Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

[mlir][sparse] Print new syntax #68130

Merged
merged 7 commits into from
Oct 4, 2023
Merged

[mlir][sparse] Print new syntax #68130

Show file tree
Hide file tree
Changes from 5 commits
Commits
Show all changes
7 commits
Select commit Hold shift + click to select a range
801ed55
[mlir][sparse] Print new syntax
yinying-lisa-li Oct 3, 2023
fcc828d
format
yinying-lisa-li Oct 3, 2023
13802d4
update function name
yinying-lisa-li Oct 3, 2023
2f6c890
make replace function more compact
yinying-lisa-li Oct 3, 2023
5e30002
address reivew comments
yinying-lisa-li Oct 4, 2023
1087c46
address comments
yinying-lisa-li Oct 4, 2023
8066a93
change printing functions to plural form
yinying-lisa-li Oct 4, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
20 changes: 10 additions & 10 deletions mlir/include/mlir/Dialect/SparseTensor/IR/Enums.h
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -215,29 +215,29 @@ constexpr const char *toMLIRString(DimLevelType dlt) {
case DimLevelType::Compressed:
return "compressed";
case DimLevelType::CompressedNu:
return "compressed_nu";
return "compressed(nonunique)";
case DimLevelType::CompressedNo:
return "compressed_no";
return "compressed(nonordered)";
case DimLevelType::CompressedNuNo:
return "compressed_nu_no";
return "compressed(nonunique, nonordered)";
case DimLevelType::Singleton:
return "singleton";
case DimLevelType::SingletonNu:
return "singleton_nu";
return "singleton(nonunique)";
case DimLevelType::SingletonNo:
return "singleton_no";
return "singleton(nonordered)";
case DimLevelType::SingletonNuNo:
return "singleton_nu_no";
return "singleton(nonunique, nonordered)";
case DimLevelType::LooseCompressed:
return "loose_compressed";
case DimLevelType::LooseCompressedNu:
return "loose_compressed_nu";
return "loose_compressed(nonunique)";
case DimLevelType::LooseCompressedNo:
return "loose_compressed_no";
return "loose_compressed(nonordered)";
case DimLevelType::LooseCompressedNuNo:
return "loose_compressed_nu_no";
return "loose_compressed(nonunique, nonordered)";
case DimLevelType::TwoOutOfFour:
return "compressed24";
return "block2_4";
}
return "";
}
Expand Down
8 changes: 8 additions & 0 deletions mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -422,6 +422,14 @@ def SparseTensorEncodingAttr : SparseTensor_Attr<"SparseTensorEncoding",
std::optional<uint64_t> getStaticLvlSliceOffset(::mlir::sparse_tensor::Level lvl) const;
std::optional<uint64_t> getStaticLvlSliceSize(::mlir::sparse_tensor::Level lvl) const;
std::optional<uint64_t> getStaticLvlSliceStride(::mlir::sparse_tensor::Level lvl) const;

//
// Printing methods.
//

void printSymbol(AffineMap &map, AsmPrinter &printer) const;
yinying-lisa-li marked this conversation as resolved.
Show resolved Hide resolved
void printDimension(AffineMap &map, AsmPrinter &printer, ArrayRef<::mlir::sparse_tensor::SparseTensorDimSliceAttr> dimSlices) const;
void printLevel(AffineMap &map, AsmPrinter &printer, ArrayRef<::mlir::sparse_tensor::DimLevelType> lvlTypes) const;
}];

let genVerifyDecl = 1;
Expand Down
72 changes: 54 additions & 18 deletions mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -586,31 +586,67 @@ Attribute SparseTensorEncodingAttr::parse(AsmParser &parser, Type type) {
}

