index
// CHECK: %[[VAL_39:.*]] = arith.andi %[[VAL_37]], %[[VAL_38]] : i1
-// CHECK: scf.condition(%[[VAL_39]]) %[[VAL_33]], %[[VAL_34]], %[[VAL_35]], %[[VAL_36]] : index, index, index, tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.condition(%[[VAL_39]]) %[[VAL_33]], %[[VAL_34]], %[[VAL_35]], %[[VAL_36]] : index, index, index, tensor<4x4xf64, #sparse{{[0-9]*}}>
// CHECK: } do {
-// CHECK: ^bb0(%[[VAL_40:.*]]: index, %[[VAL_41:.*]]: index, %[[VAL_42:.*]]: index, %[[VAL_43:.*]]: tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>):
+// CHECK: ^bb0(%[[VAL_40:.*]]: index, %[[VAL_41:.*]]: index, %[[VAL_42:.*]]: index, %[[VAL_43:.*]]: tensor<4x4xf64, #sparse{{[0-9]*}}>):
// CHECK: %[[VAL_44:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_40]]] : memref<?xindex>
// CHECK: %[[VAL_45:.*]] = memref.load %[[VAL_13]]{{\[}}%[[VAL_41]]] : memref<?xindex>
// CHECK: %[[VAL_46:.*]] = arith.cmpi ult, %[[VAL_45]], %[[VAL_44]] : index
@@ -143,7 +143,7 @@ func.func @matmul_sparse_rhs(%a: tensor<10x20xf32>,
// CHECK: %[[VAL_48:.*]] = arith.cmpi eq, %[[VAL_44]], %[[VAL_47]] : index
// CHECK: %[[VAL_49:.*]] = arith.cmpi eq, %[[VAL_45]], %[[VAL_47]] : index
// CHECK: %[[VAL_50:.*]] = arith.andi %[[VAL_48]], %[[VAL_49]] : i1
-// CHECK: %[[VAL_51:.*]]:2 = scf.if %[[VAL_50]] -> (index, tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_51:.*]]:2 = scf.if %[[VAL_50]] -> (index, tensor<4x4xf64, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_52:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_40]]] : memref<?xf64>
// CHECK: %[[VAL_53:.*]] = memref.load %[[VAL_14]]{{\[}}%[[VAL_41]]] : memref<?xindex>
// CHECK: %[[VAL_54:.*]] = arith.addi %[[VAL_41]], %[[VAL_3]] : index
@@ -167,9 +167,9 @@ func.func @matmul_sparse_rhs(%a: tensor<10x20xf32>,
// CHECK: memref.store %[[VAL_63]], %[[VAL_23]]{{\[}}%[[VAL_59]]] : memref<?xf64>
// CHECK: scf.yield %[[VAL_68:.*]] : index
// CHECK: }
-// CHECK: scf.yield %[[VAL_69:.*]], %[[VAL_43]] : index, tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_69:.*]], %[[VAL_43]] : index, tensor<4x4xf64, #sparse{{[0-9]*}}>
// CHECK: } else {
-// CHECK: scf.yield %[[VAL_42]], %[[VAL_43]] : index, tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_42]], %[[VAL_43]] : index, tensor<4x4xf64, #sparse{{[0-9]*}}>
// CHECK: }
// CHECK: %[[VAL_70:.*]] = arith.cmpi eq, %[[VAL_44]], %[[VAL_47]] : index
// CHECK: %[[VAL_71:.*]] = arith.addi %[[VAL_40]], %[[VAL_3]] : index
@@ -177,13 +177,13 @@ func.func @matmul_sparse_rhs(%a: tensor<10x20xf32>,
// CHECK: %[[VAL_73:.*]] = arith.cmpi eq, %[[VAL_45]], %[[VAL_47]] : index
// CHECK: %[[VAL_74:.*]] = arith.addi %[[VAL_41]], %[[VAL_3]] : index
// CHECK: %[[VAL_75:.*]] = arith.select %[[VAL_73]], %[[VAL_74]], %[[VAL_41]] : index
-// CHECK: scf.yield %[[VAL_72]], %[[VAL_75]], %[[VAL_76:.*]]#0, %[[VAL_76]]#1 : index, index, index, tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_72]], %[[VAL_75]], %[[VAL_76:.*]]#0, %[[VAL_76]]#1 : index, index, index, tensor<4x4xf64, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: %[[VAL_77:.*]] = sparse_tensor.compress %[[VAL_23]], %[[VAL_24]], %[[VAL_25]], %[[VAL_78:.*]]#2 into %[[VAL_78]]#3{{\[}}%[[VAL_22]]] : memref<?xf64>, memref<?xi1>, memref<?xindex>, tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: scf.yield %[[VAL_77]] : tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_77:.*]] = sparse_tensor.compress %[[VAL_23]], %[[VAL_24]], %[[VAL_25]], %[[VAL_78:.*]]#2 into %[[VAL_78]]#3{{\[}}%[[VAL_22]]] : memref<?xf64>, memref<?xi1>, memref<?xindex>, tensor<4x4xf64, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_77]] : tensor<4x4xf64, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: %[[VAL_79:.*]] = sparse_tensor.load %[[VAL_80:.*]] hasInserts : tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_79]] : tensor<4x4xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_79:.*]] = sparse_tensor.load %[[VAL_80:.*]] hasInserts : tensor<4x4xf64, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_79]] : tensor<4x4xf64, #sparse{{[0-9]*}}>
// CHECK: }
func.func @matmul2(%A: tensor<4x8xf64, #DCSR>,
%B: tensor<8x4xf64, #DCSR>) -> tensor<4x4xf64, #DCSR> {
@@ -198,18 +198,18 @@ func.func @matmul2(%A: tensor<4x8xf64, #DCSR>,
// CHECK-LABEL: func.func @conv2d(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xi32>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<3x3xi32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<3x3xi32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<6x6xi32>) -> tensor<6x6xi32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 6 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_0]] : memref<8x8xi32>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<3x3xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<3x3xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<3x3xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<3x3xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<3x3xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi32>
-// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : memref<6x6xi32>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<3x3xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<3x3xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<3x3xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<3x3xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<3x3xi32, #sparse{{[0-9]*}}> to memref<?xi32>
+// CHECK: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : memref<6x6xi32>
// CHECK: scf.for %[[VAL_13:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
// CHECK: scf.for %[[VAL_14:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_13]], %[[VAL_14]]] : memref<6x6xi32>
@@ -249,18 +249,18 @@ func.func @conv2d(%input: tensor<8x8xi32>,
// CHECK-LABEL: func.func @quantized_matmul(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<5x3xi8>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<3x6xi8, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<3x6xi8, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<5x6xi64>) -> tensor<5x6xi64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 5 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 2 : i64
// CHECK-DAG: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_0]] : memref<5x3xi8>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<3x6xi8, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<3x6xi8, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<3x6xi8, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<3x6xi8, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<3x6xi8, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi8>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<3x6xi8, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<3x6xi8, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<3x6xi8, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<3x6xi8, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<3x6xi8, #sparse{{[0-9]*}}> to memref<?xi8>
// CHECK: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_2]] : memref<5x6xi64>
// CHECK: scf.for %[[VAL_14:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -299,16 +299,16 @@ func.func @quantized_matmul(%input1: tensor<5x3xi8>,
}
// CHECK-LABEL: func.func @sparse_dot(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<1024xf32, #sparse_tensor.encoding<{{{.*}}}>>, %[[VAL_1:.*1]]: tensor<1024xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<1024xf32, #sparse{{[0-9]*}}>, %[[VAL_1:.*1]]: tensor<1024xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*2]]: tensor<f32>) -> tensor<f32> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<1024xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<1024xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<1024xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<1024xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<1024xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<1024xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<1024xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<1024xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<1024xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<1024xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<1024xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<1024xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<f32>
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_11]][] : memref<f32>
// CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_3]]] : memref<?xindex>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_lower.mlir b/mlir/test/Dialect/SparseTensor/sparse_lower.mlir
index 788dd9c26e6cd38..6112856fbf29312 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_lower.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_lower.mlir
@@ -21,15 +21,15 @@
}
// CHECK-HIR-LABEL: func @matvec(
-// CHECK-HIR-SAME: %[[VAL_0:.*]]: tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-HIR-SAME: %[[VAL_0:.*]]: tensor<32x64xf64, #sparse{{[0-9]*}}>
// CHECK-HIR-SAME: %[[VAL_1:.*]]: tensor<64xf64>,
// CHECK-HIR-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-HIR-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-HIR-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-HIR-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-HIR-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-HIR-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-HIR-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-HIR-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}>
+// CHECK-HIR-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}>
+// CHECK-HIR-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x64xf64, #sparse{{[0-9]*}}>
// CHECK-HIR-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<64xf64>
// CHECK-HIR-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xf64>
// CHECK-HIR: scf.for %[[VAL_12:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_lower_col.mlir b/mlir/test/Dialect/SparseTensor/sparse_lower_col.mlir
index da08f53bd089bd5..401da152a8bdb81 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_lower_col.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_lower_col.mlir
@@ -23,7 +23,7 @@
}
// CHECK-HIR-LABEL: func @matvec(
-// CHECK-HIR-SAME: %[[VAL_0:.*]]: tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-HIR-SAME: %[[VAL_0:.*]]: tensor<32x64xf64, #sparse{{[0-9]*}}>,
// CHECK-HIR-SAME: %[[VAL_1:.*]]: tensor<64xf64>,
// CHECK-HIR-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-HIR-DAG: %[[VAL_3:.*]] = arith.constant 64 : index
diff --git a/mlir/test/Dialect/SparseTensor/sparse_lower_inplace.mlir b/mlir/test/Dialect/SparseTensor/sparse_lower_inplace.mlir
index eb6920304ed8479..d769876d8ee8e33 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_lower_inplace.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_lower_inplace.mlir
@@ -21,15 +21,15 @@
}
// CHECK-HIR-LABEL: func @matvec(
-// CHECK-HIR-SAME: %[[VAL_0:.*]]: tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-HIR-SAME: %[[VAL_0:.*]]: tensor<32x64xf64, #sparse{{[0-9]*}}>,
// CHECK-HIR-SAME: %[[VAL_1:.*]]: tensor<64xf64>,
// CHECK-HIR-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {
// CHECK-HIR-DAG: %[[VAL_3:.*]] = arith.constant 32 : index
// CHECK-HIR-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-HIR-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-HIR: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-HIR: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-HIR: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x64xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-HIR: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}>
+// CHECK-HIR: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x64xf64, #sparse{{[0-9]*}}>
+// CHECK-HIR: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x64xf64, #sparse{{[0-9]*}}>
// CHECK-HIR: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<64xf64>
// CHECK-HIR: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]] : memref<32xf64>
// CHECK-HIR: scf.for %[[VAL_11:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_nd.mlir b/mlir/test/Dialect/SparseTensor/sparse_nd.mlir
