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[mlir][sparse] Renaming the STEA field dimLevelType to lvlTypes
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This commit is part of the migration of towards the new STEA syntax/design.  In particular, this commit includes the following changes:
* Renaming compiler-internal functions/methods:
  * `SparseTensorEncodingAttr::{getDimLevelType => getLvlTypes}`
  * `Merger::{getDimLevelType => getLvlType}` (for consistency)
  * `sparse_tensor::{getDimLevelType => buildLevelType}` (to help reduce confusion vs actual getter methods)
* Renaming external facets to match:
  * the STEA parser and printer
  * the C and Python bindings
  * PyTACO

However, the actual renaming of the `DimLevelType` itself (along with all the "dlt" names) will be handled in a separate commit.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D150330
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@wrengr
wrengr committed May 17, 2023
1 parent 4dc205f commit a0615d0
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Showing 172 changed files with 1,229 additions and 1,240 deletions.
4 changes: 2 additions & 2 deletions mlir/include/mlir-c/Dialect/SparseTensor.h
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Original file line number Diff line number Diff line change
Expand Up @@ -52,7 +52,7 @@ mlirAttributeIsASparseTensorEncodingAttr(MlirAttribute attr);
/// Creates a `sparse_tensor.encoding` attribute with the given parameters.
MLIR_CAPI_EXPORTED MlirAttribute mlirSparseTensorEncodingAttrGet(
MlirContext ctx, intptr_t lvlRank,
enum MlirSparseTensorDimLevelType const *dimLevelTypes,
enum MlirSparseTensorDimLevelType const *lvlTypes,
MlirAffineMap dimOrdering, MlirAffineMap higherOrdering, int posWidth,
int crdWidth);

Expand All @@ -62,7 +62,7 @@ mlirSparseTensorEncodingGetLvlRank(MlirAttribute attr);

/// Returns a specified level-type of the `sparse_tensor.encoding` attribute.
MLIR_CAPI_EXPORTED enum MlirSparseTensorDimLevelType
mlirSparseTensorEncodingAttrGetDimLevelType(MlirAttribute attr, intptr_t lvl);
mlirSparseTensorEncodingAttrGetLvlType(MlirAttribute attr, intptr_t lvl);

/// Returns the dimension-ordering of the `sparse_tensor.encoding` attribute.
MLIR_CAPI_EXPORTED MlirAffineMap
Expand Down
28 changes: 14 additions & 14 deletions mlir/include/mlir/Dialect/SparseTensor/IR/Enums.h
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Original file line number Diff line number Diff line change
Expand Up @@ -300,7 +300,7 @@ constexpr std::optional<LevelFormat> getLevelFormat(DimLevelType dlt) {
/// TODO: factor out a new LevelProperties type so we can add new properties
/// without changing this function's signature
constexpr std::optional<DimLevelType>
getDimLevelType(LevelFormat lf, bool ordered, bool unique) {
buildLevelType(LevelFormat lf, bool ordered, bool unique) {
auto dlt = static_cast<DimLevelType>(static_cast<uint8_t>(lf) |
(ordered ? 0 : 2) | (unique ? 0 : 1));
return isValidDLT(dlt) ? std::optional(dlt) : std::nullopt;
Expand All @@ -321,27 +321,27 @@ static_assert(
"getLevelFormat conversion is broken");