void SparseTensorEncodingAttr::print(AsmPrinter &printer) const {
// Print the struct-like storage in dictionary fashion.
printer << "<{ lvlTypes = [ ";
llvm::interleaveComma(getLvlTypes(), printer, [&](DimLevelType dlt) {
printer << "\"" << toMLIRString(dlt) << "\"";
});
printer << " ]";
auto map = static_cast<AffineMap>(getDimToLvl());
// Empty affine map indicates identity map
if (!map) {
map = AffineMap::getMultiDimIdentityMap(getLvlTypes().size(), getContext());
}
printer << "<{ map = ";
printSymbol(map, printer);
printer << '(';
printDimension(map, printer, getDimSlices());
printer << ") -> (";
printLevel(map, printer, getLvlTypes());
printer << ')';
// Print remaining members only for non-default values.
if (!isIdentity())
printer << ", dimToLvl = affine_map<" << getDimToLvl() << ">";
if (getPosWidth())
printer << ", posWidth = " << getPosWidth();
if (getCrdWidth())
printer << ", crdWidth = " << getCrdWidth();
if (!getDimSlices().empty()) {
printer << ", dimSlices = [ ";
llvm::interleaveComma(getDimSlices(), printer,
[&](SparseTensorDimSliceAttr attr) {
// Calls SparseTensorDimSliceAttr::print directly to
// skip mnemonic.
attr.print(printer);
});
printer << " ]";
printer << " }>";
}

void SparseTensorEncodingAttr::printSymbol(AffineMap &map,
AsmPrinter &printer) const {
if (map.getNumSymbols() != 0) {
yinying-lisa-li marked this conversation as resolved.
Show resolved Hide resolved
printer << '[';
for (unsigned i = 0; i < map.getNumSymbols() - 1; ++i)
printer << 's' << i << ", ";
if (map.getNumSymbols() >= 1)
printer << 's' << map.getNumSymbols() - 1;
printer << ']';
}
}

printer << " }>";
void SparseTensorEncodingAttr::printDimension(
AffineMap &map, AsmPrinter &printer,
ArrayRef<SparseTensorDimSliceAttr> dimSlices) const {
if (!dimSlices.empty()) {
for (unsigned i = 0; i < map.getNumDims() - 1; ++i)
yinying-lisa-li marked this conversation as resolved.
Show resolved Hide resolved
printer << 'd' << i << " : " << dimSlices[i] << ", ";
if (map.getNumDims() >= 1)
printer << 'd' << map.getNumDims() - 1 << " : "
<< dimSlices[map.getNumDims() - 1];
} else {
for (unsigned i = 0; i < map.getNumDims() - 1; ++i)
yinying-lisa-li marked this conversation as resolved.
Show resolved Hide resolved
printer << 'd' << i << ", ";
if (map.getNumDims() >= 1)
printer << 'd' << map.getNumDims() - 1;
}
}

void SparseTensorEncodingAttr::printLevel(
AffineMap &map, AsmPrinter &printer,
ArrayRef<DimLevelType> lvlTypes) const {
for (unsigned i = 0; i < map.getNumResults() - 1; ++i) {
yinying-lisa-li marked this conversation as resolved.
Show resolved Hide resolved
map.getResult(i).print(printer.getStream());
printer << " : " << toMLIRString(lvlTypes[i]) << ", ";
}
if (map.getNumResults() >= 1) {
auto lastIndex = map.getNumResults() - 1;
map.getResult(lastIndex).print(printer.getStream());
printer << " : " << toMLIRString(lvlTypes[lastIndex]);
}
}

LogicalResult
Expand Down
13 changes: 11 additions & 2 deletions mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorCodegen.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -472,8 +472,17 @@ class SparseInsertGenerator
llvm::raw_svector_ostream nameOstream(nameBuffer);
nameOstream << kInsertFuncNamePrefix;
const Level lvlRank = stt.getLvlRank();
for (Level l = 0; l < lvlRank; l++)
nameOstream << toMLIRString(stt.getLvlType(l)) << "_";
for (Level l = 0; l < lvlRank; l++) {
std::string lvlType = toMLIRString(stt.getLvlType(l));
// Replace/remove punctuations in level properties.
std::replace_if(
lvlType.begin(), lvlType.end(),
[](char c) { return c == '(' || c == ','; }, '_');
lvlType.erase(std::remove_if(lvlType.begin(), lvlType.end(),
[](char c) { return c == ')' || c == ' '; }),
lvlType.end());
nameOstream << lvlType << "_";
}
// Static dim sizes are used in the generated code while dynamic sizes are
// loaded from the dimSizes buffer. This is the reason for adding the shape
// to the function name.
Expand Down
8 changes: 4 additions & 4 deletions mlir/test/Dialect/SparseTensor/codegen.mlir
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -507,7 +507,7 @@ func.func @sparse_compression(%tensor: tensor<8x8xf64, #CSR>,
return %1 : tensor<8x8xf64, #CSR>
}

