[Mlir-commits] [mlir] d4088e7 - [mlir][sparse] Populate lvlToDim (#68937)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Tue Oct 17 13:09:46 PDT 2023
Author: Yinying Li
Date: 2023-10-17T16:09:39-04:00
New Revision: d4088e7d5f4849a4385a568b675d8c99c986d581
URL: https://github.com/llvm/llvm-project/commit/d4088e7d5f4849a4385a568b675d8c99c986d581
DIFF: https://github.com/llvm/llvm-project/commit/d4088e7d5f4849a4385a568b675d8c99c986d581.diff
LOG: [mlir][sparse] Populate lvlToDim (#68937)
Updates:
1. Infer lvlToDim from dimToLvl
2. Add more tests for block sparsity
3. Finish TODOs related to lvlToDim, including adding lvlToDim to python
binding
Verification of lvlToDim that user provides will be implemented in the
next PR.
Added:
Modified:
mlir/include/mlir-c/Dialect/SparseTensor.h
mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensor.h
mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
mlir/lib/Bindings/Python/DialectSparseTensor.cpp
mlir/lib/CAPI/Dialect/SparseTensor.cpp
mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
mlir/test/CAPI/sparse_tensor.c
mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir
mlir/test/Integration/Dialect/SparseTensor/python/test_SDDMM.py
mlir/test/Integration/Dialect/SparseTensor/python/test_SpMM.py
mlir/test/Integration/Dialect/SparseTensor/python/test_output.py
mlir/test/Integration/Dialect/SparseTensor/python/test_stress.py
mlir/test/python/dialects/sparse_tensor/dialect.py
Removed:
################################################################################
diff --git a/mlir/include/mlir-c/Dialect/SparseTensor.h b/mlir/include/mlir-c/Dialect/SparseTensor.h
index 7e47e54e7361d54..859a4f0dd9f52c8 100644
--- a/mlir/include/mlir-c/Dialect/SparseTensor.h
+++ b/mlir/include/mlir-c/Dialect/SparseTensor.h
@@ -51,11 +51,10 @@ MLIR_CAPI_EXPORTED bool
mlirAttributeIsASparseTensorEncodingAttr(MlirAttribute attr);
/// Creates a `sparse_tensor.encoding` attribute with the given parameters.
-/// TODO: add a version that supplied lvlToDim when it cannot be inferred
MLIR_CAPI_EXPORTED MlirAttribute mlirSparseTensorEncodingAttrGet(
MlirContext ctx, intptr_t lvlRank,
enum MlirSparseTensorDimLevelType const *lvlTypes, MlirAffineMap dimToLvl,
- int posWidth, int crdWidth);
+ MlirAffineMap lvlTodim, int posWidth, int crdWidth);
/// Returns the level-rank of the `sparse_tensor.encoding` attribute.
MLIR_CAPI_EXPORTED intptr_t
diff --git a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensor.h b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensor.h
index cbca0a7f8cc0e3a..6e834426b441764 100644
--- a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensor.h
+++ b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensor.h
@@ -160,6 +160,19 @@ inline bool hasAnySparseOperandOrResult(Operation *op) {
return hasAnySparseOperand(op) || hasAnySparseResult(op);
}
+//
+// Inference.
+//
+
+/// Given the dimToLvl map, infers the lvlToDim map, or returns
+/// empty Affine map when inference fails.
+AffineMap inferLvlToDim(AffineMap dimToLvl, MLIRContext *context);
+
+/// Returns the lvlToDim map for the given dimToLvl map specific
+/// to the block sparse cases.
+/// Asserts on failure (so only use when known to succeed).
+AffineMap inverseBlockSparsity(AffineMap dimToLvl, MLIRContext *context);
+
//
// Reordering.
