1 | //===- DialectSparseTensor.cpp - 'sparse_tensor' dialect submodule --------===// |
2 | // |
3 | // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
4 | // See https://llvm.org/LICENSE.txt for license information. |
5 | // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
6 | // |
7 | //===----------------------------------------------------------------------===// |
8 | |
9 | #include <optional> |
10 | #include <vector> |
11 | |
12 | #include "mlir-c/AffineMap.h" |
13 | #include "mlir-c/Dialect/SparseTensor.h" |
14 | #include "mlir-c/IR.h" |
15 | #include "mlir/Bindings/Python/NanobindAdaptors.h" |
16 | #include "mlir/Bindings/Python/Nanobind.h" |
17 | |
18 | namespace nb = nanobind; |
19 | using namespace llvm; |
20 | using namespace mlir; |
21 | using namespace mlir::python::nanobind_adaptors; |
22 | |
23 | static void populateDialectSparseTensorSubmodule(const nb::module_ &m) { |
24 | nb::enum_<MlirSparseTensorLevelFormat>(m, "LevelFormat" , nb::is_arithmetic(), |
25 | nb::is_flag()) |
26 | .value("dense" , MLIR_SPARSE_TENSOR_LEVEL_DENSE) |
27 | .value("n_out_of_m" , MLIR_SPARSE_TENSOR_LEVEL_N_OUT_OF_M) |
28 | .value("compressed" , MLIR_SPARSE_TENSOR_LEVEL_COMPRESSED) |
29 | .value("singleton" , MLIR_SPARSE_TENSOR_LEVEL_SINGLETON) |
30 | .value("loose_compressed" , MLIR_SPARSE_TENSOR_LEVEL_LOOSE_COMPRESSED); |
31 | |
32 | nb::enum_<MlirSparseTensorLevelPropertyNondefault>(m, "LevelProperty" ) |
33 | .value("non_ordered" , MLIR_SPARSE_PROPERTY_NON_ORDERED) |
34 | .value("non_unique" , MLIR_SPARSE_PROPERTY_NON_UNIQUE) |
35 | .value("soa" , MLIR_SPARSE_PROPERTY_SOA); |
36 | |
37 | mlir_attribute_subclass(m, "EncodingAttr" , |
38 | mlirAttributeIsASparseTensorEncodingAttr) |
39 | .def_classmethod( |
40 | "get" , |
41 | [](nb::object cls, std::vector<MlirSparseTensorLevelType> lvlTypes, |
42 | std::optional<MlirAffineMap> dimToLvl, |
43 | std::optional<MlirAffineMap> lvlToDim, int posWidth, int crdWidth, |
44 | std::optional<MlirAttribute> explicitVal, |
45 | std::optional<MlirAttribute> implicitVal, MlirContext context) { |
46 | return cls(mlirSparseTensorEncodingAttrGet( |
47 | context, lvlTypes.size(), lvlTypes.data(), |
48 | dimToLvl ? *dimToLvl : MlirAffineMap{nullptr}, |
49 | lvlToDim ? *lvlToDim : MlirAffineMap{nullptr}, posWidth, |
50 | crdWidth, explicitVal ? *explicitVal : MlirAttribute{nullptr}, |
51 | implicitVal ? *implicitVal : MlirAttribute{nullptr})); |
52 | }, |
53 | nb::arg("cls" ), nb::arg("lvl_types" ), nb::arg("dim_to_lvl" ).none(), |
54 | nb::arg("lvl_to_dim" ).none(), nb::arg("pos_width" ), |
55 | nb::arg("crd_width" ), nb::arg("explicit_val" ).none() = nb::none(), |
56 | nb::arg("implicit_val" ).none() = nb::none(), |
57 | nb::arg("context" ).none() = nb::none(), |
58 | "Gets a sparse_tensor.encoding from parameters." ) |
59 | .def_classmethod( |
60 | "build_level_type" , |
61 | [](nb::object cls, MlirSparseTensorLevelFormat lvlFmt, |
62 | const std::vector<MlirSparseTensorLevelPropertyNondefault> |
63 | &properties, |
64 | unsigned n, unsigned m) { |
65 | return mlirSparseTensorEncodingAttrBuildLvlType( |
66 | lvlFmt, properties.data(), properties.size(), n, m); |
