File: DialectSparseTensor.cpp

package info (click to toggle)
llvm-toolchain-13 1%3A13.0.1-11
  • links: PTS, VCS
  • area: main
  • in suites: bookworm
  • size: 1,418,840 kB
  • sloc: cpp: 5,290,826; ansic: 996,570; asm: 544,593; python: 188,212; objc: 72,027; lisp: 30,291; f90: 25,395; sh: 24,898; javascript: 9,780; pascal: 9,398; perl: 7,484; ml: 5,432; awk: 3,523; makefile: 2,913; xml: 953; cs: 573; fortran: 539
file content (74 lines) | stat: -rw-r--r-- 3,048 bytes parent folder | download | duplicates (3)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
//===- DialectLinalg.cpp - 'sparse_tensor' dialect submodule --------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//

#include "Dialects.h"
#include "mlir-c/Dialect/SparseTensor.h"
#include "mlir-c/IR.h"
#include "mlir/Bindings/Python/PybindAdaptors.h"

namespace py = pybind11;
using namespace llvm;
using namespace mlir;
using namespace mlir::python::adaptors;

void mlir::python::populateDialectSparseTensorSubmodule(
    py::module m, const py::module &irModule) {
  auto attributeClass = irModule.attr("Attribute");

  py::enum_<MlirSparseTensorDimLevelType>(m, "DimLevelType")
      .value("dense", MLIR_SPARSE_TENSOR_DIM_LEVEL_DENSE)
      .value("compressed", MLIR_SPARSE_TENSOR_DIM_LEVEL_COMPRESSED)
      .value("singleton", MLIR_SPARSE_TENSOR_DIM_LEVEL_SINGLETON);

  mlir_attribute_subclass(m, "EncodingAttr",
                          mlirAttributeIsASparseTensorEncodingAttr,
                          attributeClass)
      .def_classmethod(
          "get",
          [](py::object cls,
             std::vector<MlirSparseTensorDimLevelType> dimLevelTypes,
             llvm::Optional<MlirAffineMap> dimOrdering, int pointerBitWidth,
             int indexBitWidth, MlirContext context) {
            return cls(mlirSparseTensorEncodingAttrGet(
                context, dimLevelTypes.size(), dimLevelTypes.data(),
                dimOrdering ? *dimOrdering : MlirAffineMap{nullptr},
                pointerBitWidth, indexBitWidth));
          },
          py::arg("cls"), py::arg("dim_level_types"), py::arg("dim_ordering"),
          py::arg("pointer_bit_width"), py::arg("index_bit_width"),
          py::arg("context") = py::none(),
          "Gets a sparse_tensor.encoding from parameters.")
      .def_property_readonly(
          "dim_level_types",
          [](MlirAttribute self) {
            std::vector<MlirSparseTensorDimLevelType> ret;
            for (int i = 0,
                     e = mlirSparseTensorEncodingGetNumDimLevelTypes(self);
                 i < e; ++i)
              ret.push_back(
                  mlirSparseTensorEncodingAttrGetDimLevelType(self, i));
            return ret;
          })
      .def_property_readonly(
          "dim_ordering",
          [](MlirAttribute self) -> llvm::Optional<MlirAffineMap> {
            MlirAffineMap ret =
                mlirSparseTensorEncodingAttrGetDimOrdering(self);
            if (mlirAffineMapIsNull(ret))
              return {};
            return ret;
          })
      .def_property_readonly(
          "pointer_bit_width",
          [](MlirAttribute self) {
            return mlirSparseTensorEncodingAttrGetPointerBitWidth(self);
          })
      .def_property_readonly("index_bit_width", [](MlirAttribute self) {
        return mlirSparseTensorEncodingAttrGetIndexBitWidth(self);
      });
}