//
diff --git a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
index 38c7200afb41ffc..47fd18a689d5a8d 100644
--- a/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
+++ b/mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td
@@ -307,6 +307,9 @@ def SparseTensorEncodingAttr : SparseTensor_Attr<"SparseTensorEncoding",
"AffineMap":$lvlToDim,
"unsigned":$posWidth,
"unsigned":$crdWidth), [{
+ if (!lvlToDim) {
+ lvlToDim = ::mlir::sparse_tensor::inferLvlToDim(dimToLvl, $_ctxt);
+ }
return $_get($_ctxt, lvlTypes, dimToLvl, lvlToDim, posWidth, crdWidth,
ArrayRef<::mlir::sparse_tensor::SparseTensorDimSliceAttr>{});
}]>
diff --git a/mlir/lib/Bindings/Python/DialectSparseTensor.cpp b/mlir/lib/Bindings/Python/DialectSparseTensor.cpp
index 8e9e0b6baf76c20..9bde3a443ecfeca 100644
--- a/mlir/lib/Bindings/Python/DialectSparseTensor.cpp
+++ b/mlir/lib/Bindings/Python/DialectSparseTensor.cpp
@@ -41,16 +41,17 @@ static void populateDialectSparseTensorSubmodule(const py::module &m) {
.def_classmethod(
"get",
[](py::object cls, std::vector<MlirSparseTensorDimLevelType> lvlTypes,
- std::optional<MlirAffineMap> dimToLvl, int posWidth, int crdWidth,
+ std::optional<MlirAffineMap> dimToLvl,
+ std::optional<MlirAffineMap> lvlToDim, int posWidth, int crdWidth,
MlirContext context) {
- // TODO: provide dimToLvl
return cls(mlirSparseTensorEncodingAttrGet(
context, lvlTypes.size(), lvlTypes.data(),
- dimToLvl ? *dimToLvl : MlirAffineMap{nullptr}, posWidth,
+ dimToLvl ? *dimToLvl : MlirAffineMap{nullptr},
+ lvlToDim ? *lvlToDim : MlirAffineMap{nullptr}, posWidth,
crdWidth));
},
py::arg("cls"), py::arg("lvl_types"), py::arg("dim_to_lvl"),
- py::arg("pos_width"), py::arg("crd_width"),
+ py::arg("lvl_to_dim"), py::arg("pos_width"), py::arg("crd_width"),
py::arg("context") = py::none(),
"Gets a sparse_tensor.encoding from parameters.")
.def_property_readonly(
@@ -71,6 +72,14 @@ static void populateDialectSparseTensorSubmodule(const py::module &m) {
return {};
return ret;
})
+ .def_property_readonly(
+ "lvl_to_dim",
+ [](MlirAttribute self) -> std::optional<MlirAffineMap> {
+ MlirAffineMap ret = mlirSparseTensorEncodingAttrGetLvlToDim(self);
+ if (mlirAffineMapIsNull(ret))
+ return {};
+ return ret;
+ })
.def_property_readonly("pos_width",
mlirSparseTensorEncodingAttrGetPosWidth)
.def_property_readonly("crd_width",
diff --git a/mlir/lib/CAPI/Dialect/SparseTensor.cpp b/mlir/lib/CAPI/Dialect/SparseTensor.cpp
index bf3a4ad5e7a1683..c3ad95527df489f 100644
--- a/mlir/lib/CAPI/Dialect/SparseTensor.cpp
+++ b/mlir/lib/CAPI/Dialect/SparseTensor.cpp
@@ -48,15 +48,14 @@ bool mlirAttributeIsASparseTensorEncodingAttr(MlirAttribute attr) {
MlirAttribute
mlirSparseTensorEncodingAttrGet(MlirContext ctx, intptr_t lvlRank,
MlirSparseTensorDimLevelType const *lvlTypes,
- MlirAffineMap dimToLvl, int posWidth,
- int crdWidth) {
+ MlirAffineMap dimToLvl, MlirAffineMap lvlToDim,
+ int posWidth, int crdWidth) {
SmallVector<DimLevelType> cppLvlTypes;
cppLvlTypes.reserve(lvlRank);
for (intptr_t l = 0; l < lvlRank; ++l)
cppLvlTypes.push_back(static_cast<DimLevelType>(lvlTypes[l]));
- mlir::AffineMap lvlToDim; // TODO: provide in API
return wrap(SparseTensorEncodingAttr::get(unwrap(ctx), cppLvlTypes,
- unwrap(dimToLvl), lvlToDim,
+ unwrap(dimToLvl), unwrap(lvlToDim),
posWidth, crdWidth));
}
diff --git a/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp b/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
index cd1e585438ddac9..fd87bbfa905ed69 100644
--- a/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
+++ b/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
@@ -293,9 +293,8 @@ Type SparseTensorEncodingAttr::getCrdType() const {
SparseTensorEncodingAttr
SparseTensorEncodingAttr::withDimToLvl(AffineMap dimToLvl) const {
assert(getImpl() && "Uninitialized SparseTensorEncodingAttr");
- // TODO: infer lvlToDim
return SparseTensorEncodingAttr::get(getContext(), getLvlTypes(), dimToLvl,
- /*lvlToDim*/ AffineMap(), getPosWidth(),
+ getLvlToDim(), getPosWidth(),
getCrdWidth());
}
@@ -583,7 +582,8 @@ Attribute SparseTensorEncodingAttr::parse(AsmParser &parser, Type type) {
#undef RETURN_ON_FAIL
// Construct struct-like storage for attribute.
