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 "mlir-c/AffineMap.h" |
10 | #include "mlir-c/Dialect/SparseTensor.h" |
11 | #include "mlir-c/IR.h" |
12 | #include "mlir/Bindings/Python/PybindAdaptors.h" |
13 | #include <optional> |
14 | #include <pybind11/cast.h> |
15 | #include <pybind11/detail/common.h> |
16 | #include <pybind11/pybind11.h> |
17 | #include <pybind11/pytypes.h> |
18 | #include <vector> |
19 | |
20 | namespace py = pybind11; |
21 | using namespace llvm; |
22 | using namespace mlir; |
23 | using namespace mlir::python::adaptors; |
24 | |
25 | static void populateDialectSparseTensorSubmodule(const py::module &m) { |
26 | py::enum_<MlirSparseTensorLevelFormat>(m, "LevelFormat" , py::module_local()) |
27 | .value("dense" , MLIR_SPARSE_TENSOR_LEVEL_DENSE) |
28 | .value("n_out_of_m" , MLIR_SPARSE_TENSOR_LEVEL_N_OUT_OF_M) |
29 | .value("compressed" , MLIR_SPARSE_TENSOR_LEVEL_COMPRESSED) |
30 | .value("singleton" , MLIR_SPARSE_TENSOR_LEVEL_SINGLETON) |
31 | .value("loose_compressed" , MLIR_SPARSE_TENSOR_LEVEL_LOOSE_COMPRESSED); |
32 | |
33 | py::enum_<MlirSparseTensorLevelPropertyNondefault>(m, "LevelProperty" , |
34 | py::module_local()) |
35 | .value("non_ordered" , MLIR_SPARSE_PROPERTY_NON_ORDERED) |
36 | .value("non_unique" , MLIR_SPARSE_PROPERTY_NON_UNIQUE); |
37 | |
38 | mlir_attribute_subclass(m, "EncodingAttr" , |
39 | mlirAttributeIsASparseTensorEncodingAttr) |
40 | .def_classmethod( |
41 | "get" , |
42 | [](py::object cls, std::vector<MlirSparseTensorLevelType> lvlTypes, |
43 | std::optional<MlirAffineMap> dimToLvl, |
44 | std::optional<MlirAffineMap> lvlToDim, int posWidth, int crdWidth, |
45 | 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)); |
51 | }, |
52 | py::arg("cls" ), py::arg("lvl_types" ), py::arg("dim_to_lvl" ), |
53 | py::arg("lvl_to_dim" ), py::arg("pos_width" ), py::arg("crd_width" ), |
54 | py::arg("context" ) = py::none(), |
55 | "Gets a sparse_tensor.encoding from parameters." ) |
56 | .def_classmethod( |
57 | "build_level_type" , |
58 | [](py::object cls, MlirSparseTensorLevelFormat lvlFmt, |
59 | const std::vector<MlirSparseTensorLevelPropertyNondefault> |
60 | &properties, |
61 | unsigned n, unsigned m) { |
62 | return mlirSparseTensorEncodingAttrBuildLvlType( |
63 | lvlFmt, properties.data(), properties.size(), n, m); |
64 | }, |
65 | py::arg("cls" ), py::arg("lvl_fmt" ), |
66 | py::arg("properties" ) = |
67 | std::vector<MlirSparseTensorLevelPropertyNondefault>(), |
68 | py::arg("n" ) = 0, py::arg("m" ) = 0, |
69 | "Builds a sparse_tensor.encoding.level_type from parameters." ) |
70 | .def_property_readonly( |
71 | "lvl_types" , |
72 | [](MlirAttribute self) { |
73 | const int lvlRank = mlirSparseTensorEncodingGetLvlRank(self); |
74 | std::vector<MlirSparseTensorLevelType> ret; |
75 | ret.reserve(lvlRank); |
76 | for (int l = 0; l < lvlRank; ++l) |
77 | ret.push_back(mlirSparseTensorEncodingAttrGetLvlType(self, l)); |
78 | return ret; |
79 | }) |
80 | .def_property_readonly( |
81 | "dim_to_lvl" , |
82 | [](MlirAttribute self) -> std::optional<MlirAffineMap> { |
83 | MlirAffineMap ret = mlirSparseTensorEncodingAttrGetDimToLvl(self); |
84 | if (mlirAffineMapIsNull(ret)) |
85 | return {}; |
86 | return ret; |
87 | }) |
88 | .def_property_readonly( |
89 | "lvl_to_dim" , |
90 | [](MlirAttribute self) -> std::optional<MlirAffineMap> { |
91 | MlirAffineMap ret = mlirSparseTensorEncodingAttrGetLvlToDim(self); |
92 | if (mlirAffineMapIsNull(ret)) |
93 | return {}; |
94 | return ret; |
95 | }) |
96 | .def_property_readonly("pos_width" , |
97 | mlirSparseTensorEncodingAttrGetPosWidth) |
98 | .def_property_readonly("crd_width" , |
99 | mlirSparseTensorEncodingAttrGetCrdWidth) |
100 | .def_property_readonly( |
101 | "structured_n" , |
102 | [](MlirAttribute self) -> unsigned { |
103 | const int lvlRank = mlirSparseTensorEncodingGetLvlRank(self); |
104 | return mlirSparseTensorEncodingAttrGetStructuredN( |
105 | mlirSparseTensorEncodingAttrGetLvlType(self, lvlRank - 1)); |
106 | }) |
107 | .def_property_readonly( |
108 | "structured_m" , |
109 | [](MlirAttribute self) -> unsigned { |
110 | const int lvlRank = mlirSparseTensorEncodingGetLvlRank(self); |
111 | return mlirSparseTensorEncodingAttrGetStructuredM( |
112 | mlirSparseTensorEncodingAttrGetLvlType(self, lvlRank - 1)); |
113 | }) |
114 | .def_property_readonly("lvl_formats_enum" , [](MlirAttribute self) { |
115 | const int lvlRank = mlirSparseTensorEncodingGetLvlRank(self); |
116 | std::vector<MlirSparseTensorLevelFormat> ret; |
117 | ret.reserve(lvlRank); |
118 | for (int l = 0; l < lvlRank; l++) |
119 | ret.push_back(mlirSparseTensorEncodingAttrGetLvlFmt(self, l)); |
120 | return ret; |
121 | }); |
122 | } |
123 | |
124 | PYBIND11_MODULE(_mlirDialectsSparseTensor, m) { |
125 | m.doc() = "MLIR SparseTensor dialect." ; |
126 | populateDialectSparseTensorSubmodule(m); |
127 | } |
128 | |