1//===- LowerVectorScam.cpp - Lower 'vector.scan' operation ----------------===//
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// This file implements target-independent rewrites and utilities to lower the
10// 'vector.scan' operation.
11//
12//===----------------------------------------------------------------------===//
13
14#include "mlir/Dialect/Affine/IR/AffineOps.h"
15#include "mlir/Dialect/Arith/IR/Arith.h"
16#include "mlir/Dialect/Arith/Utils/Utils.h"
17#include "mlir/Dialect/Linalg/IR/Linalg.h"
18#include "mlir/Dialect/MemRef/IR/MemRef.h"
19#include "mlir/Dialect/SCF/IR/SCF.h"
20#include "mlir/Dialect/Tensor/IR/Tensor.h"
21#include "mlir/Dialect/Utils/IndexingUtils.h"
22#include "mlir/Dialect/Utils/StructuredOpsUtils.h"
23#include "mlir/Dialect/Vector/IR/VectorOps.h"
24#include "mlir/Dialect/Vector/Transforms/LoweringPatterns.h"
25#include "mlir/Dialect/Vector/Utils/VectorUtils.h"
26#include "mlir/IR/BuiltinAttributeInterfaces.h"
27#include "mlir/IR/BuiltinTypes.h"
28#include "mlir/IR/ImplicitLocOpBuilder.h"
29#include "mlir/IR/Location.h"
30#include "mlir/IR/Matchers.h"
31#include "mlir/IR/PatternMatch.h"
32#include "mlir/IR/TypeUtilities.h"
33#include "mlir/Interfaces/VectorInterfaces.h"
34
35#define DEBUG_TYPE "vector-broadcast-lowering"
36
37using namespace mlir;
38using namespace mlir::vector;
39
40/// This function checks to see if the vector combining kind
41/// is consistent with the integer or float element type.
42static bool isValidKind(bool isInt, vector::CombiningKind kind) {
43 using vector::CombiningKind;
44 enum class KindType { FLOAT, INT, INVALID };
45 KindType type{KindType::INVALID};
46 switch (kind) {
47 case CombiningKind::MINNUMF:
48 case CombiningKind::MINIMUMF:
49 case CombiningKind::MAXNUMF:
50 case CombiningKind::MAXIMUMF:
51 type = KindType::FLOAT;
52 break;
53 case CombiningKind::MINUI:
54 case CombiningKind::MINSI:
55 case CombiningKind::MAXUI:
56 case CombiningKind::MAXSI:
57 case CombiningKind::AND:
58 case CombiningKind::OR:
59 case CombiningKind::XOR:
60 type = KindType::INT;
61 break;
62 case CombiningKind::ADD:
63 case CombiningKind::MUL:
64 type = isInt ? KindType::INT : KindType::FLOAT;
65 break;
66 }
67 bool isValidIntKind = (type == KindType::INT) && isInt;
68 bool isValidFloatKind = (type == KindType::FLOAT) && (!isInt);
69 return (isValidIntKind || isValidFloatKind);
70}
71
72namespace {
73/// Convert vector.scan op into arith ops and vector.insert_strided_slice /
74/// vector.extract_strided_slice.