- AffineMap lvlToDim; // TODO: infer
+ // TODO: Fetch lvlToDim if user provides one
+ AffineMap lvlToDim = inferLvlToDim(dimToLvl, parser.getContext());
return parser.getChecked<SparseTensorEncodingAttr>(
parser.getContext(), lvlTypes, dimToLvl, lvlToDim, posWidth, crdWidth,
dimSlices);
@@ -749,6 +749,75 @@ mlir::sparse_tensor::getSparseTensorEncoding(Type type) {
return nullptr;
}
+AffineMap mlir::sparse_tensor::inferLvlToDim(AffineMap dimToLvl,
+ MLIRContext *context) {
+ auto map = static_cast<AffineMap>(dimToLvl);
+ AffineMap lvlToDim;
+ // Return an empty lvlToDim when inference is not successful.
+ if (!map || map.getNumSymbols() != 0) {
+ lvlToDim = AffineMap();
+ } else if (map.isPermutation()) {
+ lvlToDim = inversePermutation(map);
+ } else {
+ // TODO: check if it's block sparsity
+ lvlToDim = inverseBlockSparsity(map, context);
+ }
+ return lvlToDim;
+}
+
+AffineMap mlir::sparse_tensor::inverseBlockSparsity(AffineMap dimToLvl,
+ MLIRContext *context) {
+ SmallVector<AffineExpr> lvlExprs;
+ auto numLvls = dimToLvl.getNumResults();
+ lvlExprs.reserve(numLvls);
+ // lvlExprComponents stores information of the floordiv and mod operations
+ // applied to the same dimension, so as to build the lvlToDim map.
+ std::map<unsigned, SmallVector<AffineExpr, 3>> lvlExprComponents;
+ for (unsigned i = 0, n = numLvls; i < n; i++) {
+ auto result = dimToLvl.getResult(i);
+ if (auto binOp = result.dyn_cast<AffineBinaryOpExpr>()) {
+ if (result.getKind() == AffineExprKind::FloorDiv) {
+ // Position of the dimension in dimToLvl.
+ auto pos = binOp.getLHS().dyn_cast<AffineDimExpr>().getPosition();
+ assert(lvlExprComponents.find(pos) == lvlExprComponents.end() &&
+ "expected only one floordiv for each dimension");
+ SmallVector<AffineExpr, 3> components;
+ // Level variable for floordiv.
+ components.push_back(getAffineDimExpr(i, context));
+ // Multiplier.
+ components.push_back(binOp.getRHS());
+ // Map key is the position of the dimension.
+ lvlExprComponents[pos] = components;
+ } else if (result.getKind() == AffineExprKind::Mod) {
+ auto pos = binOp.getLHS().dyn_cast<AffineDimExpr>().getPosition();
+ assert(lvlExprComponents.find(pos) != lvlExprComponents.end() &&
+ "expected floordiv before mod");
+ // Add level variable for mod to the same vector
+ // of the corresponding floordiv.
+ lvlExprComponents[pos].push_back(getAffineDimExpr(i, context));
+ } else {
+ assert(false && "expected floordiv or mod");
+ }
+ } else {
+ lvlExprs.push_back(getAffineDimExpr(i, context));
+ }
+ }
+ // Build lvlExprs from lvlExprComponents.
+ // For example, for il = i floordiv 2 and ii = i mod 2, the components
+ // would be [il, 2, ii]. It could be used to build the AffineExpr
+ // i = il * 2 + ii in lvlToDim.
+ for (auto &components : lvlExprComponents) {
+ assert(components.second.size() == 3 &&
+ "expected 3 components to build lvlExprs");
+ auto mulOp = getAffineBinaryOpExpr(
+ AffineExprKind::Mul, components.second[0], components.second[1]);
+ auto addOp =
+ getAffineBinaryOpExpr(AffineExprKind::Add, mulOp, components.second[2]);
+ lvlExprs.push_back(addOp);
+ }
+ return dimToLvl.get(dimToLvl.getNumResults(), 0, lvlExprs, context);
+}
+
bool mlir::sparse_tensor::isCOOType(SparseTensorEncodingAttr enc,
Level startLvl, bool isUnique) {
if (!enc ||
@@ -811,7 +880,7 @@ RankedTensorType sparse_tensor::getCOOFromTypeWithOrdering(RankedTensorType rtt,
// default value.