// CHECK-LABEL: func.func private @_insert_dense_compressed_no_8_8_f64_0_0(
// CHECK-LABEL: func.func private @_insert_dense_compressed_nonordered_8_8_f64_0_0(
// CHECK-SAME: %[[A1:.*0]]: memref<?xindex>,
// CHECK-SAME: %[[A2:.*1]]: memref<?xindex>,
// CHECK-SAME: %[[A3:.*2]]: memref<?xf64>,
Expand All @@ -533,7 +533,7 @@ func.func @sparse_compression(%tensor: tensor<8x8xf64, #CSR>,
// CHECK: %[[A13:.*]]:4 = scf.for %[[A14:.*]] = %[[A11]] to %[[A7]] step %[[A12]] iter_args(%[[A15:.*]] = %[[A0]], %[[A16:.*]] = %[[A1]], %[[A17:.*]] = %[[A2]], %[[A18:.*]] = %[[A3]]) -> (memref<?xindex>, memref<?xindex>, memref<?xf64>, !sparse_tensor.storage_specifier
// CHECK: %[[A19:.*]] = memref.load %[[A6]]{{\[}}%[[A14]]] : memref<?xindex>
// CHECK: %[[A20:.*]] = memref.load %[[A4]]{{\[}}%[[A19]]] : memref<?xf64>
// CHECK: %[[A21:.*]]:4 = func.call @_insert_dense_compressed_no_8_8_f64_0_0(%[[A15]], %[[A16]], %[[A17]], %[[A18]], %[[A8]], %[[A19]], %[[A20]]) : (memref<?xindex>, memref<?xindex>, memref<?xf64>, !sparse_tensor.storage_specifier
// CHECK: %[[A21:.*]]:4 = func.call @_insert_dense_compressed_nonordered_8_8_f64_0_0(%[[A15]], %[[A16]], %[[A17]], %[[A18]], %[[A8]], %[[A19]], %[[A20]]) : (memref<?xindex>, memref<?xindex>, memref<?xf64>, !sparse_tensor.storage_specifier
// CHECK: memref.store %[[A10]], %[[A4]]{{\[}}%[[A19]]] : memref<?xf64>
// CHECK: memref.store %[[A9]], %[[A5]]{{\[}}%[[A19]]] : memref<?xi1>
// CHECK: scf.yield %[[A21]]#0, %[[A21]]#1, %[[A21]]#2, %[[A21]]#3 : memref<?xindex>, memref<?xindex>, memref<?xf64>, !sparse_tensor.storage_specifier
Expand Down Expand Up @@ -611,7 +611,7 @@ func.func @sparse_insert_typed(%arg0: tensor<128xf64, #SparseVector>, %arg1: ind
return %1 : tensor<128xf64, #SparseVector>
}

// CHECK-LABEL: func.func private @_insert_compressed_nu_singleton_5_6_f64_0_0(
// CHECK-LABEL: func.func private @_insert_compressed_nonunique_singleton_5_6_f64_0_0(
// CHECK-SAME: %[[A1:.*0]]: memref<?xindex>,
// CHECK-SAME: %[[A2:.*1]]: memref<?xindex>,
// CHECK-SAME: %[[A3:.*2]]: memref<?xf64>,
Expand All @@ -627,7 +627,7 @@ func.func @sparse_insert_typed(%arg0: tensor<128xf64, #SparseVector>, %arg1: ind
// CHECK-SAME: %[[A3:.*3]]: !sparse_tensor.storage_specifier
// CHECK-SAME: %[[A4:.*4]]: index,
// CHECK-SAME: %[[A5:.*5]]: f64)
// CHECK: %[[R:.*]]:4 = call @_insert_compressed_nu_singleton_5_6_f64_0_0(%[[A0]], %[[A1]], %[[A2]], %[[A3]], %[[A4]], %[[A4]], %[[A5]])
// CHECK: %[[R:.*]]:4 = call @_insert_compressed_nonunique_singleton_5_6_f64_0_0(%[[A0]], %[[A1]], %[[A2]], %[[A3]], %[[A4]], %[[A4]], %[[A5]])
// CHECK: return %[[R]]#0, %[[R]]#1, %[[R]]#2, %[[R]]#3
func.func @sparse_insert_coo(%arg0: tensor<5x6xf64, #Coo>, %arg1: index, %arg2: f64) -> tensor<5x6xf64, #Coo> {
%0 = sparse_tensor.insert %arg2 into %arg0[%arg1, %arg1] : tensor<5x6xf64, #Coo>
Expand Down
32 changes: 16 additions & 16 deletions mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
// RUN: mlir-opt %s -split-input-file | mlir-opt | FileCheck %s