75///
76/// Example:
77///
78/// ```
79/// %0:2 = vector.scan <add>, %arg0, %arg1
80/// {inclusive = true, reduction_dim = 1} :
81/// (vector<2x3xi32>, vector<2xi32>) to (vector<2x3xi32>, vector<2xi32>)
82/// ```
83///
84/// is converted to:
85///
86/// ```
87/// %cst = arith.constant dense<0> : vector<2x3xi32>
88/// %0 = vector.extract_strided_slice %arg0
89/// {offsets = [0, 0], sizes = [2, 1], strides = [1, 1]}
90/// : vector<2x3xi32> to vector<2x1xi32>
91/// %1 = vector.insert_strided_slice %0, %cst
92/// {offsets = [0, 0], strides = [1, 1]}
93/// : vector<2x1xi32> into vector<2x3xi32>
94/// %2 = vector.extract_strided_slice %arg0
95/// {offsets = [0, 1], sizes = [2, 1], strides = [1, 1]}
96/// : vector<2x3xi32> to vector<2x1xi32>
97/// %3 = arith.muli %0, %2 : vector<2x1xi32>
98/// %4 = vector.insert_strided_slice %3, %1
99/// {offsets = [0, 1], strides = [1, 1]}
100/// : vector<2x1xi32> into vector<2x3xi32>
101/// %5 = vector.extract_strided_slice %arg0
102/// {offsets = [0, 2], sizes = [2, 1], strides = [1, 1]}
103/// : vector<2x3xi32> to vector<2x1xi32>
104/// %6 = arith.muli %3, %5 : vector<2x1xi32>
105/// %7 = vector.insert_strided_slice %6, %4
106/// {offsets = [0, 2], strides = [1, 1]}
107/// : vector<2x1xi32> into vector<2x3xi32>
108/// %8 = vector.shape_cast %6 : vector<2x1xi32> to vector<2xi32>
109/// return %7, %8 : vector<2x3xi32>, vector<2xi32>
110/// ```
111struct ScanToArithOps : public OpRewritePattern<vector::ScanOp> {
112 using OpRewritePattern::OpRewritePattern;
113
114 LogicalResult matchAndRewrite(vector::ScanOp scanOp,
115 PatternRewriter &rewriter) const override {
116 auto loc = scanOp.getLoc();
117 VectorType destType = scanOp.getDestType();
118 ArrayRef<int64_t> destShape = destType.getShape();
119 auto elType = destType.getElementType();
120 bool isInt = elType.isIntOrIndex();
121 if (!isValidKind(isInt, scanOp.getKind()))
122 return failure();
123
124 VectorType resType = VectorType::get(destShape, elType);
125 Value result = rewriter.create<arith::ConstantOp>(
126 loc, resType, rewriter.getZeroAttr(resType));
127 int64_t reductionDim = scanOp.getReductionDim();
128 bool inclusive = scanOp.getInclusive();
129 int64_t destRank = destType.getRank();
130 VectorType initialValueType = scanOp.getInitialValueType();
131 int64_t initialValueRank = initialValueType.getRank();
132
133 SmallVector<int64_t> reductionShape(destShape);
134 reductionShape[reductionDim] = 1;
135 VectorType reductionType = VectorType::get(reductionShape, elType);
136 SmallVector<int64_t> offsets(destRank, 0);
137 SmallVector<int64_t> strides(destRank, 1);
138 SmallVector<int64_t> sizes(destShape);
139 sizes[reductionDim] = 1;
140 ArrayAttr scanSizes = rewriter.getI64ArrayAttr(sizes);
141 ArrayAttr scanStrides = rewriter.getI64ArrayAttr(strides);
142
143 Value lastOutput, lastInput;
144 for (int i = 0; i < destShape[reductionDim]; i++) {
145 offsets[reductionDim] = i;
146 ArrayAttr scanOffsets = rewriter.getI64ArrayAttr(offsets);
147 Value input = rewriter.create<vector::ExtractStridedSliceOp>(
148 loc, reductionType, scanOp.getSource(), scanOffsets, scanSizes,
149 scanStrides);
150 Value output;
151 if (i == 0) {
152 if (inclusive) {
153 output = input;
154 } else {
155 if (initialValueRank == 0) {
156 // ShapeCastOp cannot handle 0-D vectors
157 output = rewriter.create<vector::BroadcastOp>(
158 loc, input.getType(), scanOp.getInitialValue());
159 } else {
160 output = rewriter.create<vector::ShapeCastOp>(
161 loc, input.getType(), scanOp.getInitialValue());
162 }
163 }
164 } else {
165 Value y = inclusive ? input : lastInput;
166 output = vector::makeArithReduction(rewriter, loc, scanOp.getKind(),
167 lastOutput, y);
168 }
169 result = rewriter.create<vector::InsertStridedSliceOp>(
170 loc, output, result, offsets, strides);
171 lastOutput = output;
172 lastInput = input;
173 }
174
175 Value reduction;
176 if (initialValueRank == 0) {
177 Value v = rewriter.create<vector::ExtractOp>(loc, lastOutput, 0);
178 reduction =
179 rewriter.create<vector::BroadcastOp>(loc, initialValueType, v);
180 } else {
181 reduction = rewriter.create<vector::ShapeCastOp>(loc, initialValueType,
182 lastOutput);
183 }
184
185 rewriter.replaceOp(scanOp, {result, reduction});
186 return success();
187 }
188};
189} // namespace
190
191void mlir::vector::populateVectorScanLoweringPatterns(
192 RewritePatternSet &patterns, PatternBenefit benefit) {
193 patterns.add<ScanToArithOps>(arg: patterns.getContext(), args&: benefit);
194}
195

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source code of mlir/lib/Dialect/Vector/Transforms/LowerVectorScan.cpp