[mlir] [llvm] [mlir][sparse] Change LevelType enum to 64 bit (PR #80501)
via llvm-commits
llvm-commits at lists.llvm.org
Fri Feb 2 14:40:56 PST 2024
llvmbot wrote:
<!--LLVM PR SUMMARY COMMENT-->
@llvm/pr-subscribers-mlir-sparse
Author: Yinying Li (yinying-lisa-li)
<details>
<summary>Changes</summary>
1. C++ enum is set through enum class LevelType : uint_64.
2. C enum is set through typedef uint_64 level_type. It is due to the limitations in Windows build: setting enum width to ui64 is not supported in C.
---
Full diff: https://github.com/llvm/llvm-project/pull/80501.diff
9 Files Affected:
- (modified) mlir/include/mlir-c/Dialect/SparseTensor.h (+5-4)
- (modified) mlir/include/mlir/Dialect/SparseTensor/IR/Enums.h (+19-19)
- (modified) mlir/lib/Bindings/Python/DialectSparseTensor.cpp (+2-2)
- (modified) mlir/lib/CAPI/Dialect/SparseTensor.cpp (+8-8)
- (modified) mlir/lib/Dialect/SparseTensor/Transforms/Utils/CodegenUtils.h (+1-1)
- (modified) mlir/test/CAPI/sparse_tensor.c (+2-3)
- (modified) mlir/test/Dialect/SparseTensor/conversion.mlir (+8-8)
- (modified) mlir/test/Dialect/SparseTensor/sparse_fill_zero.mlir (+6-6)
- (modified) mlir/test/python/dialects/sparse_tensor/dialect.py (+2-2)
``````````diff
diff --git a/mlir/include/mlir-c/Dialect/SparseTensor.h b/mlir/include/mlir-c/Dialect/SparseTensor.h
index 41d024db04964..25656f1b7654c 100644
--- a/mlir/include/mlir-c/Dialect/SparseTensor.h
+++ b/mlir/include/mlir-c/Dialect/SparseTensor.h
@@ -25,6 +25,8 @@ MLIR_DECLARE_CAPI_DIALECT_REGISTRATION(SparseTensor, sparse_tensor);
/// These correspond to SparseTensorEncodingAttr::LevelType in the C++ API.
/// If updating, keep them in sync and update the static_assert in the impl
/// file.
+typedef uint64_t level_type;
+
enum MlirSparseTensorLevelType {
MLIR_SPARSE_TENSOR_LEVEL_DENSE = 4, // 0b00001_00
MLIR_SPARSE_TENSOR_LEVEL_COMPRESSED = 8, // 0b00010_00
@@ -52,16 +54,15 @@ mlirAttributeIsASparseTensorEncodingAttr(MlirAttribute attr);
/// Creates a `sparse_tensor.encoding` attribute with the given parameters.
MLIR_CAPI_EXPORTED MlirAttribute mlirSparseTensorEncodingAttrGet(
- MlirContext ctx, intptr_t lvlRank,
- enum MlirSparseTensorLevelType const *lvlTypes, MlirAffineMap dimToLvl,
- MlirAffineMap lvlTodim, int posWidth, int crdWidth);
+ MlirContext ctx, intptr_t lvlRank, level_type const *lvlTypes,
+ MlirAffineMap dimToLvl, MlirAffineMap lvlTodim, int posWidth, int crdWidth);
/// Returns the level-rank of the `sparse_tensor.encoding` attribute.
MLIR_CAPI_EXPORTED intptr_t
mlirSparseTensorEncodingGetLvlRank(MlirAttribute attr);
/// Returns a specified level-type of the `sparse_tensor.encoding` attribute.
-MLIR_CAPI_EXPORTED enum MlirSparseTensorLevelType
+MLIR_CAPI_EXPORTED level_type
mlirSparseTensorEncodingAttrGetLvlType(MlirAttribute attr, intptr_t lvl);
/// Returns the dimension-to-level mapping of the `sparse_tensor.encoding`
diff --git a/mlir/include/mlir/Dialect/SparseTensor/IR/Enums.h b/mlir/include/mlir/Dialect/SparseTensor/IR/Enums.h
index ac91bfa5ae622..1f662e2042304 100644
--- a/mlir/include/mlir/Dialect/SparseTensor/IR/Enums.h
+++ b/mlir/include/mlir/Dialect/SparseTensor/IR/Enums.h
@@ -165,7 +165,7 @@ enum class Action : uint32_t {
/// where we need to store an undefined or indeterminate `LevelType`.