unsigned posWidth = src.getPosWidth();
unsigned crdWidth = src.getCrdWidth();
- AffineMap invPerm; // TODO
+ AffineMap invPerm = src.getLvlToDim();
auto enc = SparseTensorEncodingAttr::get(src.getContext(), lvlTypes, lvlPerm,
invPerm, posWidth, crdWidth);
return RankedTensorType::get(src.getDimShape(), src.getElementType(), enc);
diff --git a/mlir/test/CAPI/sparse_tensor.c b/mlir/test/CAPI/sparse_tensor.c
index 33ee8e784096a18..3bd1508cf299a3d 100644
--- a/mlir/test/CAPI/sparse_tensor.c
+++ b/mlir/test/CAPI/sparse_tensor.c
@@ -40,6 +40,8 @@ static int testRoundtripEncoding(MlirContext ctx) {
// CHECK: level_type: 4
// CHECK: level_type: 8
// CHECK: level_type: 8
+ MlirAffineMap lvlToDim =
+ mlirSparseTensorEncodingAttrGetLvlToDim(originalAttr);
int lvlRank = mlirSparseTensorEncodingGetLvlRank(originalAttr);
enum MlirSparseTensorDimLevelType *lvlTypes =
malloc(sizeof(enum MlirSparseTensorDimLevelType) * lvlRank);
@@ -53,9 +55,8 @@ static int testRoundtripEncoding(MlirContext ctx) {
// CHECK: crdWidth: 64
int crdWidth = mlirSparseTensorEncodingAttrGetCrdWidth(originalAttr);
fprintf(stderr, "crdWidth: %d\n", crdWidth);
- // TODO: lvlToDim
MlirAttribute newAttr = mlirSparseTensorEncodingAttrGet(
- ctx, lvlRank, lvlTypes, dimToLvl, posWidth, crdWidth);
+ ctx, lvlRank, lvlTypes, dimToLvl, lvlToDim, posWidth, crdWidth);
mlirAttributeDump(newAttr); // For debugging filecheck output.
// CHECK: equal: 1
fprintf(stderr, "equal: %d\n", mlirAttributeEqual(originalAttr, newAttr));
diff --git a/mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir b/mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir
index ae3805d8b774176..ea8217ab6e3f233 100644
--- a/mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir
+++ b/mlir/test/Dialect/SparseTensor/roundtrip_encoding.mlir
@@ -160,6 +160,24 @@ func.func private @BSR(%arg0: tensor<?x?xf64, #BSR>) {
// -----
+#BCSR = #sparse_tensor.encoding<{
+ map = ( i, j, k ) ->
+ ( i floordiv 2 : dense,
+ j floordiv 3 : dense,
+ k floordiv 4 : compressed,
+ i mod 2 : dense,
+ j mod 3 : dense,
+ k 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) }>>
+func.func private @BCSR(%arg0: tensor<?x?x?xf64, #BCSR>) {
+ return
+}
+// -----
+
#BSR_explicit = #sparse_tensor.encoding<{
map =
{il, jl, ii, jj}
@@ -194,3 +212,37 @@ func.func private @BSR_explicit(%arg0: tensor<?x?xf64, #BSR_explicit>) {
func.func private @NV_24(%arg0: tensor<?x?xf64, #NV_24>) {
return
}
+
+// -----
+
+#NV_24 = #sparse_tensor.encoding<{
+ map = ( i, j, k ) ->
+ ( i : dense,
+ j : dense,
+ k floordiv 4 : dense,
+ k 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) }>>
+func.func private @NV_24(%arg0: tensor<?x?x?xf64, #NV_24>) {
+ return
+}
+
+// -----
+
+#NV_24 = #sparse_tensor.encoding<{
+ map = ( i, j, k ) ->
+ ( i : dense,
+ k floordiv 4 : dense,
+ j : dense,
+ k 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) }>>
+func.func private @NV_24(%arg0: tensor<?x?x?xf64, #NV_24>) {
+ return
+}
\ No newline at end of file
diff --git a/mlir/test/Integration/Dialect/SparseTensor/python/test_SDDMM.py b/mlir/test/Integration/Dialect/SparseTensor/python/test_SDDMM.py
index 0cdc7c88bd97fb8..1f9b6360383180c 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/python/test_SDDMM.py
+++ b/mlir/test/Integration/Dialect/SparseTensor/python/test_SDDMM.py
@@ -155,7 +155,7 @@ def main():
for iwidth in [32]:
for e in [True]:
attr = st.EncodingAttr.get(
- level, ordering, pwidth, iwidth
+ level, ordering, None, pwidth, iwidth
)