// CHECK-LABEL: func private @sparse_1d_tensor(
// CHECK-SAME: tensor<32xf64, #sparse_tensor.encoding<{ lvlTypes = [ "compressed" ] }>>)
// 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) }>>)

// -----
Expand All @@ -13,7 +13,7 @@ func.func private @sparse_1d_tensor(tensor<32xf64, #sparse_tensor.encoding<{ map
}>

// CHECK-LABEL: func private @sparse_csr(
// CHECK-SAME: tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ], posWidth = 64, crdWidth = 64 }>>)
// CHECK-SAME: tensor<?x?xf32, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed), posWidth = 64, crdWidth = 64 }>>)
func.func private @sparse_csr(tensor<?x?xf32, #CSR>)

// -----
Expand All @@ -23,7 +23,7 @@ func.func private @sparse_csr(tensor<?x?xf32, #CSR>)
}>

// CHECK-LABEL: func private @CSR_explicit(
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>>
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }>>
func.func private @CSR_explicit(%arg0: tensor<?x?xf64, #CSR_explicit>) {
return
}
Expand All @@ -37,7 +37,7 @@ func.func private @CSR_explicit(%arg0: tensor<?x?xf64, #CSR_explicit>) {
}>

// CHECK-LABEL: func private @sparse_csc(
// CHECK-SAME: tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ], dimToLvl = affine_map<(d0, d1) -> (d1, d0)> }>>)
// CHECK-SAME: tensor<?x?xf32, #sparse_tensor.encoding<{ map = (d0, d1) -> (d1 : dense, d0 : compressed) }>>)
func.func private @sparse_csc(tensor<?x?xf32, #CSC>)

// -----
Expand All @@ -49,7 +49,7 @@ func.func private @sparse_csc(tensor<?x?xf32, #CSC>)
}>

// CHECK-LABEL: func private @sparse_dcsc(
// CHECK-SAME: tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "compressed" ], dimToLvl = affine_map<(d0, d1) -> (d1, d0)>, crdWidth = 64 }>>)
// CHECK-SAME: tensor<?x?xf32, #sparse_tensor.encoding<{ map = (d0, d1) -> (d1 : compressed, d0 : compressed), crdWidth = 64 }>>)
func.func private @sparse_dcsc(tensor<?x?xf32, #DCSC>)

// -----
Expand All @@ -59,7 +59,7 @@ func.func private @sparse_dcsc(tensor<?x?xf32, #DCSC>)
}>

// CHECK-LABEL: func private @sparse_coo(
// CHECK-SAME: tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "compressed_nu_no", "singleton_no" ] }>>)
// CHECK-SAME: tensor<?x?xf32, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed(nonunique, nonordered), d1 : singleton(nonordered)) }>>)
func.func private @sparse_coo(tensor<?x?xf32, #COO>)

// -----
Expand All @@ -69,7 +69,7 @@ func.func private @sparse_coo(tensor<?x?xf32, #COO>)
}>

// CHECK-LABEL: func private @sparse_bcoo(
// CHECK-SAME: tensor<?x?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "loose_compressed_nu", "singleton" ] }>>)
// CHECK-SAME: tensor<?x?x?xf32, #sparse_tensor.encoding<{ map = (d0, d1, d2) -> (d0 : dense, d1 : loose_compressed(nonunique), d2 : singleton) }>>)
func.func private @sparse_bcoo(tensor<?x?x?xf32, #BCOO>)