/// It should not be used externally, since it does not indicate an
/// actual/representable format.
-enum class LevelType : uint8_t {
+enum class LevelType : uint64_t {
Undef = 0, // 0b00000_00
Dense = 4, // 0b00001_00
Compressed = 8, // 0b00010_00
@@ -184,7 +184,7 @@ enum class LevelType : uint8_t {
};
/// This enum defines all supported storage format without the level properties.
-enum class LevelFormat : uint8_t {
+enum class LevelFormat : uint64_t {
Dense = 4, // 0b00001_00
Compressed = 8, // 0b00010_00
Singleton = 16, // 0b00100_00
@@ -193,7 +193,7 @@ enum class LevelFormat : uint8_t {
};
/// This enum defines all the nondefault properties for storage formats.
-enum class LevelPropertyNondefault : uint8_t {
+enum class LevelPropertyNondefault : uint64_t {
Nonunique = 1, // 0b00000_01
Nonordered = 2, // 0b00000_10
};
@@ -237,8 +237,8 @@ constexpr const char *toMLIRString(LevelType lt) {
/// Check that the `LevelType` contains a valid (possibly undefined) value.
constexpr bool isValidLT(LevelType lt) {
- const uint8_t formatBits = static_cast<uint8_t>(lt) >> 2;
- const uint8_t propertyBits = static_cast<uint8_t>(lt) & 3;
+ const uint64_t formatBits = static_cast<uint64_t>(lt) >> 2;
+ const uint64_t propertyBits = static_cast<uint64_t>(lt) & 3;
// If undefined or dense, then must be unique and ordered.
// Otherwise, the format must be one of the known ones.
return (formatBits <= 1 || formatBits == 16)
@@ -251,32 +251,32 @@ constexpr bool isUndefLT(LevelType lt) { return lt == LevelType::Undef; }
/// Check if the `LevelType` is dense (regardless of properties).
constexpr bool isDenseLT(LevelType lt) {
- return (static_cast<uint8_t>(lt) & ~3) ==
- static_cast<uint8_t>(LevelType::Dense);
+ return (static_cast<uint64_t>(lt) & ~3) ==
+ static_cast<uint64_t>(LevelType::Dense);
}
/// Check if the `LevelType` is compressed (regardless of properties).
constexpr bool isCompressedLT(LevelType lt) {
- return (static_cast<uint8_t>(lt) & ~3) ==
- static_cast<uint8_t>(LevelType::Compressed);
+ return (static_cast<uint64_t>(lt) & ~3) ==
+ static_cast<uint64_t>(LevelType::Compressed);
}
/// Check if the `LevelType` is singleton (regardless of properties).
constexpr bool isSingletonLT(LevelType lt) {
- return (static_cast<uint8_t>(lt) & ~3) ==
- static_cast<uint8_t>(LevelType::Singleton);
+ return (static_cast<uint64_t>(lt) & ~3) ==
+ static_cast<uint64_t>(LevelType::Singleton);
}
/// Check if the `LevelType` is loose compressed (regardless of properties).
constexpr bool isLooseCompressedLT(LevelType lt) {
- return (static_cast<uint8_t>(lt) & ~3) ==
- static_cast<uint8_t>(LevelType::LooseCompressed);
+ return (static_cast<uint64_t>(lt) & ~3) ==
+ static_cast<uint64_t>(LevelType::LooseCompressed);
}
/// Check if the `LevelType` is 2OutOf4 (regardless of properties).
constexpr bool is2OutOf4LT(LevelType lt) {
- return (static_cast<uint8_t>(lt) & ~3) ==
- static_cast<uint8_t>(LevelType::TwoOutOfFour);
+ return (static_cast<uint64_t>(lt) & ~3) ==
+ static_cast<uint64_t>(LevelType::TwoOutOfFour);
}
/// Check if the `LevelType` needs positions array.
@@ -292,12 +292,12 @@ constexpr bool isWithCrdLT(LevelType lt) {
/// Check if the `LevelType` is ordered (regardless of storage format).
constexpr bool isOrderedLT(LevelType lt) {
- return !(static_cast<uint8_t>(lt) & 2);
+ return !(static_cast<uint64_t>(lt) & 2);
}
/// Check if the `LevelType` is unique (regardless of storage format).
constexpr bool isUniqueLT(LevelType lt) {
- return !(static_cast<uint8_t>(lt) & 1);
+ return !(static_cast<uint64_t>(lt) & 1);
}
/// Convert a LevelType to its corresponding LevelFormat.