static_assert(
(getDimLevelType(LevelFormat::Dense, false, true) == std::nullopt &&
getDimLevelType(LevelFormat::Dense, true, false) == std::nullopt &&
getDimLevelType(LevelFormat::Dense, false, false) == std::nullopt &&
*getDimLevelType(LevelFormat::Dense, true, true) == DimLevelType::Dense &&
*getDimLevelType(LevelFormat::Compressed, true, true) ==
(buildLevelType(LevelFormat::Dense, false, true) == std::nullopt &&
buildLevelType(LevelFormat::Dense, true, false) == std::nullopt &&
buildLevelType(LevelFormat::Dense, false, false) == std::nullopt &&
*buildLevelType(LevelFormat::Dense, true, true) == DimLevelType::Dense &&
*buildLevelType(LevelFormat::Compressed, true, true) ==
DimLevelType::Compressed &&
*getDimLevelType(LevelFormat::Compressed, true, false) ==
*buildLevelType(LevelFormat::Compressed, true, false) ==
DimLevelType::CompressedNu &&
*getDimLevelType(LevelFormat::Compressed, false, true) ==
*buildLevelType(LevelFormat::Compressed, false, true) ==
DimLevelType::CompressedNo &&
*getDimLevelType(LevelFormat::Compressed, false, false) ==
*buildLevelType(LevelFormat::Compressed, false, false) ==
DimLevelType::CompressedNuNo &&
*getDimLevelType(LevelFormat::Singleton, true, true) ==
*buildLevelType(LevelFormat::Singleton, true, true) ==
DimLevelType::Singleton &&
*getDimLevelType(LevelFormat::Singleton, true, false) ==
*buildLevelType(LevelFormat::Singleton, true, false) ==
DimLevelType::SingletonNu &&
*getDimLevelType(LevelFormat::Singleton, false, true) ==
*buildLevelType(LevelFormat::Singleton, false, true) ==
DimLevelType::SingletonNo &&
*getDimLevelType(LevelFormat::Singleton, false, false) ==
*buildLevelType(LevelFormat::Singleton, false, false) ==
DimLevelType::SingletonNuNo),
"getDimLevelType conversion is broken");
"buildLevelType conversion is broken");

// Ensure the above predicates work as intended.
static_assert((isValidDLT(DimLevelType::Undef) &&
Expand Down
6 changes: 3 additions & 3 deletions mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
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Original file line number Diff line number Diff line change
Expand Up @@ -266,7 +266,7 @@ def SparseTensorEncodingAttr : SparseTensor_Attr<"SparseTensorEncoding",
ArrayRefParameter<
"::mlir::sparse_tensor::DimLevelType",
"level-types"
>: $dimLevelType,
>: $lvlTypes,
// A permutation from (higher-ordering)-coordinates to level-coordinates.
"AffineMap":$dimOrdering,
// A mapping from dimension-coordinates to (higher-ordering)-coordinates.
Expand All @@ -283,12 +283,12 @@ def SparseTensorEncodingAttr : SparseTensor_Attr<"SparseTensorEncoding",
);

let builders = [
AttrBuilder<(ins "ArrayRef<::mlir::sparse_tensor::DimLevelType>":$dimLevelType,
AttrBuilder<(ins "ArrayRef<::mlir::sparse_tensor::DimLevelType>":$lvlTypes,
"AffineMap":$dimOrdering,
"AffineMap":$higherOrdering,
"unsigned":$posWidth,
"unsigned":$crdWidth), [{
return $_get($_ctxt, dimLevelType,
return $_get($_ctxt, lvlTypes,
dimOrdering,
higherOrdering,
posWidth,
Expand Down
8 changes: 4 additions & 4 deletions mlir/include/mlir/Dialect/SparseTensor/Utils/Merger.h
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Original file line number Diff line number Diff line change
Expand Up @@ -377,14 +377,14 @@ class Merger {
bool hasSparseIdxReduction(const BitVector &bits) const;

/// Gets the level-type of the `t`th tensor on `i`th loop.
DimLevelType getDimLevelType(TensorId t, LoopId i) const {
DimLevelType getLvlType(TensorId t, LoopId i) const {
assert(isValidTensorId(t) && isValidLoopId(i));
return lvlTypes[t][i];
}

/// Gets the level-type of the TensorLoopId.
DimLevelType getDimLevelType(TensorLoopId b) const {
return getDimLevelType(tensor(b), loop(b));
DimLevelType getLvlType(TensorLoopId b) const {
return getLvlType(tensor(b), loop(b));
}