index 27716a82c164fa0..50fec5b05f92106 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_nd.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_nd.mlir
@@ -24,7 +24,7 @@
// CHECK-LABEL: func @mul(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20x30x40x50x60x70x80xf32>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<80x70x60x50x40x30x20x10xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<80x70x60x50x40x30x20x10xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<10x20x30x40x50x60x70x80xf32>) -> tensor<10x20x30x40x50x60x70x80xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 10 : index
@@ -36,11 +36,11 @@
// CHECK-DAG: %[[VAL_11:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_12:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_13:.*]] = bufferization.to_memref %[[VAL_0]] : memref<10x20x30x40x50x60x70x80xf32>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 3 : index} : tensor<80x70x60x50x40x30x20x10xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 3 : index} : tensor<80x70x60x50x40x30x20x10xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 4 : index} : tensor<80x70x60x50x40x30x20x10xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_17:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 4 : index} : tensor<80x70x60x50x40x30x20x10xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_18:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<80x70x60x50x40x30x20x10xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 3 : index} : tensor<80x70x60x50x40x30x20x10xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 3 : index} : tensor<80x70x60x50x40x30x20x10xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 4 : index} : tensor<80x70x60x50x40x30x20x10xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_17:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 4 : index} : tensor<80x70x60x50x40x30x20x10xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_18:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<80x70x60x50x40x30x20x10xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_20:.*]] = bufferization.to_memref %[[VAL_2]] : memref<10x20x30x40x50x60x70x80xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_20]] : memref<10x20x30x40x50x60x70x80xf32>
// CHECK: scf.for %[[VAL_21:.*]] = %[[VAL_11]] to %[[VAL_10]] step %[[VAL_12]] {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_out.mlir b/mlir/test/Dialect/SparseTensor/sparse_out.mlir
index 8bf0625425ead11..b1795ff2e1a2268 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_out.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_out.mlir
@@ -21,13 +21,13 @@
}
// CHECK-LABEL: func.func @sparse_simply_dynamic1(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>) -> tensor<32x16xf32, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 2.000000e+00 : f32
-// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: %[[VAL_7:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_1]]] : memref<?xindex>
// CHECK: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: scf.for %[[VAL_9:.*]] = %[[VAL_7]] to %[[VAL_8]] step %[[VAL_2]] {
@@ -40,8 +40,8 @@
// CHECK: memref.store %[[VAL_15]], %[[VAL_6]]{{\[}}%[[VAL_13]]] : memref<?xf32>
// CHECK: }
// CHECK: }
-// CHECK: %[[VAL_16:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_16]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_16:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_16]] : tensor<32x16xf32, #sparse{{[0-9]*}}>
// CHECK: }
func.func @sparse_simply_dynamic1(%argx: tensor<32x16xf32, #DCSR>) -> tensor<32x16xf32, #DCSR> {
%c = arith.constant 2.0 : f32
@@ -55,12 +55,12 @@ func.func @sparse_simply_dynamic1(%argx: tensor<32x16xf32, #DCSR>) -> tensor<32x
}
// CHECK-LABEL: func.func @sparse_simply_dynamic2(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse{{[0-9]*}}>) -> tensor<32x16xf32, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_3:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_3:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: %[[VAL_6:.*]] = memref.load %[[VAL_3]]{{\[}}%[[VAL_1]]] : memref<?xindex>
// CHECK: %[[VAL_7:.*]] = memref.load %[[VAL_3]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: scf.for %[[VAL_8:.*]] = %[[VAL_6]] to %[[VAL_7]] step %[[VAL_2]] {
@@ -74,8 +74,8 @@ func.func @sparse_simply_dynamic1(%argx: tensor<32x16xf32, #DCSR>) -> tensor<32x
// CHECK: memref.store %[[VAL_15]], %[[VAL_5]]{{\[}}%[[VAL_12]]] : memref<?xf32>
// CHECK: }
// CHECK: }
-// CHECK: %[[VAL_16:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_16]] : tensor<32x16xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_16:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_16]] : tensor<32x16xf32, #sparse{{[0-9]*}}>
// CHECK: }
func.func @sparse_simply_dynamic2(%argx: tensor<32x16xf32, #DCSR>) -> tensor<32x16xf32, #DCSR> {
%0 = linalg.generic #trait_scale_inpl
@@ -97,30 +97,30 @@ func.func @sparse_simply_dynamic2(%argx: tensor<32x16xf32, #DCSR>) -> tensor<32x
}
// CHECK-LABEL: func.func @sparse_truly_dynamic(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20xf32, #sparse{{[0-9]*}}>) -> tensor<10x20xf32, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 10 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 2.000000e+00 : f32
-// CHECK-DAG: %[[VAL_5:.*]] = tensor.empty() : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK: %[[VAL_9:.*]] = scf.for %[[VAL_10:.*]] = %[[VAL_2]] to %[[VAL_1]] step %[[VAL_3]] iter_args(%[[VAL_11:.*]] = %[[VAL_5]]) -> (tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK-DAG: %[[VAL_5:.*]] = tensor.empty() : tensor<10x20xf32, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10x20xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK: %[[VAL_9:.*]] = scf.for %[[VAL_10:.*]] = %[[VAL_2]] to %[[VAL_1]] step %[[VAL_3]] iter_args(%[[VAL_11:.*]] = %[[VAL_5]]) -> (tensor<10x20xf32, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_10]]] : memref<?xindex>
// CHECK: %[[VAL_13:.*]] = arith.addi %[[VAL_10]], %[[VAL_3]] : index
// CHECK: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_13]]] : memref<?xindex>
-// CHECK: %[[VAL_15:.*]] = scf.for %[[VAL_16:.*]] = %[[VAL_12]] to %[[VAL_14]] step %[[VAL_3]] iter_args(%[[VAL_17:.*]] = %[[VAL_11]]) -> (tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_15:.*]] = scf.for %[[VAL_16:.*]] = %[[VAL_12]] to %[[VAL_14]] step %[[VAL_3]] iter_args(%[[VAL_17:.*]] = %[[VAL_11]]) -> (tensor<10x20xf32, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_16]]] : memref<?xindex>
// CHECK: %[[VAL_19:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_16]]] : memref<?xf32>
// CHECK: %[[VAL_20:.*]] = arith.mulf %[[VAL_19]], %[[VAL_4]] : f32
-// CHECK: %[[VAL_21:.*]] = sparse_tensor.insert %[[VAL_20]] into %[[VAL_17]]{{\[}}%[[VAL_10]], %[[VAL_18]]] : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: scf.yield %[[VAL_21]] : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_21:.*]] = sparse_tensor.insert %[[VAL_20]] into %[[VAL_17]]{{\[}}%[[VAL_10]], %[[VAL_18]]] : tensor<10x20xf32, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_21]] : tensor<10x20xf32, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: scf.yield %[[VAL_22:.*]] : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_22:.*]] : tensor<10x20xf32, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: %[[VAL_23:.*]] = sparse_tensor.load %[[VAL_24:.*]] hasInserts : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_23]] : tensor<10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_23:.*]] = sparse_tensor.load %[[VAL_24:.*]] hasInserts : tensor<10x20xf32, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_23]] : tensor<10x20xf32, #sparse{{[0-9]*}}>
// CHECK: }
func.func @sparse_truly_dynamic(%arga: tensor<10x20xf32, #CSR>) -> tensor<10x20xf32, #DCSR> {
%s = arith.constant 2.0 : f32
@@ -146,41 +146,41 @@ func.func @sparse_truly_dynamic(%arga: tensor<10x20xf32, #CSR>) -> tensor<10x20x
}
// CHECK-LABEL: func.func @sumred(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?x?xi32, #sparse{{[0-9]*}}>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<?x?x?xi32, #sparse{{[0-9]*}}>) -> tensor<?x?xi32, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : i32
// CHECK-DAG: %[[VAL_FALSE:.*]] = arith.constant false
// CHECK-DAG: %[[VAL_TRUE:.*]] = arith.constant true
-// CHECK: %[[VAL_5:.*]] = tensor.dim %[[VAL_0]], %[[VAL_2]] : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_6:.*]] = tensor.dim %[[VAL_0]], %[[VAL_3]] : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_7:.*]] = tensor.empty(%[[VAL_5]], %[[VAL_6]]) : tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi32>
-// CHECK: %[[VAL_15:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_16:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_17:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_18:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_19:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 2 : index} : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_20:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 2 : index} : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_21:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?x?x?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi32>
+// CHECK: %[[VAL_5:.*]] = tensor.dim %[[VAL_0]], %[[VAL_2]] : tensor<?x?x?xi32, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_6:.*]] = tensor.dim %[[VAL_0]], %[[VAL_3]] : tensor<?x?x?xi32, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_7:.*]] = tensor.empty(%[[VAL_5]], %[[VAL_6]]) : tensor<?x?xi32, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_10:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_11:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_12:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 2 : index} : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_13:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 2 : index} : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_14:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xi32>
+// CHECK: %[[VAL_15:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_16:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_17:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_18:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_19:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 2 : index} : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_20:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 2 : index} : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_21:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?x?x?xi32, #sparse{{[0-9]*}}> to memref<?xi32>
// CHECK: %[[VAL_22:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[VAL_23:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_3]]] : memref<?xindex>
// CHECK: %[[VAL_24:.*]] = memref.load %[[VAL_15]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[VAL_25:.*]] = memref.load %[[VAL_15]]{{\[}}%[[VAL_3]]] : memref<?xindex>
-// CHECK: %[[VAL_26:.*]]:3 = scf.while (%[[VAL_27:.*]] = %[[VAL_22]], %[[VAL_28:.*]] = %[[VAL_24]], %[[VAL_29:.*]] = %[[VAL_7]]) : (index, index, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>) -> (index, index, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_26:.*]]:3 = scf.while (%[[VAL_27:.*]] = %[[VAL_22]], %[[VAL_28:.*]] = %[[VAL_24]], %[[VAL_29:.*]] = %[[VAL_7]]) : (index, index, tensor<?x?xi32, #sparse{{[0-9]*}}>) -> (index, index, tensor<?x?xi32, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_30:.*]] = arith.cmpi ult, %[[VAL_27]], %[[VAL_23]] : index
// CHECK: %[[VAL_31:.*]] = arith.cmpi ult, %[[VAL_28]], %[[VAL_25]] : index
// CHECK: %[[VAL_32:.*]] = arith.andi %[[VAL_30]], %[[VAL_31]] : i1
-// CHECK: scf.condition(%[[VAL_32]]) %[[VAL_27]], %[[VAL_28]], %[[VAL_29]] : index, index, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.condition(%[[VAL_32]]) %[[VAL_27]], %[[VAL_28]], %[[VAL_29]] : index, index, tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: } do {
-// CHECK: ^bb0(%[[VAL_33:.*]]: index, %[[VAL_34:.*]]: index, %[[VAL_35:.*]]: tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>):