@@ -305,7 +305,7 @@ constexpr bool isUniqueLT(LevelType lt) {
constexpr std::optional<LevelFormat> getLevelFormat(LevelType lt) {
if (lt == LevelType::Undef)
return std::nullopt;
- return static_cast<LevelFormat>(static_cast<uint8_t>(lt) & ~3);
+ return static_cast<LevelFormat>(static_cast<uint64_t>(lt) & ~3);
}
/// Convert a LevelFormat to its corresponding LevelType with the given
@@ -313,7 +313,7 @@ constexpr std::optional<LevelFormat> getLevelFormat(LevelType lt) {
/// for the input level format.
constexpr std::optional<LevelType> buildLevelType(LevelFormat lf, bool ordered,
bool unique) {
- auto lt = static_cast<LevelType>(static_cast<uint8_t>(lf) |
+ auto lt = static_cast<LevelType>(static_cast<uint64_t>(lf) |
(ordered ? 0 : 2) | (unique ? 0 : 1));
return isValidLT(lt) ? std::optional(lt) : std::nullopt;
}
diff --git a/mlir/lib/Bindings/Python/DialectSparseTensor.cpp b/mlir/lib/Bindings/Python/DialectSparseTensor.cpp
index 8706c523988b1..3fe6a9e495dc5 100644
--- a/mlir/lib/Bindings/Python/DialectSparseTensor.cpp
+++ b/mlir/lib/Bindings/Python/DialectSparseTensor.cpp
@@ -46,7 +46,7 @@ static void populateDialectSparseTensorSubmodule(const py::module &m) {
mlirAttributeIsASparseTensorEncodingAttr)
.def_classmethod(
"get",
- [](py::object cls, std::vector<MlirSparseTensorLevelType> lvlTypes,
+ [](py::object cls, std::vector<level_type> lvlTypes,
std::optional<MlirAffineMap> dimToLvl,
std::optional<MlirAffineMap> lvlToDim, int posWidth, int crdWidth,
MlirContext context) {
@@ -64,7 +64,7 @@ static void populateDialectSparseTensorSubmodule(const py::module &m) {
"lvl_types",
[](MlirAttribute self) {
const int lvlRank = mlirSparseTensorEncodingGetLvlRank(self);
- std::vector<MlirSparseTensorLevelType> ret;
+ std::vector<level_type> ret;
ret.reserve(lvlRank);
for (int l = 0; l < lvlRank; ++l)
ret.push_back(mlirSparseTensorEncodingAttrGetLvlType(self, l));
diff --git a/mlir/lib/CAPI/Dialect/SparseTensor.cpp b/mlir/lib/CAPI/Dialect/SparseTensor.cpp
index e4534ad132385..3f17b740e813c 100644
--- a/mlir/lib/CAPI/Dialect/SparseTensor.cpp
+++ b/mlir/lib/CAPI/Dialect/SparseTensor.cpp
@@ -44,11 +44,11 @@ bool mlirAttributeIsASparseTensorEncodingAttr(MlirAttribute attr) {
return isa<SparseTensorEncodingAttr>(unwrap(attr));
}
-MlirAttribute
-mlirSparseTensorEncodingAttrGet(MlirContext ctx, intptr_t lvlRank,
- MlirSparseTensorLevelType const *lvlTypes,
- MlirAffineMap dimToLvl, MlirAffineMap lvlToDim,
- int posWidth, int crdWidth) {
+MlirAttribute mlirSparseTensorEncodingAttrGet(MlirContext ctx, intptr_t lvlRank,
+ level_type const *lvlTypes,
+ MlirAffineMap dimToLvl,
+ MlirAffineMap lvlToDim,
+ int posWidth, int crdWidth) {
SmallVector<LevelType> cppLvlTypes;
cppLvlTypes.reserve(lvlRank);
for (intptr_t l = 0; l < lvlRank; ++l)
@@ -70,9 +70,9 @@ intptr_t mlirSparseTensorEncodingGetLvlRank(MlirAttribute attr) {
return cast<SparseTensorEncodingAttr>(unwrap(attr)).getLvlRank();
}
-MlirSparseTensorLevelType
-mlirSparseTensorEncodingAttrGetLvlType(MlirAttribute attr, intptr_t lvl) {
- return static_cast<MlirSparseTensorLevelType>(
+level_type mlirSparseTensorEncodingAttrGetLvlType(MlirAttribute attr,
+ intptr_t lvl) {
+ return static_cast<level_type>(
cast<SparseTensorEncodingAttr>(unwrap(attr)).getLvlType(lvl));
}
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/CodegenUtils.h b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/CodegenUtils.h
index 8d54b5959d871..cc119bc704559 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/Utils/CodegenUtils.h
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/Utils/CodegenUtils.h
@@ -423,7 +423,7 @@ inline Value constantPrimaryTypeEncoding(OpBuilder &builder, Location loc,
/// Generates a constant of the internal dimension level type encoding.