// -----
Expand All @@ -79,7 +79,7 @@ func.func private @sparse_bcoo(tensor<?x?x?xf32, #BCOO>)
}>

// CHECK-LABEL: func private @sparse_sorted_coo(
// CHECK-SAME: tensor<10x10xf64, #sparse_tensor.encoding<{ lvlTypes = [ "compressed_nu", "singleton" ] }>>)
// CHECK-SAME: tensor<10x10xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton) }>>)
func.func private @sparse_sorted_coo(tensor<10x10xf64, #SortedCOO>)

// -----
Expand All @@ -94,7 +94,7 @@ func.func private @sparse_sorted_coo(tensor<10x10xf64, #SortedCOO>)
}>

// CHECK-LABEL: func private @sparse_bcsr(
// CHECK-SAME: tensor<10x60xf64, #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "compressed", "dense", "dense" ], dimToLvl = affine_map<(d0, d1) -> (d0 floordiv 2, d1 floordiv 3, d0 mod 2, d1 mod 3)> }>>
// CHECK-SAME: tensor<10x60xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 floordiv 2 : compressed, d1 floordiv 3 : compressed, d0 mod 2 : dense, d1 mod 3 : dense) }>>
func.func private @sparse_bcsr(tensor<10x60xf64, #BCSR>)


Expand All @@ -105,7 +105,7 @@ func.func private @sparse_bcsr(tensor<10x60xf64, #BCSR>)
}>

// CHECK-LABEL: func private @sparse_ell(
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "dense", "compressed" ], dimToLvl = affine_map<(d0, d1)[s0] -> (d0 * (s0 * 4), d0, d1)> }>>
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = [s0](d0, d1) -> (d0 * (s0 * 4) : dense, d0 : dense, d1 : compressed) }>>
func.func private @sparse_ell(tensor<?x?xf64, #ELL>)

// -----
Expand All @@ -115,7 +115,7 @@ func.func private @sparse_ell(tensor<?x?xf64, #ELL>)
}>

// CHECK-LABEL: func private @sparse_slice(
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ], dimSlices = [ (1, 4, 1), (1, 4, 2) ] }>>
// 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) }>>
func.func private @sparse_slice(tensor<?x?xf64, #CSR_SLICE>)

// -----
Expand All @@ -125,7 +125,7 @@ func.func private @sparse_slice(tensor<?x?xf64, #CSR_SLICE>)
}>

// CHECK-LABEL: func private @sparse_slice(
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ], dimSlices = [ (1, ?, 1), (?, 4, 2) ] }>>
// 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) }>>
func.func private @sparse_slice(tensor<?x?xf64, #CSR_SLICE>)

// -----
Expand All @@ -138,7 +138,7 @@ func.func private @sparse_slice(tensor<?x?xf64, #CSR_SLICE>)
}>

// CHECK-LABEL: func private @sparse_2_out_of_4(
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed24" ] }>>
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : block2_4) }>>
func.func private @sparse_2_out_of_4(tensor<?x?xf64, #NV_24>)

// -----
Expand All @@ -153,7 +153,7 @@ func.func private @sparse_2_out_of_4(tensor<?x?xf64, #NV_24>)
}>

// CHECK-LABEL: func private @BCSR(
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "compressed", "dense", "dense" ], dimToLvl = affine_map<(d0, d1) -> (d0 floordiv 2, d1 floordiv 3, d0 mod 2, d1 mod 3)> }>>
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 floordiv 2 : compressed, d1 floordiv 3 : compressed, d0 mod 2 : dense, d1 mod 3 : dense) }>>
func.func private @BCSR(%arg0: tensor<?x?xf64, #BCSR>) {
return
}
Expand All @@ -174,7 +174,7 @@ func.func private @BCSR(%arg0: tensor<?x?xf64, #BCSR>) {
}>