+// CHECK: ^bb0(%[[VAL_33:.*]]: index, %[[VAL_34:.*]]: index, %[[VAL_35:.*]]: tensor<?x?xi32, #sparse{{[0-9]*}}>):
// CHECK: %[[VAL_36:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_33]]] : memref<?xindex>
// CHECK: %[[VAL_37:.*]] = memref.load %[[VAL_16]]{{\[}}%[[VAL_34]]] : memref<?xindex>
// CHECK: %[[VAL_38:.*]] = arith.cmpi ult, %[[VAL_37]], %[[VAL_36]] : index
@@ -188,20 +188,20 @@ func.func @sparse_truly_dynamic(%arga: tensor<10x20xf32, #CSR>) -> tensor<10x20x
// CHECK: %[[VAL_40:.*]] = arith.cmpi eq, %[[VAL_36]], %[[VAL_39]] : index
// CHECK: %[[VAL_41:.*]] = arith.cmpi eq, %[[VAL_37]], %[[VAL_39]] : index
// CHECK: %[[VAL_42:.*]] = arith.andi %[[VAL_40]], %[[VAL_41]] : i1
-// CHECK: %[[VAL_43:.*]] = scf.if %[[VAL_42]] -> (tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_43:.*]] = scf.if %[[VAL_42]] -> (tensor<?x?xi32, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_44:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_33]]] : memref<?xindex>
// CHECK: %[[VAL_45:.*]] = arith.addi %[[VAL_33]], %[[VAL_3]] : index
// CHECK: %[[VAL_46:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_45]]] : memref<?xindex>
// CHECK: %[[VAL_47:.*]] = memref.load %[[VAL_17]]{{\[}}%[[VAL_34]]] : memref<?xindex>
// CHECK: %[[VAL_48:.*]] = arith.addi %[[VAL_34]], %[[VAL_3]] : index
// CHECK: %[[VAL_49:.*]] = memref.load %[[VAL_17]]{{\[}}%[[VAL_48]]] : memref<?xindex>
-// CHECK: %[[VAL_50:.*]]:3 = scf.while (%[[VAL_51:.*]] = %[[VAL_44]], %[[VAL_52:.*]] = %[[VAL_47]], %[[VAL_53:.*]] = %[[VAL_35]]) : (index, index, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>) -> (index, index, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_50:.*]]:3 = scf.while (%[[VAL_51:.*]] = %[[VAL_44]], %[[VAL_52:.*]] = %[[VAL_47]], %[[VAL_53:.*]] = %[[VAL_35]]) : (index, index, tensor<?x?xi32, #sparse{{[0-9]*}}>) -> (index, index, tensor<?x?xi32, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_54:.*]] = arith.cmpi ult, %[[VAL_51]], %[[VAL_46]] : index
// CHECK: %[[VAL_55:.*]] = arith.cmpi ult, %[[VAL_52]], %[[VAL_49]] : index
// CHECK: %[[VAL_56:.*]] = arith.andi %[[VAL_54]], %[[VAL_55]] : i1
-// CHECK: scf.condition(%[[VAL_56]]) %[[VAL_51]], %[[VAL_52]], %[[VAL_53]] : index, index, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.condition(%[[VAL_56]]) %[[VAL_51]], %[[VAL_52]], %[[VAL_53]] : index, index, tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: } do {
-// CHECK: ^bb0(%[[VAL_57:.*]]: index, %[[VAL_58:.*]]: index, %[[VAL_59:.*]]: tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>):
+// CHECK: ^bb0(%[[VAL_57:.*]]: index, %[[VAL_58:.*]]: index, %[[VAL_59:.*]]: tensor<?x?xi32, #sparse{{[0-9]*}}>):
// CHECK: %[[VAL_60:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_57]]] : memref<?xindex>
// CHECK: %[[VAL_61:.*]] = memref.load %[[VAL_18]]{{\[}}%[[VAL_58]]] : memref<?xindex>
// CHECK: %[[VAL_62:.*]] = arith.cmpi ult, %[[VAL_61]], %[[VAL_60]] : index
@@ -209,20 +209,20 @@ func.func @sparse_truly_dynamic(%arga: tensor<10x20xf32, #CSR>) -> tensor<10x20x
// CHECK: %[[VAL_64:.*]] = arith.cmpi eq, %[[VAL_60]], %[[VAL_63]] : index
// CHECK: %[[VAL_65:.*]] = arith.cmpi eq, %[[VAL_61]], %[[VAL_63]] : index
// CHECK: %[[VAL_66:.*]] = arith.andi %[[VAL_64]], %[[VAL_65]] : i1
-// CHECK: %[[VAL_67:.*]] = scf.if %[[VAL_66]] -> (tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_67:.*]] = scf.if %[[VAL_66]] -> (tensor<?x?xi32, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_68:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_57]]] : memref<?xindex>
// CHECK: %[[VAL_69:.*]] = arith.addi %[[VAL_57]], %[[VAL_3]] : index
// CHECK: %[[VAL_70:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_69]]] : memref<?xindex>
// CHECK: %[[VAL_71:.*]] = memref.load %[[VAL_19]]{{\[}}%[[VAL_58]]] : memref<?xindex>
// CHECK: %[[VAL_72:.*]] = arith.addi %[[VAL_58]], %[[VAL_3]] : index
// CHECK: %[[VAL_73:.*]] = memref.load %[[VAL_19]]{{\[}}%[[VAL_72]]] : memref<?xindex>
-// CHECK: %[[VAL_74:.*]]:5 = scf.while (%[[VAL_75:.*]] = %[[VAL_68]], %[[VAL_76:.*]] = %[[VAL_71]], %[[VAL_77:.*]] = %[[VAL_4]], %[[VAL_200:.*]] = %[[VAL_FALSE]], %[[VAL_78:.*]] = %[[VAL_59]]) : (index, index, i32, i1, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>) -> (index, index, i32, i1, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_74:.*]]:5 = scf.while (%[[VAL_75:.*]] = %[[VAL_68]], %[[VAL_76:.*]] = %[[VAL_71]], %[[VAL_77:.*]] = %[[VAL_4]], %[[VAL_200:.*]] = %[[VAL_FALSE]], %[[VAL_78:.*]] = %[[VAL_59]]) : (index, index, i32, i1, tensor<?x?xi32, #sparse{{[0-9]*}}>) -> (index, index, i32, i1, tensor<?x?xi32, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_79:.*]] = arith.cmpi ult, %[[VAL_75]], %[[VAL_70]] : index
// CHECK: %[[VAL_80:.*]] = arith.cmpi ult, %[[VAL_76]], %[[VAL_73]] : index
// CHECK: %[[VAL_81:.*]] = arith.andi %[[VAL_79]], %[[VAL_80]] : i1
-// CHECK: scf.condition(%[[VAL_81]]) %[[VAL_75]], %[[VAL_76]], %[[VAL_77]], %[[VAL_200]], %[[VAL_78]] : index, index, i32, i1, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.condition(%[[VAL_81]]) %[[VAL_75]], %[[VAL_76]], %[[VAL_77]], %[[VAL_200]], %[[VAL_78]] : index, index, i32, i1, tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: } do {
-// CHECK: ^bb0(%[[VAL_82:.*]]: index, %[[VAL_83:.*]]: index, %[[VAL_84:.*]]: i32, %[[VAL_201:.*]]: i1, %[[VAL_85:.*]]: tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>):
+// CHECK: ^bb0(%[[VAL_82:.*]]: index, %[[VAL_83:.*]]: index, %[[VAL_84:.*]]: i32, %[[VAL_201:.*]]: i1, %[[VAL_85:.*]]: tensor<?x?xi32, #sparse{{[0-9]*}}>):
// CHECK: %[[VAL_86:.*]] = memref.load %[[VAL_13]]{{\[}}%[[VAL_82]]] : memref<?xindex>
// CHECK: %[[VAL_87:.*]] = memref.load %[[VAL_20]]{{\[}}%[[VAL_83]]] : memref<?xindex>
// CHECK: %[[VAL_88:.*]] = arith.cmpi ult, %[[VAL_87]], %[[VAL_86]] : index
@@ -230,14 +230,14 @@ func.func @sparse_truly_dynamic(%arga: tensor<10x20xf32, #CSR>) -> tensor<10x20x
// CHECK: %[[VAL_90:.*]] = arith.cmpi eq, %[[VAL_86]], %[[VAL_89]] : index
// CHECK: %[[VAL_91:.*]] = arith.cmpi eq, %[[VAL_87]], %[[VAL_89]] : index
// CHECK: %[[VAL_92:.*]] = arith.andi %[[VAL_90]], %[[VAL_91]] : i1
-// CHECK: %[[VAL_93:.*]]:3 = scf.if %[[VAL_92]] -> (i32, i1, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_93:.*]]:3 = scf.if %[[VAL_92]] -> (i32, i1, tensor<?x?xi32, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_94:.*]] = memref.load %[[VAL_14]]{{\[}}%[[VAL_82]]] : memref<?xi32>
// CHECK: %[[VAL_95:.*]] = memref.load %[[VAL_21]]{{\[}}%[[VAL_83]]] : memref<?xi32>
// CHECK: %[[VAL_96:.*]] = arith.muli %[[VAL_94]], %[[VAL_95]] : i32
// CHECK: %[[VAL_97:.*]] = arith.addi %[[VAL_84]], %[[VAL_96]] : i32
-// CHECK: scf.yield %[[VAL_97]], %[[VAL_TRUE]], %[[VAL_85]] : i32, i1, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_97]], %[[VAL_TRUE]], %[[VAL_85]] : i32, i1, tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: } else {
-// CHECK: scf.yield %[[VAL_84]], %[[VAL_201]], %[[VAL_85]] : i32, i1, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_84]], %[[VAL_201]], %[[VAL_85]] : i32, i1, tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: }
// CHECK: %[[VAL_98:.*]] = arith.cmpi eq, %[[VAL_86]], %[[VAL_89]] : index
// CHECK: %[[VAL_99:.*]] = arith.addi %[[VAL_82]], %[[VAL_3]] : index
@@ -245,17 +245,17 @@ func.func @sparse_truly_dynamic(%arga: tensor<10x20xf32, #CSR>) -> tensor<10x20x
// CHECK: %[[VAL_101:.*]] = arith.cmpi eq, %[[VAL_87]], %[[VAL_89]] : index
// CHECK: %[[VAL_102:.*]] = arith.addi %[[VAL_83]], %[[VAL_3]] : index
// CHECK: %[[VAL_103:.*]] = arith.select %[[VAL_101]], %[[VAL_102]], %[[VAL_83]] : index
-// CHECK: scf.yield %[[VAL_100]], %[[VAL_103]], %[[VAL_104:.*]]#0, %[[VAL_104]]#1, %[[VAL_104]]#2 : index, index, i32, i1, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_100]], %[[VAL_103]], %[[VAL_104:.*]]#0, %[[VAL_104]]#1, %[[VAL_104]]#2 : index, index, i32, i1, tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: %[[VAL_202:.*]] = scf.if %[[VAL_74]]#3 -> (tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>) {
-// CHECK: %[[VAL_105:.*]] = sparse_tensor.insert %[[VAL_74]]#2 into %[[VAL_74]]#4{{\[}}%[[VAL_39]], %[[VAL_63]]] : tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: scf.yield %[[VAL_105]] : tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_202:.*]] = scf.if %[[VAL_74]]#3 -> (tensor<?x?xi32, #sparse{{[0-9]*}}>) {
+// CHECK: %[[VAL_105:.*]] = sparse_tensor.insert %[[VAL_74]]#2 into %[[VAL_74]]#4{{\[}}%[[VAL_39]], %[[VAL_63]]] : tensor<?x?xi32, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_105]] : tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: } else {
-// CHECK: scf.yield %[[VAL_74]]#4 : tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_74]]#4 : tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: scf.yield %[[VAL_202]] : tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_202]] : tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: } else {
-// CHECK: scf.yield %[[VAL_59]] : tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_59]] : tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: }
// CHECK: %[[VAL_107:.*]] = arith.cmpi eq, %[[VAL_60]], %[[VAL_63]] : index
// CHECK: %[[VAL_108:.*]] = arith.addi %[[VAL_57]], %[[VAL_3]] : index
@@ -263,11 +263,11 @@ func.func @sparse_truly_dynamic(%arga: tensor<10x20xf32, #CSR>) -> tensor<10x20x
// CHECK: %[[VAL_110:.*]] = arith.cmpi eq, %[[VAL_61]], %[[VAL_63]] : index
// CHECK: %[[VAL_111:.*]] = arith.addi %[[VAL_58]], %[[VAL_3]] : index
// CHECK: %[[VAL_112:.*]] = arith.select %[[VAL_110]], %[[VAL_111]], %[[VAL_58]] : index
-// CHECK: scf.yield %[[VAL_109]], %[[VAL_112]], %[[VAL_113:.*]] : index, index, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_109]], %[[VAL_112]], %[[VAL_113:.*]] : index, index, tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: scf.yield %[[VAL_114:.*]]#2 : tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_114:.*]]#2 : tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: } else {
-// CHECK: scf.yield %[[VAL_35]] : tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_35]] : tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: }
// CHECK: %[[VAL_115:.*]] = arith.cmpi eq, %[[VAL_36]], %[[VAL_39]] : index
// CHECK: %[[VAL_116:.*]] = arith.addi %[[VAL_33]], %[[VAL_3]] : index
@@ -275,10 +275,10 @@ func.func @sparse_truly_dynamic(%arga: tensor<10x20xf32, #CSR>) -> tensor<10x20x
// CHECK: %[[VAL_118:.*]] = arith.cmpi eq, %[[VAL_37]], %[[VAL_39]] : index
// CHECK: %[[VAL_119:.*]] = arith.addi %[[VAL_34]], %[[VAL_3]] : index
// CHECK: %[[VAL_120:.*]] = arith.select %[[VAL_118]], %[[VAL_119]], %[[VAL_34]] : index
-// CHECK: scf.yield %[[VAL_117]], %[[VAL_120]], %[[VAL_121:.*]] : index, index, tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_117]], %[[VAL_120]], %[[VAL_121:.*]] : index, index, tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: %[[VAL_122:.*]] = sparse_tensor.load %[[VAL_123:.*]]#2 hasInserts : tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_122]] : tensor<?x?xi32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_122:.*]] = sparse_tensor.load %[[VAL_123:.*]]#2 hasInserts : tensor<?x?xi32, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_122]] : tensor<?x?xi32, #sparse{{[0-9]*}}>
// CHECK: }
func.func @sumred(%arga: tensor<?x?x?xi32, #SparseTensor>,
%argb: tensor<?x?x?xi32, #SparseTensor>) -> tensor<?x?xi32, #DCSR> {
@@ -310,42 +310,42 @@ func.func @sumred(%arga: tensor<?x?x?xi32, #SparseTensor>,
}
// CHECK-LABEL: func.func @matmat(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?xf32, #sparse{{[0-9]*}}>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<?x?xf32, #sparse{{[0-9]*}}>) -> tensor<?x?xf32, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant false
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant true
-// CHECK: %[[VAL_6:.*]] = tensor.dim %[[VAL_0]], %[[VAL_2]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_7:.*]] = tensor.dim %[[VAL_1]], %[[VAL_3]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_8:.*]] = tensor.empty(%[[VAL_6]], %[[VAL_7]]) : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