inline Value constantLevelTypeEncoding(OpBuilder &builder, Location loc,
LevelType lt) {
- return constantI8(builder, loc, static_cast<uint8_t>(lt));
+ return constantI64(builder, loc, static_cast<uint64_t>(lt));
}
inline bool isZeroRankedTensorOrScalar(Type type) {
diff --git a/mlir/test/CAPI/sparse_tensor.c b/mlir/test/CAPI/sparse_tensor.c
index b0bc9bb6e881a..f3edce81c35f5 100644
--- a/mlir/test/CAPI/sparse_tensor.c
+++ b/mlir/test/CAPI/sparse_tensor.c
@@ -43,11 +43,10 @@ static int testRoundtripEncoding(MlirContext ctx) {
MlirAffineMap lvlToDim =
mlirSparseTensorEncodingAttrGetLvlToDim(originalAttr);
int lvlRank = mlirSparseTensorEncodingGetLvlRank(originalAttr);
- enum MlirSparseTensorLevelType *lvlTypes =
- malloc(sizeof(enum MlirSparseTensorLevelType) * lvlRank);
+ level_type *lvlTypes = malloc(sizeof(level_type) * lvlRank);
for (int l = 0; l < lvlRank; ++l) {
lvlTypes[l] = mlirSparseTensorEncodingAttrGetLvlType(originalAttr, l);
- fprintf(stderr, "level_type: %d\n", lvlTypes[l]);
+ fprintf(stderr, "level_type: %lu\n", lvlTypes[l]);
}
// CHECK: posWidth: 32
int posWidth = mlirSparseTensorEncodingAttrGetPosWidth(originalAttr);
diff --git a/mlir/test/Dialect/SparseTensor/conversion.mlir b/mlir/test/Dialect/SparseTensor/conversion.mlir
index e4e825bf85043..465f210862660 100644
--- a/mlir/test/Dialect/SparseTensor/conversion.mlir
+++ b/mlir/test/Dialect/SparseTensor/conversion.mlir
@@ -78,8 +78,8 @@ func.func @sparse_dim3d_const(%arg0: tensor<10x20x30xf64, #SparseTensor>) -> ind
// CHECK-DAG: %[[DimShape0:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[DimShape:.*]] = memref.cast %[[DimShape0]] : memref<1xindex> to memref<?xindex>
// CHECK: %[[Reader:.*]] = call @createCheckedSparseTensorReader(%[[A]], %[[DimShape]], %{{.*}})
-// CHECK-DAG: %[[LvlTypes0:.*]] = memref.alloca() : memref<1xi8>
-// CHECK-DAG: %[[LvlTypes:.*]] = memref.cast %[[LvlTypes0]] : memref<1xi8> to memref<?xi8>
+// CHECK-DAG: %[[LvlTypes0:.*]] = memref.alloca() : memref<1xi64>
+// CHECK-DAG: %[[LvlTypes:.*]] = memref.cast %[[LvlTypes0]] : memref<1xi64> to memref<?xi64>
// CHECK-DAG: %[[Iota0:.*]] = memref.alloca() : memref<1xindex>
// CHECK-DAG: %[[Iota:.*]] = memref.cast %[[Iota0]] : memref<1xindex> to memref<?xindex>
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[DimShape]], %[[DimShape]], %[[LvlTypes]], %[[Iota]], %[[Iota]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[Reader]])
@@ -96,8 +96,8 @@ func.func @sparse_new1d(%arg0: !llvm.ptr) -> tensor<128xf64, #SparseVector> {
// CHECK-DAG: %[[DimShape:.*]] = memref.cast %[[DimShape0]] : memref<2xindex> to memref<?xindex>
// CHECK: %[[Reader:.*]] = call @createCheckedSparseTensorReader(%[[A]], %[[DimShape]], %{{.*}})
// CHECK: %[[DimSizes:.*]] = call @getSparseTensorReaderDimSizes(%[[Reader]])
-// CHECK-DAG: %[[LvlTypes0:.*]] = memref.alloca() : memref<2xi8>
-// CHECK-DAG: %[[LvlTypes:.*]] = memref.cast %[[LvlTypes0]] : memref<2xi8> to memref<?xi8>