/// Gets the loop identifier for the `lvl`th level of the `t`th tensor.
Expand Down Expand Up @@ -434,7 +434,7 @@ class Merger {
for (const TensorLoopId b : bits.set_bits()) {
const TensorId t = tensor(b);
const auto optLvl = getLvl(b);
const auto lvlTp = getDimLevelType(b);
const auto lvlTp = getLvlType(b);
if (isLvlWithNonTrivialIdxExp(b)) {
// This must be an undefined level.
assert(!optLvl.has_value());
Expand Down
12 changes: 5 additions & 7 deletions mlir/lib/Bindings/Python/DialectSparseTensor.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -39,30 +39,28 @@ static void populateDialectSparseTensorSubmodule(const py::module &m) {
mlirAttributeIsASparseTensorEncodingAttr)
.def_classmethod(
"get",
[](py::object cls,
std::vector<MlirSparseTensorDimLevelType> dimLevelTypes,
[](py::object cls, std::vector<MlirSparseTensorDimLevelType> lvlTypes,
std::optional<MlirAffineMap> dimOrdering,
std::optional<MlirAffineMap> higherOrdering, int posWidth,
int crdWidth, MlirContext context) {
return cls(mlirSparseTensorEncodingAttrGet(
context, dimLevelTypes.size(), dimLevelTypes.data(),
context, lvlTypes.size(), lvlTypes.data(),
dimOrdering ? *dimOrdering : MlirAffineMap{nullptr},
higherOrdering ? *higherOrdering : MlirAffineMap{nullptr},
posWidth, crdWidth));
},
py::arg("cls"), py::arg("dim_level_types"), py::arg("dim_ordering"),
py::arg("cls"), py::arg("lvl_types"), py::arg("dim_ordering"),
py::arg("higher_ordering"), py::arg("pos_width"),
py::arg("crd_width"), py::arg("context") = py::none(),
"Gets a sparse_tensor.encoding from parameters.")
.def_property_readonly(
"dim_level_types",
"lvl_types",
[](MlirAttribute self) {
const int lvlRank = mlirSparseTensorEncodingGetLvlRank(self);
std::vector<MlirSparseTensorDimLevelType> ret;
ret.reserve(lvlRank);
for (int l = 0; l < lvlRank; ++l)
ret.push_back(
mlirSparseTensorEncodingAttrGetDimLevelType(self, l));
ret.push_back(mlirSparseTensorEncodingAttrGetLvlType(self, l));
return ret;
})
.def_property_readonly(
Expand Down
17 changes: 8 additions & 9 deletions mlir/lib/CAPI/Dialect/SparseTensor.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -47,16 +47,15 @@ bool mlirAttributeIsASparseTensorEncodingAttr(MlirAttribute attr) {

MlirAttribute mlirSparseTensorEncodingAttrGet(
MlirContext ctx, intptr_t lvlRank,
MlirSparseTensorDimLevelType const *dimLevelTypes,
MlirAffineMap dimOrdering, MlirAffineMap higherOrdering, int posWidth,
int crdWidth) {
SmallVector<DimLevelType> cppDimLevelTypes;
cppDimLevelTypes.reserve(lvlRank);
MlirSparseTensorDimLevelType const *lvlTypes, MlirAffineMap dimOrdering,
MlirAffineMap higherOrdering, int posWidth, int crdWidth) {
SmallVector<DimLevelType> cppLvlTypes;
cppLvlTypes.reserve(lvlRank);
for (intptr_t l = 0; l < lvlRank; ++l)
cppDimLevelTypes.push_back(static_cast<DimLevelType>(dimLevelTypes[l]));
cppLvlTypes.push_back(static_cast<DimLevelType>(lvlTypes[l]));
return wrap(SparseTensorEncodingAttr::get(
unwrap(ctx), cppDimLevelTypes, unwrap(dimOrdering),
unwrap(higherOrdering), posWidth, crdWidth));
unwrap(ctx), cppLvlTypes, unwrap(dimOrdering), unwrap(higherOrdering),
posWidth, crdWidth));
}

MlirAffineMap mlirSparseTensorEncodingAttrGetDimOrdering(MlirAttribute attr) {
Expand All @@ -73,7 +72,7 @@ intptr_t mlirSparseTensorEncodingGetLvlRank(MlirAttribute attr) {
}

MlirSparseTensorDimLevelType
mlirSparseTensorEncodingAttrGetDimLevelType(MlirAttribute attr, intptr_t lvl) {
mlirSparseTensorEncodingAttrGetLvlType(MlirAttribute attr, intptr_t lvl) {
return static_cast<MlirSparseTensorDimLevelType>(
cast<SparseTensorEncodingAttr>(unwrap(attr)).getLvlType(lvl));
}
Expand Down
48 changes: 23 additions & 25 deletions mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -130,23 +130,22 @@ Type SparseTensorEncodingAttr::getCrdType() const {
}