-// CHECK: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_16:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_17:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_18:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK: %[[VAL_6:.*]] = tensor.dim %[[VAL_0]], %[[VAL_2]] : tensor<?x?xf32, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_7:.*]] = tensor.dim %[[VAL_1]], %[[VAL_3]] : tensor<?x?xf32, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_8:.*]] = tensor.empty(%[[VAL_6]], %[[VAL_7]]) : tensor<?x?xf32, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
+// CHECK: %[[VAL_14:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_15:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 0 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_16:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_17:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_18:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK: %[[VAL_19:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[VAL_20:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_3]]] : memref<?xindex>
-// CHECK: %[[VAL_21:.*]] = scf.for %[[VAL_22:.*]] = %[[VAL_19]] to %[[VAL_20]] step %[[VAL_3]] iter_args(%[[VAL_23:.*]] = %[[VAL_8]]) -> (tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_21:.*]] = scf.for %[[VAL_22:.*]] = %[[VAL_19]] to %[[VAL_20]] step %[[VAL_3]] iter_args(%[[VAL_23:.*]] = %[[VAL_8]]) -> (tensor<?x?xf32, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_24:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_22]]] : memref<?xindex>
-// CHECK: %[[VAL_25:.*]], %[[VAL_26:.*]], %[[VAL_27:.*]], %[[VAL_28:.*]] = sparse_tensor.expand %[[VAL_8]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>, memref<?xi1>, memref<?xindex>
+// CHECK: %[[VAL_25:.*]], %[[VAL_26:.*]], %[[VAL_27:.*]], %[[VAL_28:.*]] = sparse_tensor.expand %[[VAL_8]] : tensor<?x?xf32, #sparse{{[0-9]*}}> to memref<?xf32>, memref<?xi1>, memref<?xindex>
// CHECK: %[[VAL_29:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_22]]] : memref<?xindex>
// CHECK: %[[VAL_30:.*]] = arith.addi %[[VAL_22]], %[[VAL_3]] : index
// CHECK: %[[VAL_31:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_30]]] : memref<?xindex>
// CHECK: %[[VAL_32:.*]] = memref.load %[[VAL_14]]{{\[}}%[[VAL_2]]] : memref<?xindex>
// CHECK: %[[VAL_33:.*]] = memref.load %[[VAL_14]]{{\[}}%[[VAL_3]]] : memref<?xindex>
-// CHECK: %[[VAL_34:.*]]:4 = scf.while (%[[VAL_35:.*]] = %[[VAL_29]], %[[VAL_36:.*]] = %[[VAL_32]], %[[VAL_37:.*]] = %[[VAL_28]], %[[VAL_38:.*]] = %[[VAL_23]]) : (index, index, index, tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>) -> (index, index, index, tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_34:.*]]:4 = scf.while (%[[VAL_35:.*]] = %[[VAL_29]], %[[VAL_36:.*]] = %[[VAL_32]], %[[VAL_37:.*]] = %[[VAL_28]], %[[VAL_38:.*]] = %[[VAL_23]]) : (index, index, index, tensor<?x?xf32, #sparse{{[0-9]*}}>) -> (index, index, index, tensor<?x?xf32, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_39:.*]] = arith.cmpi ult, %[[VAL_35]], %[[VAL_31]] : index
// CHECK: %[[VAL_40:.*]] = arith.cmpi ult, %[[VAL_36]], %[[VAL_33]] : index
// CHECK: %[[VAL_41:.*]] = arith.andi %[[VAL_39]], %[[VAL_40]] : i1
-// CHECK: scf.condition(%[[VAL_41]]) %[[VAL_35]], %[[VAL_36]], %[[VAL_37]], %[[VAL_38]] : index, index, index, tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.condition(%[[VAL_41]]) %[[VAL_35]], %[[VAL_36]], %[[VAL_37]], %[[VAL_38]] : index, index, index, tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: } do {
-// CHECK: ^bb0(%[[VAL_42:.*]]: index, %[[VAL_43:.*]]: index, %[[VAL_44:.*]]: index, %[[VAL_45:.*]]: tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>):
+// CHECK: ^bb0(%[[VAL_42:.*]]: index, %[[VAL_43:.*]]: index, %[[VAL_44:.*]]: index, %[[VAL_45:.*]]: tensor<?x?xf32, #sparse{{[0-9]*}}>):
// CHECK: %[[VAL_46:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_42]]] : memref<?xindex>
// CHECK: %[[VAL_47:.*]] = memref.load %[[VAL_15]]{{\[}}%[[VAL_43]]] : memref<?xindex>
// CHECK: %[[VAL_48:.*]] = arith.cmpi ult, %[[VAL_47]], %[[VAL_46]] : index
@@ -353,7 +353,7 @@ func.func @sumred(%arga: tensor<?x?x?xi32, #SparseTensor>,
// CHECK: %[[VAL_50:.*]] = arith.cmpi eq, %[[VAL_46]], %[[VAL_49]] : index
// CHECK: %[[VAL_51:.*]] = arith.cmpi eq, %[[VAL_47]], %[[VAL_49]] : index
// CHECK: %[[VAL_52:.*]] = arith.andi %[[VAL_50]], %[[VAL_51]] : i1
-// CHECK: %[[VAL_53:.*]]:2 = scf.if %[[VAL_52]] -> (index, tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_53:.*]]:2 = scf.if %[[VAL_52]] -> (index, tensor<?x?xf32, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_54:.*]] = memref.load %[[VAL_13]]{{\[}}%[[VAL_42]]] : memref<?xf32>
// CHECK: %[[VAL_55:.*]] = memref.load %[[VAL_16]]{{\[}}%[[VAL_43]]] : memref<?xindex>
// CHECK: %[[VAL_56:.*]] = arith.addi %[[VAL_43]], %[[VAL_3]] : index
@@ -377,9 +377,9 @@ func.func @sumred(%arga: tensor<?x?x?xi32, #SparseTensor>,
// CHECK: memref.store %[[VAL_65]], %[[VAL_25]]{{\[}}%[[VAL_61]]] : memref<?xf32>
// CHECK: scf.yield %[[VAL_70:.*]] : index
// CHECK: }
-// CHECK: scf.yield %[[VAL_71:.*]], %[[VAL_45]] : index, tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_71:.*]], %[[VAL_45]] : index, tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: } else {
-// CHECK: scf.yield %[[VAL_44]], %[[VAL_45]] : index, tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_44]], %[[VAL_45]] : index, tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: }
// CHECK: %[[VAL_72:.*]] = arith.cmpi eq, %[[VAL_46]], %[[VAL_49]] : index
// CHECK: %[[VAL_73:.*]] = arith.addi %[[VAL_42]], %[[VAL_3]] : index
@@ -387,13 +387,13 @@ func.func @sumred(%arga: tensor<?x?x?xi32, #SparseTensor>,
// CHECK: %[[VAL_75:.*]] = arith.cmpi eq, %[[VAL_47]], %[[VAL_49]] : index
// CHECK: %[[VAL_76:.*]] = arith.addi %[[VAL_43]], %[[VAL_3]] : index
// CHECK: %[[VAL_77:.*]] = arith.select %[[VAL_75]], %[[VAL_76]], %[[VAL_43]] : index
-// CHECK: scf.yield %[[VAL_74]], %[[VAL_77]], %[[VAL_78:.*]]#0, %[[VAL_78]]#1 : index, index, index, tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_74]], %[[VAL_77]], %[[VAL_78:.*]]#0, %[[VAL_78]]#1 : index, index, index, tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: %[[VAL_79:.*]] = sparse_tensor.compress %[[VAL_25]], %[[VAL_26]], %[[VAL_27]], %[[VAL_80:.*]]#2 into %[[VAL_80]]#3{{\[}}%[[VAL_24]]] : memref<?xf32>, memref<?xi1>, memref<?xindex>, tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: scf.yield %[[VAL_79]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_79:.*]] = sparse_tensor.compress %[[VAL_25]], %[[VAL_26]], %[[VAL_27]], %[[VAL_80:.*]]#2 into %[[VAL_80]]#3{{\[}}%[[VAL_24]]] : memref<?xf32>, memref<?xi1>, memref<?xindex>, tensor<?x?xf32, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_79]] : tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: %[[VAL_81:.*]] = sparse_tensor.load %[[VAL_82:.*]] hasInserts : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_81]] : tensor<?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_81:.*]] = sparse_tensor.load %[[VAL_82:.*]] hasInserts : tensor<?x?xf32, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_81]] : tensor<?x?xf32, #sparse{{[0-9]*}}>
// CHECK: }
func.func @matmat(%arga: tensor<?x?xf32, #DCSR>,
%argb: tensor<?x?xf32, #DCSR>) -> tensor<?x?xf32, #DCSR> {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_pack.mlir b/mlir/test/Dialect/SparseTensor/sparse_pack.mlir
index 80cfa3c635f3613..7cb699092f88335 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_pack.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_pack.mlir
@@ -40,7 +40,7 @@ func.func @sparse_pack(%values: tensor<6xf64>, %pos:tensor<2xindex>, %coordinate
// CHECK-SAME: %[[VAL_0:.*]]: memref<?xindex>,
// CHECK-SAME: %[[VAL_1:.*]]: memref<?xi32>,
// CHECK-SAME: %[[VAL_2:.*]]: memref<?xf64>,
-// CHECK-SAME: %[[VAL_3:.*]]: !sparse_tensor.storage_specifier<#sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_3:.*]]: !sparse_tensor.storage_specifier<#sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_4:.*]]: tensor<6xf64>,
// CHECK-SAME: %[[VAL_5:.*]]: tensor<2xindex>,
// CHECK-SAME: %[[VAL_6:.*]]: tensor<6x2xi32>) -> (tensor<6xf64>, tensor<2xindex>, tensor<6x2xi32>) {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_parallel_reduce.mlir b/mlir/test/Dialect/SparseTensor/sparse_parallel_reduce.mlir
index 8118eeceb6a62ee..7a35e0ff0c3a977 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_parallel_reduce.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_parallel_reduce.mlir
@@ -15,7 +15,7 @@
doc = "x(i) += A(i,j) * b(j)"
}
// CHECK-LABEL: func.func @matvec(
-// CHECK-SAME: %[[TMP_arg0:.*]]: tensor<16x32xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[TMP_arg0:.*]]: tensor<16x32xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[TMP_arg1:.*]]: tensor<32xf32>,
// CHECK-SAME: %[[TMP_arg2:.*]]: tensor<16xf32>) -> tensor<16xf32> {
// CHECK-DAG: %[[TMP_c16:.*]] = arith.constant 16 : index
diff --git a/mlir/test/Dialect/SparseTensor/sparse_perm.mlir b/mlir/test/Dialect/SparseTensor/sparse_perm.mlir
index 83cbfa771f1d626..e1e474ebee5fac1 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_perm.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_perm.mlir
@@ -14,7 +14,7 @@
}
// CHECK-LABEL: func @sparse_static_dims(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20x30xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20x30xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<20x30x10xf32>) -> tensor<20x30x10xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 20 : index
@@ -23,7 +23,7 @@
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
// CHECK: %[[DEMAP:.*]] = sparse_tensor.reinterpret_map %[[VAL_0]]
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[DEMAP]] : tensor<30x10x20xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.values %[[DEMAP]] : tensor<30x10x20xf32, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<20x30x10xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_9]] : memref<20x30x10xf32>)
// CHECK: scf.for %[[VAL_10:.*]] = %[[VAL_5]] to %[[VAL_3]] step %[[VAL_6]] {
@@ -53,17 +53,17 @@ func.func @sparse_static_dims(%arga: tensor<10x20x30xf32, #X>,
}
// CHECK-LABEL: func @sparse_dynamic_dims(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?x?xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {
// CHECK-DAG: %[[ZERO:.*]] = arith.constant 0.000000e+00 : f32
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 2 : index
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index
// CHECK: %[[DEMAP:.*]] = sparse_tensor.reinterpret_map %[[VAL_0]]
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.values %[[DEMAP]] : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.lvl %[[DEMAP]], %[[VAL_2]] : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.lvl %[[DEMAP]], %[[VAL_3]] : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.lvl %[[DEMAP]], %[[VAL_4]] : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.values %[[DEMAP]] : tensor<?x?x?xf32, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.lvl %[[DEMAP]], %[[VAL_2]] : tensor<?x?x?xf32, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.lvl %[[DEMAP]], %[[VAL_3]] : tensor<?x?x?xf32, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.lvl %[[DEMAP]], %[[VAL_4]] : tensor<?x?x?xf32, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<?x?x?xf32>
// CHECK: linalg.fill ins(%[[ZERO]] : f32) outs(%[[VAL_10]] : memref<?x?x?xf32>)
// CHECK: scf.for %[[VAL_11:.*]] = %[[VAL_3]] to %[[VAL_7]] step %[[VAL_4]] {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_perm_lower.mlir b/mlir/test/Dialect/SparseTensor/sparse_perm_lower.mlir
index 1078e5c282df11a..3ec2c89af420046 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_perm_lower.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_perm_lower.mlir
@@ -16,16 +16,16 @@
}
// CHECK-HIR-LABEL: func @sparse_dynamic_dims(
-// CHECK-HIR-SAME: %[[VAL_0:.*]]: tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-HIR-SAME: %[[VAL_0:.*]]: tensor<?x?x?xf32, #sparse{{[0-9]*}}>,