opt = f"parallelization-strategy=none"
compiler = sparse_compiler.SparseCompiler(
diff --git a/mlir/test/Integration/Dialect/SparseTensor/python/test_SpMM.py b/mlir/test/Integration/Dialect/SparseTensor/python/test_SpMM.py
index 01d74a4dc82fa1d..69f6cdcea967fae 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/python/test_SpMM.py
+++ b/mlir/test/Integration/Dialect/SparseTensor/python/test_SpMM.py
@@ -145,7 +145,7 @@ def main():
for pwidth in bitwidths:
for iwidth in bitwidths:
attr = st.EncodingAttr.get(
- level, ordering, pwidth, iwidth
+ level, ordering, None, pwidth, iwidth
)
build_compile_and_run_SpMM(attr, compiler)
count = count + 1
diff --git a/mlir/test/Integration/Dialect/SparseTensor/python/test_output.py b/mlir/test/Integration/Dialect/SparseTensor/python/test_output.py
index 8f3f4e5af1e58ef..7d7749008020515 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/python/test_output.py
+++ b/mlir/test/Integration/Dialect/SparseTensor/python/test_output.py
@@ -91,7 +91,7 @@ def main():
for level in levels:
for ordering in orderings:
for bwidth in bitwidths:
- attr = st.EncodingAttr.get(level, ordering, bwidth, bwidth)
+ attr = st.EncodingAttr.get(level, ordering, None, bwidth, bwidth)
build_compile_and_run_output(attr, compiler)
count = count + 1
diff --git a/mlir/test/Integration/Dialect/SparseTensor/python/test_stress.py b/mlir/test/Integration/Dialect/SparseTensor/python/test_stress.py
index ef266672ce42afc..841b02bc10c8bec 100644
--- a/mlir/test/Integration/Dialect/SparseTensor/python/test_stress.py
+++ b/mlir/test/Integration/Dialect/SparseTensor/python/test_stress.py
@@ -227,7 +227,7 @@ def main():
for pwidth in bitwidths:
for iwidth in bitwidths:
attr = st.EncodingAttr.get(
- level, ordering, pwidth, iwidth
+ level, ordering, None, pwidth, iwidth
)
types.append(ir.RankedTensorType.get(shape, f64, attr))
#
diff --git a/mlir/test/python/dialects/sparse_tensor/dialect.py b/mlir/test/python/dialects/sparse_tensor/dialect.py
index d80b878323377a4..240db6ebd1d1eb3 100644
--- a/mlir/test/python/dialects/sparse_tensor/dialect.py
+++ b/mlir/test/python/dialects/sparse_tensor/dialect.py
@@ -32,12 +32,14 @@ def testEncodingAttr1D():
print(f"lvl_types: {casted.lvl_types}")
# CHECK: dim_to_lvl: None
print(f"dim_to_lvl: {casted.dim_to_lvl}")
+ # CHECK: lvl_to_dim: None
+ print(f"lvl_to_dim: {casted.lvl_to_dim}")
# CHECK: pos_width: 16
print(f"pos_width: {casted.pos_width}")
# CHECK: crd_width: 32
print(f"crd_width: {casted.crd_width}")
- created = st.EncodingAttr.get(casted.lvl_types, None, 0, 0)
+ created = st.EncodingAttr.get(casted.lvl_types, None, None, 0, 0)
# CHECK: #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }>
print(created)
# CHECK: created_equal: False
@@ -72,12 +74,20 @@ def testEncodingAttr2D():
print(f"lvl_types: {casted.lvl_types}")
# CHECK: dim_to_lvl: (d0, d1) -> (d1, d0)
print(f"dim_to_lvl: {casted.dim_to_lvl}")
+ # CHECK: lvl_to_dim: (d0, d1) -> (d1, d0)
+ print(f"lvl_to_dim: {casted.lvl_to_dim}")
# CHECK: pos_width: 8
print(f"pos_width: {casted.pos_width}")
# CHECK: crd_width: 32
print(f"crd_width: {casted.crd_width}")
- created = st.EncodingAttr.get(casted.lvl_types, casted.dim_to_lvl, 8, 32)
+ created = st.EncodingAttr.get(
+ casted.lvl_types,
+ casted.dim_to_lvl,
+ casted.lvl_to_dim,
+ 8,
+ 32,
+ )
# CHECK: #sparse_tensor.encoding<{ map = (d0, d1) -> (d1 : dense, d0 : compressed), posWidth = 8, crdWidth = 32 }>
print(created)
# CHECK: created_equal: True
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