SparseTensorEncodingAttr SparseTensorEncodingAttr::withoutOrdering() const {
return SparseTensorEncodingAttr::get(getContext(), getDimLevelType(),
AffineMap(), AffineMap(), getPosWidth(),
return SparseTensorEncodingAttr::get(getContext(), getLvlTypes(), AffineMap(),
AffineMap(), getPosWidth(),
getCrdWidth());
}

SparseTensorEncodingAttr SparseTensorEncodingAttr::withoutBitWidths() const {
return SparseTensorEncodingAttr::get(getContext(), getDimLevelType(),
getDimOrdering(), getHigherOrdering(), 0,
0);
return SparseTensorEncodingAttr::get(
getContext(), getLvlTypes(), getDimOrdering(), getHigherOrdering(), 0, 0);
}

bool SparseTensorEncodingAttr::isAllDense() const {
return !getImpl() || llvm::all_of(getDimLevelType(), isDenseDLT);
return !getImpl() || llvm::all_of(getLvlTypes(), isDenseDLT);
}

bool SparseTensorEncodingAttr::isAllOrdered() const {
return !getImpl() || llvm::all_of(getDimLevelType(), isOrderedDLT);
return !getImpl() || llvm::all_of(getLvlTypes(), isOrderedDLT);
}

bool SparseTensorEncodingAttr::hasIdDimOrdering() const {
Expand All @@ -155,14 +154,14 @@ bool SparseTensorEncodingAttr::hasIdDimOrdering() const {

Level SparseTensorEncodingAttr::getLvlRank() const {
assert(getImpl() && "Uninitialized SparseTensorEncodingAttr");
return getDimLevelType().size();
return getLvlTypes().size();
}

DimLevelType SparseTensorEncodingAttr::getLvlType(Level l) const {
if (!getImpl())
return DimLevelType::Dense;
assert(l < getLvlRank() && "Level is out of bounds");
return getDimLevelType()[l];
return getLvlTypes()[l];
}

std::optional<uint64_t>
Expand Down Expand Up @@ -243,9 +242,8 @@ Attribute SparseTensorEncodingAttr::parse(AsmParser &parser, Type type) {

StringRef attrName;
// Exactly 6 keys.
SmallVector<StringRef, 6> keys = {"dimLevelType", "dimOrdering",
"higherOrdering", "posWidth",
"crdWidth", "slice"};
SmallVector<StringRef, 6> keys = {"lvlTypes", "dimOrdering", "higherOrdering",
"posWidth", "crdWidth", "slice"};
while (succeeded(parser.parseOptionalKeyword(&attrName))) {
if (!llvm::is_contained(keys, attrName)) {
parser.emitError(parser.getNameLoc(), "unexpected key: ") << attrName;
Expand All @@ -258,7 +256,7 @@ Attribute SparseTensorEncodingAttr::parse(AsmParser &parser, Type type) {
// cost of the `is_contained` check above. Should instead use some
// "find" function that returns the index into `keys` so that we can
// dispatch on that instead.
if (attrName == "dimLevelType") {
if (attrName == "lvlTypes") {
Attribute attr;
RETURN_ON_FAIL(parser.parseAttribute(attr));
auto arrayAttr = llvm::dyn_cast<ArrayAttr>(attr);
Expand Down Expand Up @@ -336,8 +334,8 @@ Attribute SparseTensorEncodingAttr::parse(AsmParser &parser, Type type) {

void SparseTensorEncodingAttr::print(AsmPrinter &printer) const {
// Print the struct-like storage in dictionary fashion.
printer << "<{ dimLevelType = [ ";
llvm::interleaveComma(getDimLevelType(), printer, [&](DimLevelType dlt) {
printer << "<{ lvlTypes = [ ";
llvm::interleaveComma(getLvlTypes(), printer, [&](DimLevelType dlt) {
printer << "\"" << toMLIRString(dlt) << "\"";
});
printer << " ]";
Expand Down Expand Up @@ -366,7 +364,7 @@ void SparseTensorEncodingAttr::print(AsmPrinter &printer) const {