// CHECK-HIR-SAME: %[[VAL_1:.*]]: tensor<f32>) -> tensor<f32> {
// CHECK-HIR-DAG: %[[VAL_2:.*]] = arith.constant 1 : index
// CHECK-HIR-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-HIR-DAG: %[[VAL_4:.*]] = arith.constant 2 : index
// CHECK-HIR: %[[DEMAP:. *]] = sparse_tensor.reinterpret_map %[[VAL_0]]
-// CHECK-HIR-DAG: %[[VAL_5:.*]] = sparse_tensor.lvl %[[DEMAP]], %[[VAL_3]] : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-HIR-DAG: %[[VAL_6:.*]] = sparse_tensor.lvl %[[DEMAP]], %[[VAL_2]] : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-HIR-DAG: %[[VAL_7:.*]] = sparse_tensor.lvl %[[DEMAP]], %[[VAL_4]] : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-HIR-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[DEMAP]] : tensor<?x?x?xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-HIR-DAG: %[[VAL_5:.*]] = sparse_tensor.lvl %[[DEMAP]], %[[VAL_3]] : tensor<?x?x?xf32, #sparse{{[0-9]*}}>
+// CHECK-HIR-DAG: %[[VAL_6:.*]] = sparse_tensor.lvl %[[DEMAP]], %[[VAL_2]] : tensor<?x?x?xf32, #sparse{{[0-9]*}}>
+// CHECK-HIR-DAG: %[[VAL_7:.*]] = sparse_tensor.lvl %[[DEMAP]], %[[VAL_4]] : tensor<?x?x?xf32, #sparse{{[0-9]*}}>
+// CHECK-HIR-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[DEMAP]] : tensor<?x?x?xf32, #sparse{{[0-9]*}}>
// CHECK-HIR-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_1]] : memref<f32>
// CHECK-HIR: %[[VAL_11:.*]] = tensor.extract %[[VAL_1]][] : tensor<f32>
// CHECK-HIR: %[[VAL_12:.*]] = scf.for %[[VAL_13:.*]] = %[[VAL_3]] to %[[VAL_5]] step %[[VAL_2]] iter_args(%[[VAL_14:.*]] = %[[VAL_11]]) -> (f32) {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_reinterpret_map.mlir b/mlir/test/Dialect/SparseTensor/sparse_reinterpret_map.mlir
index c4931c62c62633e..c6a3a366af9f379 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_reinterpret_map.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_reinterpret_map.mlir
@@ -25,11 +25,11 @@
// CHECK-LABEL: func @mul(
// CHECK-SAME: %[[A0:.*0]]: tensor<32x32xf32>,
// CHECK-SAME: %[[A1:.*1]]: tensor<32x32xf32>,
-// CHECK-SAME: %[[A2:.*2]]: tensor<32x32xf32, #sparse_tensor.encoding<{{{.*}}}>>)
+// CHECK-SAME: %[[A2:.*2]]: tensor<32x32xf32, #sparse{{[0-9]*}}>)
// CHECK: %[[T0:.*]] = sparse_tensor.reinterpret_map %[[A2]]
// CHECK: %[[T1:.*]] = linalg.generic {doc = {{.*}} indexing_maps = [#[[$map0]], #[[$map1]], #[[$map2]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]}
// CHECK: %[[T2:.*]] = sparse_tensor.reinterpret_map %[[T1]]
-// CHECK: return %[[T2]] : tensor<32x32xf32, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: return %[[T2]] : tensor<32x32xf32, #sparse{{[0-9]*}}>
func.func @mul(%arg0: tensor<32x32xf32>,
%arg1: tensor<32x32xf32>,
%arg2: tensor<32x32xf32, #BSR>) -> tensor<32x32xf32, #BSR> {
@@ -56,17 +56,17 @@ func.func @mul(%arg0: tensor<32x32xf32>,
}>
// CHECK-LABEL: func.func @sparse_foreach_reinterpret_map(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<2x4xf64
-// CHECK: %[[VAL_1:.*]] = bufferization.alloc_tensor() : tensor<1x2x2x2xf64
-// CHECK: %[[VAL_2:.*]] = sparse_tensor.reinterpret_map %[[VAL_0]] : tensor<2x4xf64
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<2x4xf64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_1:.*]] = bufferization.alloc_tensor() : tensor<1x2x2x2xf64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_2:.*]] = sparse_tensor.reinterpret_map %[[VAL_0]] : tensor<2x4xf64, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_4:.*]] = sparse_tensor.foreach in %[[VAL_2]] init(%[[VAL_1]])
-// CHECK: ^bb0(%[[VAL_5:.*]]: index, %[[VAL_6:.*]]: index, %[[VAL_7:.*]]: index, %[[VAL_8:.*]]: index, %[[VAL_9:.*]]: f64, %[[VAL_10:.*]]: tensor<1x2x2x2xf64
-// CHECK: %[[VAL_11:.*]] = sparse_tensor.insert %[[VAL_9]] into %[[VAL_10]]{{\[}}%[[VAL_5]], %[[VAL_6]], %[[VAL_7]], %[[VAL_8]]] : tensor<1x2x2x2xf64
-// CHECK: sparse_tensor.yield %[[VAL_11]] : tensor<1x2x2x2xf64
+// CHECK: ^bb0(%[[VAL_5:.*]]: index, %[[VAL_6:.*]]: index, %[[VAL_7:.*]]: index, %[[VAL_8:.*]]: index, %[[VAL_9:.*]]: f64, %[[VAL_10:.*]]: tensor<1x2x2x2xf64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_11:.*]] = sparse_tensor.insert %[[VAL_9]] into %[[VAL_10]]{{\[}}%[[VAL_5]], %[[VAL_6]], %[[VAL_7]], %[[VAL_8]]] : tensor<1x2x2x2xf64, #sparse{{[0-9]*}}>
+// CHECK: sparse_tensor.yield %[[VAL_11]] : tensor<1x2x2x2xf64, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: %[[VAL_12:.*]] = sparse_tensor.reinterpret_map %[[VAL_4]] : tensor<1x2x2x2xf64
-// CHECK: %[[VAL_13:.*]] = sparse_tensor.load %[[VAL_12]] hasInserts : tensor<2x4xf64
-// CHECK: return %[[VAL_13]] : tensor<2x4xf64
+// CHECK: %[[VAL_12:.*]] = sparse_tensor.reinterpret_map %[[VAL_4]] : tensor<1x2x2x2xf64, #sparse{{[0-9]*}}>
+// CHECK: %[[VAL_13:.*]] = sparse_tensor.load %[[VAL_12]] hasInserts : tensor<2x4xf64, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_13]] : tensor<2x4xf64, #sparse{{[0-9]*}}>
// CHECK: }
func.func @sparse_foreach_reinterpret_map(%6 : tensor<2x4xf64, #BSR>) -> tensor<2x4xf64, #BSR> {
%7 = bufferization.alloc_tensor() : tensor<2x4xf64, #BSR>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_reshape.mlir b/mlir/test/Dialect/SparseTensor/sparse_reshape.mlir
index d3d6d8c91fa45a1..eea77c6e5a6cc6b 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_reshape.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_reshape.mlir
@@ -11,9 +11,9 @@
// roundtrip:
//
// CHECK-ROUND-LABEL: func.func @sparse_expand(
-// CHECK-ROUND-SAME: %[[A:.*]]: tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-ROUND: %[[E:.*]] = tensor.expand_shape %[[A]] {{\[\[}}0, 1]] : tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>> into tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-ROUND: return %[[E]] : tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-ROUND-SAME: %[[A:.*]]: tensor<100xf64, #sparse{{[0-9]*}}>) -> tensor<10x10xf64, #sparse{{[0-9]*}}>
+// CHECK-ROUND: %[[E:.*]] = tensor.expand_shape %[[A]] {{\[\[}}0, 1]] : tensor<100xf64, #sparse{{[0-9]*}}> into tensor<10x10xf64, #sparse{{[0-9]*}}>
+// CHECK-ROUND: return %[[E]] : tensor<10x10xf64, #sparse{{[0-9]*}}>
//
// CHECK-LABEL: func.func @sparse_expand(
// CHECK-SAME: %[[S:.*0]]:
@@ -36,7 +36,7 @@
// CHECK: }
// CHECK: %[[NT1:.*]] = sparse_tensor.load %[[RET]] hasInserts
// CHECK-NOT: sparse_tensor.convert
-// CHECK: return %[[NT1]] : tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: return %[[NT1]] : tensor<10x10xf64, #sparse{{[0-9]*}}>
//
func.func @sparse_expand(%arg0: tensor<100xf64, #SparseVector>) -> tensor<10x10xf64, #SparseMatrix> {
%0 = tensor.expand_shape %arg0 [[0, 1]] :
@@ -48,9 +48,9 @@ func.func @sparse_expand(%arg0: tensor<100xf64, #SparseVector>) -> tensor<10x10x
// roundtrip:
//
// CHECK-ROUND-LABEL: func.func @sparse_collapse(
-// CHECK-ROUND-SAME: %[[A:.*]]: tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-ROUND: %[[C:.*]] = tensor.collapse_shape %[[A]] {{\[\[}}0, 1]] : tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>> into tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-ROUND: return %[[C]] : tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-ROUND-SAME: %[[A:.*]]: tensor<10x10xf64, #sparse{{[0-9]*}}>) -> tensor<100xf64, #sparse{{[0-9]*}}>
+// CHECK-ROUND: %[[C:.*]] = tensor.collapse_shape %[[A]] {{\[\[}}0, 1]] : tensor<10x10xf64, #sparse{{[0-9]*}}> into tensor<100xf64, #sparse{{[0-9]*}}>
+// CHECK-ROUND: return %[[C]] : tensor<100xf64, #sparse{{[0-9]*}}>
//
// CHECK-LABEL: func.func @sparse_collapse(
// CHECK-SAME: %[[S:.*0]]:
@@ -82,7 +82,7 @@ func.func @sparse_expand(%arg0: tensor<100xf64, #SparseVector>) -> tensor<10x10x
// CHECK: }
// CHECK: %[[NT1:.*]] = sparse_tensor.load %[[RET]] hasInserts
// CHECK-NOT: sparse_tensor.convert
-// CHECK: return %[[NT1]] : tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: return %[[NT1]] : tensor<100xf64, #sparse{{[0-9]*}}>
//
func.func @sparse_collapse(%arg0: tensor<10x10xf64, #SparseMatrix>) -> tensor<100xf64, #SparseVector> {
%0 = tensor.collapse_shape %arg0 [[0, 1]] :
@@ -94,9 +94,9 @@ func.func @sparse_collapse(%arg0: tensor<10x10xf64, #SparseMatrix>) -> tensor<10
// roundtrip:
//
// CHECK-ROUND-LABEL: func.func @dynamic_sparse_expand(
-// CHECK-ROUND-SAME: %[[A:.*]]: tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<?x10xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-ROUND: %[[E:.*]] = tensor.expand_shape %[[A]] {{\[\[}}0, 1]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>> into tensor<?x10xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-ROUND: return %[[E]] : tensor<?x10xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-ROUND-SAME: %[[A:.*]]: tensor<?xf64, #sparse{{[0-9]*}}>) -> tensor<?x10xf64, #sparse{{[0-9]*}}>
+// CHECK-ROUND: %[[E:.*]] = tensor.expand_shape %[[A]] {{\[\[}}0, 1]] : tensor<?xf64, #sparse{{[0-9]*}}> into tensor<?x10xf64, #sparse{{[0-9]*}}>
+// CHECK-ROUND: return %[[E]] : tensor<?x10xf64, #sparse{{[0-9]*}}>
//
// CHECK-LABEL: func.func @dynamic_sparse_expand(
// CHECK-SAME: %[[S:.*0]]:
@@ -125,7 +125,7 @@ func.func @sparse_collapse(%arg0: tensor<10x10xf64, #SparseMatrix>) -> tensor<10
// CHECK: }
// CHECK: %[[NT1:.*]] = sparse_tensor.load %[[RET]] hasInserts
// CHECK-NOT: sparse_tensor.convert
-// CHECK: return %[[NT1]] : tensor<?x10xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: return %[[NT1]] : tensor<?x10xf64, #sparse{{[0-9]*}}>
//
func.func @dynamic_sparse_expand(%arg0: tensor<?xf64, #SparseVector>) -> tensor<?x10xf64, #SparseMatrix> {
%0 = tensor.expand_shape %arg0 [[0, 1]] :
@@ -137,9 +137,9 @@ func.func @dynamic_sparse_expand(%arg0: tensor<?xf64, #SparseVector>) -> tensor<
// roundtrip:
//
// CHECK-ROUND-LABEL: func.func @dynamic_sparse_collapse(
-// CHECK-ROUND-SAME: %[[A:.*]]: tensor<10x?xf64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-ROUND: %[[C:.*]] = tensor.collapse_shape %[[A]] {{\[\[}}0, 1]] : tensor<10x?xf64, #sparse_tensor.encoding<{{{.*}}}>> into tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-ROUND: return %[[C]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-ROUND-SAME: %[[A:.*]]: tensor<10x?xf64, #sparse{{[0-9]*}}>) -> tensor<?xf64, #sparse{{[0-9]*}}>
+// CHECK-ROUND: %[[C:.*]] = tensor.collapse_shape %[[A]] {{\[\[}}0, 1]] : tensor<10x?xf64, #sparse{{[0-9]*}}> into tensor<?xf64, #sparse{{[0-9]*}}>
+// CHECK-ROUND: return %[[C]] : tensor<?xf64, #sparse{{[0-9]*}}>
//
// CHECK-LABEL: func.func @dynamic_sparse_collapse(
// CHECK-SAME: %[[S:.*0]]:
@@ -176,7 +176,7 @@ func.func @dynamic_sparse_expand(%arg0: tensor<?xf64, #SparseVector>) -> tensor<
// CHECK: }
// CHECK: %[[NT1:.*]] = sparse_tensor.load %[[RET]] hasInserts
// CHECK-NOT: sparse_tensor.convert
-// CHECK: return %[[NT1]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: return %[[NT1]] : tensor<?xf64, #sparse{{[0-9]*}}>
//
func.func @dynamic_sparse_collapse(%arg0: tensor<10x?xf64, #SparseMatrix>) -> tensor<?xf64, #SparseVector> {
%0 = tensor.collapse_shape %arg0 [[0, 1]] :
diff --git a/mlir/test/Dialect/SparseTensor/sparse_scalars.mlir b/mlir/test/Dialect/SparseTensor/sparse_scalars.mlir
index 4ca577b9f729031..666882edcbab383 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_scalars.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_scalars.mlir
@@ -19,7 +19,7 @@
}
// CHECK-LABEL: func @mul(
-// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>>,
+// CHECK-SAME: %[[VAL_0:.*0]]: tensor<32x16xf32, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*1]]: tensor<f32>,
// CHECK-SAME: %[[VAL_2:.*2]]: f32,
// CHECK-SAME: %[[VAL_3:.*3]]: f32,
@@ -28,11 +28,11 @@
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_8:.*]] = arith.addf %[[VAL_2]], %[[VAL_3]] : f32
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xf32>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-DAG: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_1]] : memref<f32>
// CHECK-DAG: %[[VAL_15:.*]] = bufferization.to_memref %[[VAL_4]] : memref<32x16xf32>
// CHECK-DAG: %[[VAL_16:.*]] = memref.load %[[VAL_14]][] : memref<f32>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_sddmm.mlir b/mlir/test/Dialect/SparseTensor/sparse_sddmm.mlir