67 | }, |
68 | nb::arg("cls" ), nb::arg("lvl_fmt" ), |
69 | nb::arg("properties" ) = |
70 | std::vector<MlirSparseTensorLevelPropertyNondefault>(), |
71 | nb::arg("n" ) = 0, nb::arg("m" ) = 0, |
72 | "Builds a sparse_tensor.encoding.level_type from parameters." ) |
73 | .def_property_readonly( |
74 | "lvl_types" , |
75 | [](MlirAttribute self) { |
76 | const int lvlRank = mlirSparseTensorEncodingGetLvlRank(self); |
77 | std::vector<MlirSparseTensorLevelType> ret; |
78 | ret.reserve(lvlRank); |
79 | for (int l = 0; l < lvlRank; ++l) |
80 | ret.push_back(mlirSparseTensorEncodingAttrGetLvlType(self, l)); |
81 | return ret; |
82 | }) |
83 | .def_property_readonly( |
84 | "dim_to_lvl" , |
85 | [](MlirAttribute self) -> std::optional<MlirAffineMap> { |
86 | MlirAffineMap ret = mlirSparseTensorEncodingAttrGetDimToLvl(self); |
87 | if (mlirAffineMapIsNull(ret)) |
88 | return {}; |
89 | return ret; |
90 | }) |
91 | .def_property_readonly( |
92 | "lvl_to_dim" , |
93 | [](MlirAttribute self) -> std::optional<MlirAffineMap> { |
94 | MlirAffineMap ret = mlirSparseTensorEncodingAttrGetLvlToDim(self); |
95 | if (mlirAffineMapIsNull(ret)) |
96 | return {}; |
97 | return ret; |
98 | }) |
99 | .def_property_readonly("pos_width" , |
100 | mlirSparseTensorEncodingAttrGetPosWidth) |
101 | .def_property_readonly("crd_width" , |
102 | mlirSparseTensorEncodingAttrGetCrdWidth) |
103 | .def_property_readonly( |
104 | "explicit_val" , |
105 | [](MlirAttribute self) -> std::optional<MlirAttribute> { |
106 | MlirAttribute ret = |
107 | mlirSparseTensorEncodingAttrGetExplicitVal(self); |
108 | if (mlirAttributeIsNull(ret)) |
109 | return {}; |
110 | return ret; |
111 | }) |
112 | .def_property_readonly( |
113 | "implicit_val" , |
114 | [](MlirAttribute self) -> std::optional<MlirAttribute> { |
115 | MlirAttribute ret = |
116 | mlirSparseTensorEncodingAttrGetImplicitVal(self); |
117 | if (mlirAttributeIsNull(ret)) |
118 | return {}; |
119 | return ret; |
120 | }) |
121 | .def_property_readonly( |
122 | "structured_n" , |
123 | [](MlirAttribute self) -> unsigned { |
124 | const int lvlRank = mlirSparseTensorEncodingGetLvlRank(self); |
125 | return mlirSparseTensorEncodingAttrGetStructuredN( |
126 | mlirSparseTensorEncodingAttrGetLvlType(self, lvlRank - 1)); |
127 | }) |
128 | .def_property_readonly( |
129 | "structured_m" , |
130 | [](MlirAttribute self) -> unsigned { |
131 | const int lvlRank = mlirSparseTensorEncodingGetLvlRank(self); |
132 | return mlirSparseTensorEncodingAttrGetStructuredM( |
133 | mlirSparseTensorEncodingAttrGetLvlType(self, lvlRank - 1)); |
134 | }) |
135 | .def_property_readonly("lvl_formats_enum" , [](MlirAttribute self) { |
136 | const int lvlRank = mlirSparseTensorEncodingGetLvlRank(self); |
137 | std::vector<MlirSparseTensorLevelFormat> ret; |
138 | ret.reserve(lvlRank); |
139 | for (int l = 0; l < lvlRank; l++) |
140 | ret.push_back(mlirSparseTensorEncodingAttrGetLvlFmt(self, l)); |
141 | return ret; |
142 | }); |
143 | } |
144 | |
145 | NB_MODULE(_mlirDialectsSparseTensor, m) { |
146 | m.doc() = "MLIR SparseTensor dialect." ; |
147 | populateDialectSparseTensorSubmodule(m); |
148 | } |
149 | |