// CHECK-LABEL: func private @BCSR_explicit(
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ lvlTypes = [ "compressed", "compressed", "dense", "dense" ], dimToLvl = affine_map<(d0, d1) -> (d0 floordiv 2, d1 floordiv 3, d0 mod 2, d1 mod 3)> }>>
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 floordiv 2 : compressed, d1 floordiv 3 : compressed, d0 mod 2 : dense, d1 mod 3 : dense) }>>
func.func private @BCSR_explicit(%arg0: tensor<?x?xf64, #BCSR_explicit>) {
return
}
Expand All @@ -190,7 +190,7 @@ func.func private @BCSR_explicit(%arg0: tensor<?x?xf64, #BCSR_explicit>) {
}>

// CHECK-LABEL: func private @NV_24(
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "dense", "compressed24" ], dimToLvl = affine_map<(d0, d1) -> (d0, d1 floordiv 4, d1 mod 4)> }>>
// CHECK-SAME: tensor<?x?xf64, #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 floordiv 4 : dense, d1 mod 4 : block2_4) }>>
func.func private @NV_24(%arg0: tensor<?x?xf64, #NV_24>) {
return
}
8 changes: 4 additions & 4 deletions mlir/test/Dialect/SparseTensor/sparse_reshape.mlir
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,7 @@
// CHECK-ROUND: return %[[E]] : tensor<10x10xf64, #sparse_tensor.encoding<{{{.*}}}>>
//
// CHECK-LABEL: func.func @sparse_expand(
// CHECK-SAME: %[[S:.*]]:
// CHECK-SAME: %[[S:[a-zA-Z0-9_]*]]:
yinying-lisa-li marked this conversation as resolved.
Show resolved Hide resolved
// CHECK-DAG: %[[C10:.*]] = arith.constant 10 : index
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
Expand Down Expand Up @@ -53,7 +53,7 @@ func.func @sparse_expand(%arg0: tensor<100xf64, #SparseVector>) -> tensor<10x10x
// CHECK-ROUND: return %[[C]] : tensor<100xf64, #sparse_tensor.encoding<{{{.*}}}>>
//
// CHECK-LABEL: func.func @sparse_collapse(
// CHECK-SAME: %[[S:.*]]:
// CHECK-SAME: %[[S:[a-zA-Z0-9_]*]]:
// CHECK-DAG: %[[C10:.*]] = arith.constant 10 : index
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
Expand Down Expand Up @@ -99,7 +99,7 @@ func.func @sparse_collapse(%arg0: tensor<10x10xf64, #SparseMatrix>) -> tensor<10
// CHECK-ROUND: return %[[E]] : tensor<?x10xf64, #sparse_tensor.encoding<{{{.*}}}>>
//
// CHECK-LABEL: func.func @dynamic_sparse_expand(
// CHECK-SAME: %[[S:.*]]:
// CHECK-SAME: %[[S:[a-zA-Z0-9_]*]]:
// CHECK-DAG: %[[C10:.*]] = arith.constant 10 : index
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
Expand Down Expand Up @@ -142,7 +142,7 @@ func.func @dynamic_sparse_expand(%arg0: tensor<?xf64, #SparseVector>) -> tensor<
// CHECK-ROUND: return %[[C]] : tensor<?xf64, #sparse_tensor.encoding<{{{.*}}}>>
//
// CHECK-LABEL: func.func @dynamic_sparse_collapse(
// CHECK-SAME: %[[S:.*]]:
// CHECK-SAME: %[[S:[a-zA-Z0-9_]*]]:
// CHECK-DAG: %[[C10:.*]] = arith.constant 10 : index
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
Expand Down
2 changes: 1 addition & 1 deletion mlir/test/Dialect/SparseTensor/sparse_tensor_reshape.mlir
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
#SparseMatrix = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed, d1 : compressed) }>

// CHECK: func.func @sparse_reshape(
// CHECK-SAME: %[[S:.*]]:
// CHECK-SAME: %[[S:[a-zA-Z0-9_]*]]:
// CHECK-DAG: %[[C25:.*]] = arith.constant 25 : index
// CHECK-DAG: %[[C10:.*]] = arith.constant 10 : index
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
Expand Down
Loading
Loading