index 1d95fe8d0569a23..6fc2db481c6fd4d 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_sddmm.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_sddmm.mlir
@@ -55,7 +55,7 @@ func.func @fold_yield_direct_zero() -> tensor<32xf64> {
}
// CHECK-LABEL: func.func @sampled_dd_unfused(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<8x8xf64>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<8x8xf64>) -> tensor<8x8xf64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 8 : index
@@ -66,11 +66,11 @@ func.func @fold_yield_direct_zero() -> tensor<32xf64> {
// CHECK-DAG: %[[VAL_8:.*]] = bufferization.alloc_tensor() copy(%[[VAL_6]]) {memory_space = 0 : i64} : tensor<8x8xf64>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<8x8xf64>
// CHECK-DAG: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]] : memref<8x8xf64>
-// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xf64, #sparse_tensor.encoding<{{.*}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_16:.*]] = bufferization.to_memref %[[VAL_8]] : memref<8x8xf64>
// CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_4]]] : memref<?xindex>
// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_5]]] : memref<?xindex>
@@ -121,9 +121,9 @@ func.func @sampled_dd_unfused(%args: tensor<8x8xf64, #SM>,
}
// CHECK-LABEL: func.func @sparse_sampled_dd_unfused(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<8x8xf64>,
-// CHECK-SAME: %[[VAL_2:.*]]: tensor<8x8xf64>) -> tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_2:.*]]: tensor<8x8xf64>) -> tensor<8x8xf64, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
@@ -131,19 +131,19 @@ func.func @sampled_dd_unfused(%args: tensor<8x8xf64, #SM>,
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant dense<0.000000e+00> : tensor<8x8xf64>
// CHECK-DAG: %[[VAL_9:.*]] = bufferization.alloc_tensor() copy(%[[VAL_8]]) : tensor<8x8xf64>
-// CHECK-DAG: %[[VAL_10:.*]] = tensor.empty() : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK-DAG: %[[VAL_10:.*]] = tensor.empty() : tensor<8x8xf64, #sparse{{[0-9]*}}>
// CHECK-DAG: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_1]] : memref<8x8xf64>
// CHECK-DAG: %[[VAL_12:.*]] = bufferization.to_memref %[[VAL_2]] : memref<8x8xf64>
-// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_17:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_13:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_14:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_15:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_16:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_17:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_13]]{{\[}}%[[VAL_4]]] : memref<?xindex>
// CHECK: %[[VAL_19:.*]] = memref.load %[[VAL_13]]{{\[}}%[[VAL_5]]] : memref<?xindex>
-// CHECK: %[[VAL_20:.*]] = scf.for %[[VAL_21:.*]] = %[[VAL_18]] to %[[VAL_19]] step %[[VAL_5]] iter_args(%[[VAL_22:.*]] = %[[VAL_10]]) -> (tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_20:.*]] = scf.for %[[VAL_21:.*]] = %[[VAL_18]] to %[[VAL_19]] step %[[VAL_5]] iter_args(%[[VAL_22:.*]] = %[[VAL_10]]) -> (tensor<8x8xf64, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_23:.*]] = memref.load %[[VAL_14]]{{\[}}%[[VAL_21]]] : memref<?xindex>
-// CHECK: %[[VAL_24:.*]], %[[VAL_25:.*]], %[[VAL_26:.*]], %[[VAL_27:.*]] = sparse_tensor.expand %[[VAL_10]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>, memref<?xi1>, memref<?xindex>
+// CHECK: %[[VAL_24:.*]], %[[VAL_25:.*]], %[[VAL_26:.*]], %[[VAL_27:.*]] = sparse_tensor.expand %[[VAL_10]] : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xf64>, memref<?xi1>, memref<?xindex>
// CHECK: %[[VAL_28:.*]] = scf.for %[[VAL_29:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] iter_args(%[[VAL_30:.*]] = %[[VAL_27]]) -> (index) {
// CHECK: %[[VAL_31:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_23]], %[[VAL_29]]] : memref<8x8xf64>
// CHECK: %[[VAL_32:.*]] = memref.load %[[VAL_15]]{{\[}}%[[VAL_21]]] : memref<?xindex>
@@ -172,11 +172,11 @@ func.func @sampled_dd_unfused(%args: tensor<8x8xf64, #SM>,
// CHECK: }
// CHECK: scf.yield %[[VAL_35]] : index
// CHECK: }
-// CHECK: %[[VAL_49:.*]] = sparse_tensor.compress %[[VAL_24]], %[[VAL_25]], %[[VAL_26]], %[[VAL_28]] into %[[VAL_22]]{{\[}}%[[VAL_23]]] : memref<?xf64>, memref<?xi1>, memref<?xindex>, tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: scf.yield %[[VAL_49]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_49:.*]] = sparse_tensor.compress %[[VAL_24]], %[[VAL_25]], %[[VAL_26]], %[[VAL_28]] into %[[VAL_22]]{{\[}}%[[VAL_23]]] : memref<?xf64>, memref<?xi1>, memref<?xindex>, tensor<8x8xf64, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_49]] : tensor<8x8xf64, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: %[[VAL_50:.*]] = sparse_tensor.load %[[VAL_20]] hasInserts : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_50]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_50:.*]] = sparse_tensor.load %[[VAL_20]] hasInserts : tensor<8x8xf64, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_50]] : tensor<8x8xf64, #sparse{{[0-9]*}}>
// CHECK: }
func.func @sparse_sampled_dd_unfused(%args: tensor<8x8xf64, #SM>,
%arga: tensor<8x8xf64>,
diff --git a/mlir/test/Dialect/SparseTensor/sparse_sddmm_org.mlir b/mlir/test/Dialect/SparseTensor/sparse_sddmm_org.mlir
index 79bedcf5a49e16c..5fa332f8f1819a4 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_sddmm_org.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_sddmm_org.mlir
@@ -21,27 +21,27 @@
}
// CHECK-LABEL: func.func @sparse_sampled_dd_unfused(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>,
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<8x8xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_1:.*]]: tensor<8x8xf64>,
-// CHECK-SAME: %[[VAL_2:.*]]: tensor<8x8xf64>) -> tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_2:.*]]: tensor<8x8xf64>) -> tensor<8x8xf64, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant false
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant true
-// CHECK: %[[VAL_8:.*]] = tensor.empty() : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_8:.*]] = tensor.empty() : tensor<8x8xf64, #sparse{{[0-9]*}}>
// CHECK: %[[VAL_9:.*]] = bufferization.to_memref %[[VAL_1]] : memref<8x8xf64>
// CHECK: %[[VAL_10:.*]] = bufferization.to_memref %[[VAL_2]] : memref<8x8xf64>
-// CHECK: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_13:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_14:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_15:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_13:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_14:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_15:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_4]]] : memref<?xindex>
// CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_5]]] : memref<?xindex>
-// CHECK: %[[VAL_18:.*]] = scf.for %[[VAL_19:.*]] = %[[VAL_16]] to %[[VAL_17]] step %[[VAL_5]] iter_args(%[[VAL_20:.*]] = %[[VAL_8]]) -> (tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_18:.*]] = scf.for %[[VAL_19:.*]] = %[[VAL_16]] to %[[VAL_17]] step %[[VAL_5]] iter_args(%[[VAL_20:.*]] = %[[VAL_8]]) -> (tensor<8x8xf64, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_21:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_19]]] : memref<?xindex>
-// CHECK: %[[VAL_22:.*]], %[[VAL_23:.*]], %[[VAL_24:.*]], %[[VAL_25:.*]] = sparse_tensor.expand %[[VAL_8]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>, memref<?xi1>, memref<?xindex>
+// CHECK: %[[VAL_22:.*]], %[[VAL_23:.*]], %[[VAL_24:.*]], %[[VAL_25:.*]] = sparse_tensor.expand %[[VAL_8]] : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xf64>, memref<?xi1>, memref<?xindex>
// CHECK: %[[VAL_26:.*]] = scf.for %[[VAL_27:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] iter_args(%[[VAL_28:.*]] = %[[VAL_25]]) -> (index) {
// CHECK: %[[VAL_29:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_21]], %[[VAL_27]]] : memref<8x8xf64>
// CHECK: %[[VAL_30:.*]] = memref.load %[[VAL_13]]{{\[}}%[[VAL_19]]] : memref<?xindex>
@@ -70,11 +70,11 @@
// CHECK: } {"Emitted from" = "linalg.generic"}
// CHECK: scf.yield %[[VAL_48:.*]] : index
// CHECK: } {"Emitted from" = "linalg.generic"}
-// CHECK: %[[VAL_49:.*]] = sparse_tensor.compress %[[VAL_22]], %[[VAL_23]], %[[VAL_24]], %[[VAL_50:.*]] into %[[VAL_20]]{{\[}}%[[VAL_21]]] : memref<?xf64>, memref<?xi1>, memref<?xindex>, tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: scf.yield %[[VAL_49]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_49:.*]] = sparse_tensor.compress %[[VAL_22]], %[[VAL_23]], %[[VAL_24]], %[[VAL_50:.*]] into %[[VAL_20]]{{\[}}%[[VAL_21]]] : memref<?xf64>, memref<?xi1>, memref<?xindex>, tensor<8x8xf64, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_49]] : tensor<8x8xf64, #sparse{{[0-9]*}}>
// CHECK: } {"Emitted from" = "linalg.generic"}
-// CHECK: %[[VAL_51:.*]] = sparse_tensor.load %[[VAL_52:.*]] hasInserts : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_51]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_51:.*]] = sparse_tensor.load %[[VAL_52:.*]] hasInserts : tensor<8x8xf64, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_51]] : tensor<8x8xf64, #sparse{{[0-9]*}}>
// CHECK: }
func.func @sparse_sampled_dd_unfused(%args: tensor<8x8xf64, #SM>,
%arga: tensor<8x8xf64>,
diff --git a/mlir/test/Dialect/SparseTensor/sparse_tensor_reshape.mlir b/mlir/test/Dialect/SparseTensor/sparse_tensor_reshape.mlir
index 339d65ce5716fab..47d24ebf24fc6af 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_tensor_reshape.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_tensor_reshape.mlir
@@ -35,7 +35,7 @@
// CHECK: scf.yield %[[RET_1]]
// CHECK: }
// CHECK: %[[NT1:.*]] = sparse_tensor.load %[[RET]] hasInserts
-// CHECK: return %[[NT1]] : tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: return %[[NT1]] : tensor<10x10xf64, #sparse{{[0-9]*}}>
//
func.func @sparse_reshape(%arg0: tensor<4x25xf64, #SparseMatrix>) -> tensor<10x10xf64, #SparseMatrix> {
%shape = arith.constant dense <[ 10, 10 ]> : tensor<2xi32>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_transpose.mlir b/mlir/test/Dialect/SparseTensor/sparse_transpose.mlir
index fd41fedf91c2cbb..80a989d789df21e 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_transpose.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_transpose.mlir
@@ -16,34 +16,34 @@
// TODO: improve auto-conversion followed by yield
// CHECK-LABEL: func.func @sparse_transpose_auto(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<3x4xf64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<3x4xf64, #sparse{{[0-9]*}}>) -> tensor<4x3xf64, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[VAL_3:.*]] = tensor.empty() : tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.convert %[[VAL_0]] : tensor<3x4xf64, #sparse_tensor.encoding<{{{.*}}}>> to tensor<3x4xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: %[[DEMAP:.*]] = sparse_tensor.reinterpret_map %[[VAL_4]] : tensor<3x4xf64, #sparse_tensor.encoding<{{{.*}}}>> to tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[DEMAP]] {level = 0 : index} : tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[DEMAP]] {level = 0 : index} : tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[DEMAP]] {level = 1 : index} : tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[DEMAP]] {level = 1 : index} : tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[DEMAP]] : tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_3:.*]] = tensor.empty() : tensor<4x3xf64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_4:.*]] = sparse_tensor.convert %[[VAL_0]] : tensor<3x4xf64, #sparse{{[0-9]*}}> to tensor<3x4xf64, #sparse{{[0-9]*}}>
+// CHECK: %[[DEMAP:.*]] = sparse_tensor.reinterpret_map %[[VAL_4]] : tensor<3x4xf64, #sparse{{[0-9]*}}> to tensor<4x3xf64, #sparse{{[0-9]*}}>