LogicalResult SparseTensorEncodingAttr::verify(
function_ref<InFlightDiagnostic()> emitError,
ArrayRef<DimLevelType> dimLevelType, AffineMap dimOrdering,
ArrayRef<DimLevelType> lvlTypes, AffineMap dimOrdering,
AffineMap higherOrdering, unsigned posWidth, unsigned crdWidth,
ArrayRef<SparseTensorDimSliceAttr> dimSlices) {
if (!acceptBitWidth(posWidth))
Expand All @@ -378,7 +376,7 @@ LogicalResult SparseTensorEncodingAttr::verify(
// the `getLvlRank` method is the length of the level-types array,
// since it must always be provided and have full rank; therefore we
// use that same source-of-truth here.
const Level lvlRank = dimLevelType.size();
const Level lvlRank = lvlTypes.size();
if (lvlRank == 0)
return emitError() << "expected a non-empty array for level types";
if (dimOrdering) {
Expand Down Expand Up @@ -415,9 +413,9 @@ LogicalResult SparseTensorEncodingAttr::verifyEncoding(
function_ref<InFlightDiagnostic()> emitError) const {
// Check structural integrity. In particular, this ensures that the
// level-rank is coherent across all the fields.
RETURN_FAILURE_IF_FAILED(verify(emitError, getDimLevelType(),
getDimOrdering(), getHigherOrdering(),
getPosWidth(), getCrdWidth(), getDimSlices()))
RETURN_FAILURE_IF_FAILED(verify(emitError, getLvlTypes(), getDimOrdering(),
getHigherOrdering(), getPosWidth(),
getCrdWidth(), getDimSlices()))
// Check integrity with tensor type specifics. In particular, we
// need only check that the dimension-rank of the tensor agrees with
// the dimension-rank of the encoding.
Expand Down Expand Up @@ -496,14 +494,14 @@ RankedTensorType sparse_tensor::getCOOFromTypeWithOrdering(RankedTensorType rtt,
// An unordered and non-unique compressed level at beginning.
// If this is also the last level, then it is unique.
lvlTypes.push_back(
*getDimLevelType(LevelFormat::Compressed, ordered, lvlRank == 1));
*buildLevelType(LevelFormat::Compressed, ordered, lvlRank == 1));
if (lvlRank > 1) {
// TODO: it is actually ordered at the level for ordered input.
// Followed by unordered non-unique n-2 singleton levels.
std::fill_n(std::back_inserter(lvlTypes), lvlRank - 2,
*getDimLevelType(LevelFormat::Singleton, ordered, false));
*buildLevelType(LevelFormat::Singleton, ordered, false));
// Ends by a unique singleton level unless the lvlRank is 1.
lvlTypes.push_back(*getDimLevelType(LevelFormat::Singleton, ordered, true));
lvlTypes.push_back(*buildLevelType(LevelFormat::Singleton, ordered, true));
}

// TODO: Maybe pick the bitwidth based on input/output tensors (probably the
Expand Down Expand Up @@ -580,8 +578,8 @@ Level mlir::sparse_tensor::toStoredDim(RankedTensorType type, Dimension d) {
static SparseTensorEncodingAttr
getNormalizedEncodingForSpecifier(SparseTensorEncodingAttr enc) {
SmallVector<DimLevelType> dlts;
for (auto dlt : enc.getDimLevelType())
dlts.push_back(*getDimLevelType(*getLevelFormat(dlt), true, true));
for (auto dlt : enc.getLvlTypes())
dlts.push_back(*buildLevelType(*getLevelFormat(dlt), true, true));

return SparseTensorEncodingAttr::get(
enc.getContext(), dlts,
Expand Down
6 changes: 2 additions & 4 deletions mlir/lib/Dialect/SparseTensor/Transforms/CodegenEnv.h
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Original file line number Diff line number Diff line change
Expand Up @@ -79,11 +79,9 @@ class CodegenEnv {
const LatPoint &lat(LatPointId l) const { return latticeMerger.lat(l); }
ArrayRef<LatPointId> set(LatSetId s) const { return latticeMerger.set(s); }
DimLevelType dlt(TensorId t, LoopId i) const {
return latticeMerger.getDimLevelType(t, i);
}
DimLevelType dlt(TensorLoopId b) const {
return latticeMerger.getDimLevelType(b);
return latticeMerger.getLvlType(t, i);
}
DimLevelType dlt(TensorLoopId b) const { return latticeMerger.getLvlType(b); }