+// CHECK-DAG: %[[LvlTypes0:.*]] = memref.alloca() : memref<2xi64>
+// CHECK-DAG: %[[LvlTypes:.*]] = memref.cast %[[LvlTypes0]] : memref<2xi64> to memref<?xi64>
// CHECK-DAG: %[[Iota0:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[Iota:.*]] = memref.cast %[[Iota0]] : memref<2xindex> to memref<?xindex>
// CHECK: %[[T:.*]] = call @newSparseTensor(%[[DimSizes]], %[[DimSizes]], %[[LvlTypes]], %[[Iota]], %[[Iota]], %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[Reader]])
@@ -114,8 +114,8 @@ func.func @sparse_new2d(%arg0: !llvm.ptr) -> tensor<?x?xf32, #CSR> {
// CHECK-DAG: %[[DimShape:.*]] = memref.cast %[[DimShape0]] : memref<3xindex> to memref<?xindex>
// CHECK: %[[Reader:.*]] = call @createCheckedSparseTensorReader(%[[A]], %[[DimShape]], %{{.*}})
// CHECK: %[[DimSizes:.*]] = call @getSparseTensorReaderDimSizes(%[[Reader]])
-// CHECK-DAG: %[[LvlTypes0:.*]] = memref.alloca() : memref<3xi8>
-// CHECK-DAG: %[[LvlTypes:.*]] = memref.cast %[[LvlTypes0]] : memref<3xi8> to memref<?xi8>
+// CHECK-DAG: %[[LvlTypes0:.*]] = memref.alloca() : memref<3xi64>
+// CHECK-DAG: %[[LvlTypes:.*]] = memref.cast %[[LvlTypes0]] : memref<3xi64> to memref<?xi64>
// CHECK-DAG: %[[Dim2Lvl0:.*]] = memref.alloca() : memref<3xindex>
// CHECK-DAG: %[[Dim2Lvl:.*]] = memref.cast %[[Dim2Lvl0]] : memref<3xindex> to memref<?xindex>
// CHECK-DAG: %[[Lvl2Dim0:.*]] = memref.alloca() : memref<3xindex>
@@ -136,10 +136,10 @@ func.func @sparse_new3d(%arg0: !llvm.ptr) -> tensor<?x?x?xf32, #SparseTensor> {
// CHECK-DAG: %[[Empty:.*]] = arith.constant 0 : i32
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
-// CHECK-DAG: %[[LvlTypes0:.*]] = memref.alloca() : memref<2xi8>
+// CHECK-DAG: %[[LvlTypes0:.*]] = memref.alloca() : memref<2xi64>
// CHECK-DAG: %[[Sizes0:.*]] = memref.alloca() : memref<2xindex>
// CHECK-DAG: %[[Iota0:.*]] = memref.alloca() : memref<2xindex>
-// CHECK-DAG: %[[LvlTypes:.*]] = memref.cast %[[LvlTypes0]] : memref<2xi8> to memref<?xi8>
+// CHECK-DAG: %[[LvlTypes:.*]] = memref.cast %[[LvlTypes0]] : memref<2xi64> to memref<?xi64>
// CHECK-DAG: %[[Sizes:.*]] = memref.cast %[[Sizes0]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: %[[Iota:.*]] = memref.cast %[[Iota0]] : memref<2xindex> to memref<?xindex>
// CHECK-DAG: memref.store %[[I]], %[[Sizes0]][%[[C0]]] : memref<2xindex>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_fill_zero.mlir b/mlir/test/Dialect/SparseTensor/sparse_fill_zero.mlir
index 40367f12f85a4..7c494b2bcfe1d 100644
--- a/mlir/test/Dialect/SparseTensor/sparse_fill_zero.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_fill_zero.mlir
@@ -14,11 +14,11 @@
// CHECK-DAG: %[[VAL_8:.*]] = arith.constant true
// CHECK-DAG: %[[VAL_9:.*]] = arith.constant 100 : index
// CHECK-DAG: %[[VAL_10:.*]] = arith.constant 300 : index
-// CHECK-DAG: %[[VAL_11:.*]] = arith.constant 8 : i8
-// CHECK: %[[VAL_12:.*]] = memref.alloca() : memref<2xi8>