+// CHECK-DAG: %[[VAL_5:.*]] = sparse_tensor.positions %[[DEMAP]] {level = 0 : index} : tensor<4x3xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_6:.*]] = sparse_tensor.coordinates %[[DEMAP]] {level = 0 : index} : tensor<4x3xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_7:.*]] = sparse_tensor.positions %[[DEMAP]] {level = 1 : index} : tensor<4x3xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.coordinates %[[DEMAP]] {level = 1 : index} : tensor<4x3xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.values %[[DEMAP]] : tensor<4x3xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_1]]] : memref<?xindex>
// CHECK: %[[VAL_11:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_2]]] : memref<?xindex>
-// CHECK: %[[VAL_12:.*]] = scf.for %[[VAL_13:.*]] = %[[VAL_10]] to %[[VAL_11]] step %[[VAL_2]] iter_args(%[[VAL_14:.*]] = %[[VAL_3]]) -> (tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_12:.*]] = scf.for %[[VAL_13:.*]] = %[[VAL_10]] to %[[VAL_11]] step %[[VAL_2]] iter_args(%[[VAL_14:.*]] = %[[VAL_3]]) -> (tensor<4x3xf64, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_13]]] : memref<?xindex>
// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_13]]] : memref<?xindex>
// CHECK: %[[VAL_17:.*]] = arith.addi %[[VAL_13]], %[[VAL_2]] : index
// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_17]]] : memref<?xindex>
-// CHECK: %[[VAL_19:.*]] = scf.for %[[VAL_20:.*]] = %[[VAL_16]] to %[[VAL_18]] step %[[VAL_2]] iter_args(%[[VAL_21:.*]] = %[[VAL_14]]) -> (tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>>) {
+// CHECK: %[[VAL_19:.*]] = scf.for %[[VAL_20:.*]] = %[[VAL_16]] to %[[VAL_18]] step %[[VAL_2]] iter_args(%[[VAL_21:.*]] = %[[VAL_14]]) -> (tensor<4x3xf64, #sparse{{[0-9]*}}>) {
// CHECK: %[[VAL_22:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_20]]] : memref<?xindex>
// CHECK: %[[VAL_23:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_20]]] : memref<?xf64>
-// CHECK: %[[VAL_24:.*]] = sparse_tensor.insert %[[VAL_23]] into %[[VAL_21]]{{\[}}%[[VAL_15]], %[[VAL_22]]] : tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: scf.yield %[[VAL_24]] : tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_24:.*]] = sparse_tensor.insert %[[VAL_23]] into %[[VAL_21]]{{\[}}%[[VAL_15]], %[[VAL_22]]] : tensor<4x3xf64, #sparse{{[0-9]*}}>
+// CHECK: scf.yield %[[VAL_24]] : tensor<4x3xf64, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: scf.yield %[[VAL_25:.*]] : tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: scf.yield %[[VAL_25:.*]] : tensor<4x3xf64, #sparse{{[0-9]*}}>
// CHECK: }
-// CHECK: %[[VAL_26:.*]] = sparse_tensor.load %[[VAL_27:.*]] hasInserts : tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_26]] : tensor<4x3xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_26:.*]] = sparse_tensor.load %[[VAL_27:.*]] hasInserts : tensor<4x3xf64, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_26]] : tensor<4x3xf64, #sparse{{[0-9]*}}>
// CHECK: }
func.func @sparse_transpose_auto(%arga: tensor<3x4xf64, #DCSR>)
-> tensor<4x3xf64, #DCSR> {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_vector_chain.mlir b/mlir/test/Dialect/SparseTensor/sparse_vector_chain.mlir
index 269a4926c9ec375..e3508f11cb758c9 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_vector_chain.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_vector_chain.mlir
@@ -18,19 +18,19 @@
//
// CHECK-LABEL: func.func @sparse_matrix_sum(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<f64>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<64x32xf64, #sparse_tensor.encoding<{{{.*}}}>>,
-// CHECK-SAME: %[[VAL_2:.*]]: tensor<64x32xf64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<f64> {
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<64x32xf64, #sparse{{[0-9]*}}>,
+// CHECK-SAME: %[[VAL_2:.*]]: tensor<64x32xf64, #sparse{{[0-9]*}}>) -> tensor<f64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant dense<0.000000e+00> : vector<8xf64>
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 64 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_7:.*]] = arith.constant 1 : index
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<64x32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<64x32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<64x32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
-// CHECK: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 1 : index} : tensor<64x32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 1 : index} : tensor<64x32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<64x32xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 1 : index} : tensor<64x32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_1]] {level = 1 : index} : tensor<64x32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<64x32xf64, #sparse{{[0-9]*}}> to memref<?xf64>
+// CHECK: %[[VAL_11:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 1 : index} : tensor<64x32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_12:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 1 : index} : tensor<64x32xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_13:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<64x32xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: %[[VAL_14:.*]] = bufferization.to_memref %[[VAL_0]] : memref<f64>
// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_14]][] : memref<f64>
// CHECK: %[[VAL_16:.*]] = scf.for %[[VAL_17:.*]] = %[[VAL_6]] to %[[VAL_5]] step %[[VAL_7]] iter_args(%[[VAL_18:.*]] = %[[VAL_15]]) -> (f64) {
diff --git a/mlir/test/Dialect/SparseTensor/sparse_vector_index.mlir b/mlir/test/Dialect/SparseTensor/sparse_vector_index.mlir
index 9bc24fd02b827d0..c9d432924c0db08 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_vector_index.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_vector_index.mlir
@@ -17,7 +17,7 @@
}
// CHECK-LABEL: func.func @sparse_index_1d_conj(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<8xi64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<8xi64> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<8xi64, #sparse{{[0-9]*}}>) -> tensor<8xi64> {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant dense<0> : vector<8xi64>
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant dense<0> : vector<8xindex>
@@ -25,9 +25,9 @@
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_7:.*]] = tensor.empty() : tensor<8xi64>
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<8xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<8xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi64>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<8xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<8xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8xi64, #sparse{{[0-9]*}}> to memref<?xi64>
// CHECK: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_7]] : memref<8xi64>
// CHECK: linalg.fill ins(%[[VAL_4]] : i64) outs(%[[VAL_11]] : memref<8xi64>)
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_5]]] : memref<?xindex>
@@ -59,7 +59,7 @@ func.func @sparse_index_1d_conj(%arga: tensor<8xi64, #SparseVector>) -> tensor<8
}
// CHECK-LABEL: func.func @sparse_index_1d_disj(
-// CHECK-SAME: %[[VAL_0:.*]]: tensor<8xi64, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<8xi64> {
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<8xi64, #sparse{{[0-9]*}}>) -> tensor<8xi64> {
// CHECK-DAG: %[[VAL_1:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_2:.*]] = arith.constant dense<[0, 1, 2, 3, 4, 5, 6, 7]> : vector<8xindex>
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 0 : i64
@@ -67,9 +67,9 @@ func.func @sparse_index_1d_conj(%arga: tensor<8xi64, #SparseVector>) -> tensor<8
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_6:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_7:.*]] = tensor.empty() : tensor<8xi64>
-// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<8xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<8xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8xi64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi64>
+// CHECK: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_0]] {level = 0 : index} : tensor<8xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_0]] {level = 0 : index} : tensor<8xi64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<8xi64, #sparse{{[0-9]*}}> to memref<?xi64>
// CHECK: %[[VAL_11:.*]] = bufferization.to_memref %[[VAL_7]] : memref<8xi64>
// CHECK: linalg.fill ins(%[[VAL_3]] : i64) outs(%[[VAL_11]] : memref<8xi64>)
// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_4]]] : memref<?xindex>
diff --git a/mlir/test/Dialect/SparseTensor/spy_sddmm.mlir b/mlir/test/Dialect/SparseTensor/spy_sddmm.mlir
index a4211991f260833..287b62ef44c65fb 100644
--- a/mlir/test/Dialect/SparseTensor/spy_sddmm.mlir
+++ b/mlir/test/Dialect/SparseTensor/spy_sddmm.mlir
@@ -20,15 +20,15 @@
// CHECK-LABEL: func.func @sparse_sampled_dd(
// CHECK-SAME: %[[VAL_0:.*0]]: tensor<8x8xf64>,
// CHECK-SAME: %[[VAL_1:.*1]]: tensor<8x8xf64>,
-// CHECK-SAME: %[[VAL_2:.*2]]: tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> {
+// CHECK-SAME: %[[VAL_2:.*2]]: tensor<8x8xf64, #sparse{{[0-9]*}}>) -> tensor<8x8xf64, #sparse{{[0-9]*}}> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_0]] : memref<8x8xf64>
// CHECK-DAG: %[[VAL_7:.*]] = bufferization.to_memref %[[VAL_1]] : memref<8x8xf64>
-// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 1 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 1 : index} : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf64>
+// CHECK-DAG: %[[VAL_8:.*]] = sparse_tensor.positions %[[VAL_2]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_9:.*]] = sparse_tensor.coordinates %[[VAL_2]] {level = 1 : index} : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-DAG: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_2]] : tensor<8x8xf64, #sparse{{[0-9]*}}> to memref<?xf64>
// CHECK: scf.for %[[VAL_11:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
// CHECK: scf.for %[[VAL_12:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {
// CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_11]]] : memref<?xindex>
@@ -45,8 +45,8 @@
// CHECK: } {"Emitted from" = "linalg.generic"}
// CHECK: } {"Emitted from" = "linalg.generic"}
// CHECK: } {"Emitted from" = "linalg.generic"}
-// CHECK: %[[VAL_23:.*]] = sparse_tensor.load %[[VAL_2]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
-// CHECK: return %[[VAL_23]] : tensor<8x8xf64, #sparse_tensor.encoding<{{{.*}}}>>
+// CHECK: %[[VAL_23:.*]] = sparse_tensor.load %[[VAL_2]] : tensor<8x8xf64, #sparse{{[0-9]*}}>
+// CHECK: return %[[VAL_23]] : tensor<8x8xf64, #sparse{{[0-9]*}}>
// CHECK: }
func.func @sparse_sampled_dd(%argA: tensor<8x8xf64>,
%argB: tensor<8x8xf64>,
diff --git a/mlir/test/Dialect/SparseTensor/unused-tensor.mlir b/mlir/test/Dialect/SparseTensor/unused-tensor.mlir
index 330bb9fa57483f5..f85acb9c6969a85 100644
--- a/mlir/test/Dialect/SparseTensor/unused-tensor.mlir
+++ b/mlir/test/Dialect/SparseTensor/unused-tensor.mlir
@@ -21,7 +21,7 @@
// CHECK-LABEL: func.func @b_ununsed(
// CHECK-SAME: %[[VAL_0:.*]]: tensor<2x4xf64>,
-// CHECK-SAME: %[[VAL_1:.*]]: tensor<8x4xf64, #sparse_tensor.encoding<{{.*}}>>,
+// CHECK-SAME: %[[VAL_1:.*]]: tensor<8x4xf64, #sparse{{[0-9]*}}>,
// CHECK-SAME: %[[VAL_2:.*]]: tensor<2x4xf64>) -> tensor<2x4xf64> {
// CHECK-DAG: %[[VAL_3:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[VAL_4:.*]] = arith.constant 2 : index
diff --git a/mlir/test/Dialect/SparseTensor/vectorize_reduction.mlir b/mlir/test/Dialect/SparseTensor/vectorize_reduction.mlir
index ef3c0f88d4222f2..d2b51322e0be491 100644
--- a/mlir/test/Dialect/SparseTensor/vectorize_reduction.mlir
+++ b/mlir/test/Dialect/SparseTensor/vectorize_reduction.mlir
@@ -9,13 +9,13 @@
// CHECK-ON-LABEL: func.func @sparse_reduction_ori(
// CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<i13>,
-// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi13, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<i13> {
+// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi13, #sparse{{[0-9]*}}>) -> tensor<i13> {
// CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
// CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant dense<0> : vector<8xi13>
// CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi13, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi13, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi13>
+// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi13, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi13, #sparse{{[0-9]*}}> to memref<?xi13>
// CHECK-ON: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : memref<i13>
// CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<i13>
// CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -37,11 +37,11 @@
//
// CHECK-OFF-LABEL: func.func @sparse_reduction_ori(
// CHECK-OFF-SAME: %[[VAL_0:.*]]: tensor<i13>,
-// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xi13, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<i13> {
+// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xi13, #sparse{{[0-9]*}}>) -> tensor<i13> {
// CHECK-OFF-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-OFF-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi13, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi13, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi13>
+// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi13, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi13, #sparse{{[0-9]*}}> to memref<?xi13>
// CHECK-OFF: %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_0]] : memref<i13>
// CHECK-OFF: %[[VAL_7:.*]] = memref.load %[[VAL_6]][] : memref<i13>
// CHECK-OFF: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
@@ -86,13 +86,13 @@ func.func @sparse_reduction_ori(%argx: tensor<i13>,
// CHECK-ON-LABEL: func.func @sparse_reduction_ori_accumulator_on_rhs(
// CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<i13>,
-// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi13, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<i13> {
+// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi13, #sparse{{[0-9]*}}>) -> tensor<i13> {
// CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
// CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant dense<0> : vector<8xi13>
// CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi13, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi13, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi13>
+// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi13, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi13, #sparse{{[0-9]*}}> to memref<?xi13>
// CHECK-ON: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : memref<i13>
// CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<i13>
// CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -114,11 +114,11 @@ func.func @sparse_reduction_ori(%argx: tensor<i13>,
//
// CHECK-OFF-LABEL: func.func @sparse_reduction_ori_accumulator_on_rhs(
// CHECK-OFF-SAME: %[[VAL_0:.*]]: tensor<i13>,
-// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xi13, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<i13> {
+// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xi13, #sparse{{[0-9]*}}>) -> tensor<i13> {
// CHECK-OFF-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-OFF-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi13, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi13, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi13>
+// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi13, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi13, #sparse{{[0-9]*}}> to memref<?xi13>
// CHECK-OFF: %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_0]] : memref<i13>
// CHECK-OFF: %[[VAL_7:.*]] = memref.load %[[VAL_6]][] : memref<i13>
// CHECK-OFF: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
@@ -161,13 +161,13 @@ func.func @sparse_reduction_ori_accumulator_on_rhs(%argx: tensor<i13>,
//
// CHECK-ON-LABEL: func.func @sparse_reduction_subi(
// CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<i32>,
-// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<i32> {
+// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse{{[0-9]*}}>) -> tensor<i32> {
// CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
// CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant 0 : index
// CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant dense<0> : vector<8xi32>
// CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi32>
+// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xi32>
// CHECK-ON: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : memref<i32>
// CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<i32>
// CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_3]]] : memref<?xindex>
@@ -189,11 +189,11 @@ func.func @sparse_reduction_ori_accumulator_on_rhs(%argx: tensor<i13>,
//
// CHECK-OFF-LABEL: func.func @sparse_reduction_subi(
// CHECK-OFF-SAME: %[[VAL_0:.*]]: tensor<i32>,
-// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<i32> {
+// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse{{[0-9]*}}>) -> tensor<i32> {
// CHECK-OFF-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-OFF-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi32>
+// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xi32>
// CHECK-OFF: %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_0]] : memref<i32>
// CHECK-OFF: %[[VAL_7:.*]] = memref.load %[[VAL_6]][] : memref<i32>
// CHECK-OFF: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
@@ -236,13 +236,13 @@ func.func @sparse_reduction_subi(%argx: tensor<i32>,
// CHECK-ON-LABEL: func.func @sparse_reduction_xor(
// CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<i32>,
-// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<i32> {
+// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse{{[0-9]*}}>) -> tensor<i32> {
// CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
// CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant dense<0> : vector<8xi32>
// CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi32>
+// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xi32>
// CHECK-ON: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : memref<i32>
// CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<i32>
// CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -264,11 +264,11 @@ func.func @sparse_reduction_subi(%argx: tensor<i32>,
//
// CHECK-OFF-LABEL: func.func @sparse_reduction_xor(
// CHECK-OFF-SAME: %[[VAL_0:.*]]: tensor<i32>,
-// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<i32> {
+// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse{{[0-9]*}}>) -> tensor<i32> {
// CHECK-OFF-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-OFF-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi32>
+// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xi32>
// CHECK-OFF: %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_0]] : memref<i32>
// CHECK-OFF: %[[VAL_7:.*]] = memref.load %[[VAL_6]][] : memref<i32>
// CHECK-OFF: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
@@ -312,13 +312,13 @@ func.func @sparse_reduction_xor(%argx: tensor<i32>,
// CHECK-ON-LABEL: func.func @sparse_reduction_addi(
// CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<i32>,
-// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<i32> {
+// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse{{[0-9]*}}>) -> tensor<i32> {
// CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
// CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant dense<0> : vector<8xi32>
// CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi32>
+// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xi32>
// CHECK-ON: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : memref<i32>
// CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<i32>
// CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -340,11 +340,11 @@ func.func @sparse_reduction_xor(%argx: tensor<i32>,
//
// CHECK-OFF-LABEL: func.func @sparse_reduction_addi(
// CHECK-OFF-SAME: %[[VAL_0:.*]]: tensor<i32>,
-// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<i32> {
+// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xi32, #sparse{{[0-9]*}}>) -> tensor<i32> {
// CHECK-OFF-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-OFF-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xi32>
+// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xi32, #sparse{{[0-9]*}}> to memref<?xi32>
// CHECK-OFF: %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_0]] : memref<i32>
// CHECK-OFF: %[[VAL_7:.*]] = memref.load %[[VAL_6]][] : memref<i32>
// CHECK-OFF: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
@@ -388,13 +388,13 @@ func.func @sparse_reduction_addi(%argx: tensor<i32>,
// CHECK-ON-LABEL: func.func @sparse_reduction_subf(
// CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<f32>,
-// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<f32> {
+// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xf32, #sparse{{[0-9]*}}>) -> tensor<f32> {
// CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
// CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant dense<0.000000e+00> : vector<8xf32>
// CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-ON: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : memref<f32>
// CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<f32>
// CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -416,11 +416,11 @@ func.func @sparse_reduction_addi(%argx: tensor<i32>,
//
// CHECK-OFF-LABEL: func.func @sparse_reduction_subf(
// CHECK-OFF-SAME: %[[VAL_0:.*]]: tensor<f32>,
-// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<f32> {
+// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xf32, #sparse{{[0-9]*}}>) -> tensor<f32> {
// CHECK-OFF-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-OFF-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-OFF: %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_0]] : memref<f32>
// CHECK-OFF: %[[VAL_7:.*]] = memref.load %[[VAL_6]][] : memref<f32>
// CHECK-OFF: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
@@ -464,13 +464,13 @@ func.func @sparse_reduction_subf(%argx: tensor<f32>,
// CHECK-ON-LABEL: func.func @sparse_reduction_addf(
// CHECK-ON-SAME: %[[VAL_0:.*]]: tensor<f32>,
-// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<f32> {
+// CHECK-ON-SAME: %[[VAL_1:.*]]: tensor<?xf32, #sparse{{[0-9]*}}>) -> tensor<f32> {
// CHECK-ON-DAG: %[[VAL_2:.*]] = arith.constant 8 : index
// CHECK-ON-DAG: %[[VAL_3:.*]] = arith.constant dense<0.000000e+00> : vector<8xf32>
// CHECK-ON-DAG: %[[VAL_4:.*]] = arith.constant 0 : index
// CHECK-ON-DAG: %[[VAL_5:.*]] = arith.constant 1 : index
-// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-ON: %[[VAL_6:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-ON: %[[VAL_7:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-ON: %[[VAL_8:.*]] = bufferization.to_memref %[[VAL_0]] : memref<f32>
// CHECK-ON: %[[VAL_9:.*]] = memref.load %[[VAL_8]][] : memref<f32>
// CHECK-ON: %[[VAL_10:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_4]]] : memref<?xindex>
@@ -492,11 +492,11 @@ func.func @sparse_reduction_subf(%argx: tensor<f32>,
//
// CHECK-OFF-LABEL: func.func @sparse_reduction_addf(
// CHECK-OFF-SAME: %[[VAL_0:.*]]: tensor<f32>,
-// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>>) -> tensor<f32> {
+// CHECK-OFF-SAME: %[[VAL_1:.*]]: tensor<?xf32, #sparse{{[0-9]*}}>) -> tensor<f32> {
// CHECK-OFF-DAG: %[[VAL_2:.*]] = arith.constant 0 : index
// CHECK-OFF-DAG: %[[VAL_3:.*]] = arith.constant 1 : index
-// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xindex>
-// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf32, #sparse_tensor.encoding<{{{.*}}}>> to memref<?xf32>
+// CHECK-OFF: %[[VAL_4:.*]] = sparse_tensor.positions %[[VAL_1]] {level = 0 : index} : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xindex>
+// CHECK-OFF: %[[VAL_5:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?xf32, #sparse{{[0-9]*}}> to memref<?xf32>
// CHECK-OFF: %[[VAL_6:.*]] = bufferization.to_memref %[[VAL_0]] : memref<f32>
// CHECK-OFF: %[[VAL_7:.*]] = memref.load %[[VAL_6]][] : memref<f32>
// CHECK-OFF: %[[VAL_8:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex>
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