//
// LoopEmitter delegates.
Expand Down
2 changes: 1 addition & 1 deletion mlir/lib/Dialect/SparseTensor/Transforms/LoopEmitter.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -288,7 +288,7 @@ void LoopEmitter::initialize(ValueRange ts, StringAttr loopTag, bool hasOutput,
if (stt.hasEncoding() && !(isOutputTensor(tid) && isSparseOut)) {
const auto enc = stt.getEncoding();
isSparseSlices[tid] = enc.isSlice();
for (auto lvlTp : enc.getDimLevelType())
for (auto lvlTp : enc.getLvlTypes())
lvlTypes[tid].push_back(lvlTp);
} else {
lvlTypes[tid].assign(lvlRank, DimLevelType::Dense);
Expand Down
2 changes: 1 addition & 1 deletion mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorCodegen.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -1159,7 +1159,7 @@ class SparseExtractSliceConverter
// TODO: We should check these in ExtractSliceOp::verify.
if (!srcEnc || !dstEnc || !dstEnc.isSlice())
return failure();
assert(srcEnc.getDimLevelType() == dstEnc.getDimLevelType());
assert(srcEnc.getLvlTypes() == dstEnc.getLvlTypes());
assert(srcEnc.getDimOrdering() == dstEnc.getDimOrdering());
assert(srcEnc.getHigherOrdering() == dstEnc.getHigherOrdering());
assert(srcEnc.getPosWidth() == dstEnc.getPosWidth());
Expand Down
10 changes: 5 additions & 5 deletions mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorConversion.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -205,7 +205,7 @@ static Value genLvlTypesBuffer(OpBuilder &builder, Location loc,
SparseTensorType stt) {
SmallVector<Value> lvlTypes;
lvlTypes.reserve(stt.getLvlRank());
for (const auto dlt : stt.getEncoding().getDimLevelType())
for (const auto dlt : stt.getEncoding().getLvlTypes())
lvlTypes.push_back(constantDimLevelTypeEncoding(builder, loc, dlt));
return allocaBuffer(builder, loc, lvlTypes);
}
Expand Down Expand Up @@ -565,7 +565,7 @@ static void genSparseCOOIterationLoop(
rewriter.setInsertionPointToStart(after);

const bool hasDenseDim =
llvm::any_of(stt.getEncoding().getDimLevelType(), isDenseDLT);
llvm::any_of(stt.getEncoding().getLvlTypes(), isDenseDLT);
if (hasDenseDim) {
Value elemV = rewriter.create<memref::LoadOp>(loc, elemPtr);
Value isZero = genIsNonzero(rewriter, loc, elemV);
Expand Down Expand Up @@ -880,11 +880,11 @@ class SparseTensorConvertConverter : public OpConversionPattern<ConvertOp> {
break;
case SparseToSparseConversionStrategy::kDirect:
useDirectConversion = true;
assert(canUseDirectConversion(dstEnc.getDimLevelType()) &&
assert(canUseDirectConversion(dstEnc.getLvlTypes()) &&
"Unsupported target for direct sparse-to-sparse conversion");
break;
case SparseToSparseConversionStrategy::kAuto:
useDirectConversion = canUseDirectConversion(dstEnc.getDimLevelType());
useDirectConversion = canUseDirectConversion(dstEnc.getLvlTypes());
break;
}
if (useDirectConversion) {
Expand All @@ -896,7 +896,7 @@ class SparseTensorConvertConverter : public OpConversionPattern<ConvertOp> {
// method calls can share most parameters, while still providing
// the correct sparsity information to either of them.
const auto mixedEnc = SparseTensorEncodingAttr::get(
op->getContext(), dstEnc.getDimLevelType(), dstEnc.getDimOrdering(),
op->getContext(), dstEnc.getLvlTypes(), dstEnc.getDimOrdering(),
dstEnc.getHigherOrdering(), srcEnc.getPosWidth(),
srcEnc.getCrdWidth());
// TODO: This is the only place where `kToCOO` (or `kToIterator`)
Expand Down
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