-// CHECK: %[[VAL_13:.*]] = memref.cast %[[VAL_12]] : memref<2xi8> to memref<?xi8>
-// CHECK: memref.store %[[VAL_11]], %[[VAL_12]]{{\[}}%[[VAL_5]]] : memref<2xi8>
-// CHECK: memref.store %[[VAL_11]], %[[VAL_12]]{{\[}}%[[VAL_6]]] : memref<2xi8>
+// CHECK-DAG: %[[VAL_11:.*]] = arith.constant 8 : i64
+// CHECK: %[[VAL_12:.*]] = memref.alloca() : memref<2xi64>
+// CHECK: %[[VAL_13:.*]] = memref.cast %[[VAL_12]] : memref<2xi64> to memref<?xi64>
+// CHECK: memref.store %[[VAL_11]], %[[VAL_12]]{{\[}}%[[VAL_5]]] : memref<2xi64>
+// CHECK: memref.store %[[VAL_11]], %[[VAL_12]]{{\[}}%[[VAL_6]]] : memref<2xi64>
// CHECK: %[[VAL_14:.*]] = memref.alloca() : memref<2xindex>
// CHECK: %[[VAL_15:.*]] = memref.cast %[[VAL_14]] : memref<2xindex> to memref<?xindex>
// CHECK: memref.store %[[VAL_9]], %[[VAL_14]]{{\[}}%[[VAL_5]]] : memref<2xindex>
@@ -28,7 +28,7 @@
// CHECK: memref.store %[[VAL_5]], %[[VAL_16]]{{\[}}%[[VAL_5]]] : memref<2xindex>
// CHECK: memref.store %[[VAL_6]], %[[VAL_16]]{{\[}}%[[VAL_6]]] : memref<2xindex>
// CHECK: %[[VAL_18:.*]] = llvm.mlir.zero : !llvm.ptr
-// CHECK: %[[VAL_19:.*]] = call @newSparseTensor(%[[VAL_15]], %[[VAL_15]], %[[VAL_13]], %[[VAL_17]], %[[VAL_17]], %[[VAL_4]], %[[VAL_4]], %[[VAL_3]], %[[VAL_4]], %[[VAL_18]]) : (memref<?xindex>, memref<?xindex>, memref<?xi8>, memref<?xindex>, memref<?xindex>, i32, i32, i32, i32, !llvm.ptr) -> !llvm.ptr
+// CHECK: %[[VAL_19:.*]] = call @newSparseTensor(%[[VAL_15]], %[[VAL_15]], %[[VAL_13]], %[[VAL_17]], %[[VAL_17]], %[[VAL_4]], %[[VAL_4]], %[[VAL_3]], %[[VAL_4]], %[[VAL_18]]) : (memref<?xindex>, memref<?xindex>, memref<?xi64>, memref<?xindex>, memref<?xindex>, i32, i32, i32, i32, !llvm.ptr) -> !llvm.ptr
// CHECK: %[[VAL_20:.*]] = memref.alloc() : memref<300xf64>
// CHECK: %[[VAL_21:.*]] = memref.cast %[[VAL_20]] : memref<300xf64> to memref<?xf64>
// CHECK: %[[VAL_22:.*]] = memref.alloc() : memref<300xi1>
diff --git a/mlir/test/python/dialects/sparse_tensor/dialect.py b/mlir/test/python/dialects/sparse_tensor/dialect.py
index 88a5595d75aea..946a224dab064 100644
--- a/mlir/test/python/dialects/sparse_tensor/dialect.py
+++ b/mlir/test/python/dialects/sparse_tensor/dialect.py
@@ -28,7 +28,7 @@ def testEncodingAttr1D():
# CHECK: equal: True
print(f"equal: {casted == parsed}")
- # CHECK: lvl_types: [<LevelType.compressed: 8>]
+ # CHECK: lvl_types: [8]
print(f"lvl_types: {casted.lvl_types}")
# CHECK: dim_to_lvl: (d0) -> (d0)
print(f"dim_to_lvl: {casted.dim_to_lvl}")
@@ -70,7 +70,7 @@ def testEncodingAttr2D():
# CHECK: equal: True
print(f"equal: {casted == parsed}")
- # CHECK: lvl_types: [<LevelType.dense: 4>, <LevelType.compressed: 8>]
+ # CHECK: lvl_types: [4, 8]
print(f"lvl_types: {casted.lvl_types}")
# CHECK: dim_to_lvl: (d0, d1) -> (d1, d0)
print(f"dim_to_lvl: {casted.dim_to_lvl}")
``````````
</details>
https://github.com/llvm/llvm-project/pull/80501
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