1 | //===- NamedOpConversions.cpp - Implements conversions between named ops --===// |
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 conversions between named ops that can be seens as |
10 | // canonicalizations of named ops. |
11 | // |
12 | //===----------------------------------------------------------------------===// |
13 | |
14 | #include "mlir/Dialect/Linalg/Passes.h" |
15 | |
16 | #include "mlir/Dialect/Linalg/IR/Linalg.h" |
17 | #include "mlir/Dialect/Linalg/Transforms/Transforms.h" |
18 | #include "mlir/IR/PatternMatch.h" |
19 | #include "mlir/Transforms/GreedyPatternRewriteDriver.h" |
20 | #include "llvm/ADT/SmallVector.h" |
21 | #include "llvm/ADT/TypeSwitch.h" |
22 | |
23 | namespace mlir { |
24 | #define GEN_PASS_DEF_LINALGNAMEDOPCONVERSIONPASS |
25 | #include "mlir/Dialect/Linalg/Passes.h.inc" |
26 | } // namespace mlir |
27 | |
28 | using namespace mlir; |
29 | using namespace mlir::linalg; |
30 | |
31 | static llvm::SmallVector<int64_t> getIndicesVector(int start, int end) { |
32 | return llvm::to_vector<2>(llvm::seq<int64_t>(start, end)); |
33 | } |
34 | |
35 | static LogicalResult |
36 | matchAndReplaceDepthwiseConv(Operation *operation, Value input, Value kernel, |
37 | Value iZp, Value kZp, Value init, Attribute stride, |
38 | Attribute dilation, PatternRewriter &rewriter) { |
39 | Location loc = operation->getLoc(); |
40 | auto linalgOp = dyn_cast<LinalgOp>(operation); |
41 | // Exit out on the memref version of this operation. |
42 | if (!linalgOp || !linalgOp.hasPureTensorSemantics()) |
43 | return failure(); |
44 | |
45 | auto result = operation->getResult(idx: 0); |
46 | |
47 | auto kernelTy = dyn_cast<RankedTensorType>(kernel.getType()); |
48 | auto initTy = dyn_cast<RankedTensorType>(init.getType()); |
49 | auto resultTy = dyn_cast<RankedTensorType>(result.getType()); |
50 | if (!kernelTy || !initTy || !resultTy) |
51 | return failure(); |
52 | |
53 | if (kernelTy.getDimSize(3) != 1) |
54 | return failure(); |
55 | |
56 | // Collapse kernel dims. |
57 | SmallVector<ReassociationIndices, 4> collapsedKernelDims = { |
58 | getIndicesVector(start: 0, end: 1), getIndicesVector(start: 1, end: 2), getIndicesVector(start: 2, end: 4)}; |
59 | auto newKernelTy = RankedTensorType::get( |
60 | {kernelTy.getDimSize(0), kernelTy.getDimSize(1), kernelTy.getDimSize(2)}, |
61 | kernelTy.getElementType()); |
62 | auto collapsedKernel = rewriter.create<tensor::CollapseShapeOp>( |
63 | loc, newKernelTy, kernel, collapsedKernelDims); |
64 | |
65 | // Collapse init dims. |
66 | SmallVector<ReassociationIndices, 4> collapsedInitDims = { |
67 | getIndicesVector(start: 0, end: 1), getIndicesVector(start: 1, end: 2), getIndicesVector(start: 2, end: 3), |
68 | getIndicesVector(start: 3, end: 5)}; |
69 | auto newInitTy = |
70 | RankedTensorType::get({initTy.getDimSize(0), initTy.getDimSize(1), |
71 | initTy.getDimSize(2), initTy.getDimSize(3)}, |
72 | initTy.getElementType()); |
73 | auto collapsedInit = rewriter.create<tensor::CollapseShapeOp>( |
74 | loc, newInitTy, init, collapsedInitDims); |
75 | |
76 | SmallVector<NamedAttribute> preservedAttrs; |
77 | Operation *newConv = |
78 | TypeSwitch<Operation *, Operation *>(operation) |
79 | .Case<DepthwiseConv2DNhwcHwcmOp>([&](auto op) { |
80 | preservedAttrs = getPrunedAttributeList(op); |
81 | return rewriter.create<DepthwiseConv2DNhwcHwcOp>( |
82 | loc, newInitTy, ValueRange{input, collapsedKernel}, |
83 | ValueRange{collapsedInit}, stride, dilation); |
84 | }) |
85 | .Case<DepthwiseConv2DNhwcHwcmQOp>([&](auto op) { |
86 | preservedAttrs = getPrunedAttributeList(op); |
87 | return rewriter.create<DepthwiseConv2DNhwcHwcQOp>( |
88 | loc, newInitTy, ValueRange{input, collapsedKernel, iZp, kZp}, |
89 | ValueRange{collapsedInit}, stride, dilation); |
90 | }) |
91 | .Default([](Operation *op) { return nullptr; }); |
92 | if (!newConv) |
93 | return failure(); |
94 | for (auto attr : preservedAttrs) |
95 | newConv->setAttr(attr.getName(), attr.getValue()); |
96 | |
97 | // Expand dimensions back out to |
98 | rewriter.replaceOpWithNewOp<tensor::ExpandShapeOp>( |
99 | operation, resultTy, newConv->getResult(0), collapsedInitDims); |
100 | return success(); |
101 | } |
102 | |
103 | namespace { |
104 | struct SimplifyDepthwiseConvOp |
105 | : public OpRewritePattern<DepthwiseConv2DNhwcHwcmOp> { |
106 | using OpRewritePattern<DepthwiseConv2DNhwcHwcmOp>::OpRewritePattern; |
107 | |
108 | LogicalResult matchAndRewrite(DepthwiseConv2DNhwcHwcmOp op, |
109 | PatternRewriter &rewriter) const override { |
110 | Operation *operation = op.getOperation(); |
111 | Value input = op.getDpsInputOperand(0)->get(); |
112 | Value kernel = op.getDpsInputOperand(1)->get(); |
113 | Value init = op.getDpsInitOperand(0)->get(); |
114 | |
115 | auto stride = op.getStrides(); |
116 | auto dilation = op.getDilations(); |
117 | |
118 | return matchAndReplaceDepthwiseConv(operation, input, kernel, nullptr, |
119 | nullptr, init, stride, dilation, |
120 | rewriter); |
121 | } |
122 | }; |
123 | |
124 | struct SimplifyDepthwiseConvQOp |
125 | : public OpRewritePattern<DepthwiseConv2DNhwcHwcmQOp> { |
126 | using OpRewritePattern<DepthwiseConv2DNhwcHwcmQOp>::OpRewritePattern; |
127 | |
128 | LogicalResult matchAndRewrite(DepthwiseConv2DNhwcHwcmQOp op, |
129 | PatternRewriter &rewriter) const override { |
130 | Operation *operation = op.getOperation(); |
131 | Value input = op.getDpsInputOperand(0)->get(); |
132 | Value kernel = op.getDpsInputOperand(1)->get(); |
133 | Value iZp = op.getDpsInputOperand(2)->get(); |
134 | Value kZp = op.getDpsInputOperand(3)->get(); |
135 | Value init = op.getDpsInitOperand(0)->get(); |
136 | |
137 | auto stride = op.getStrides(); |
138 | auto dilation = op.getDilations(); |
139 | |
140 | return matchAndReplaceDepthwiseConv(operation, input, kernel, iZp, kZp, |
141 | init, stride, dilation, rewriter); |
142 | } |
143 | }; |
144 | |
145 | struct LinalgNamedOpConversionPass |
146 | : public impl::LinalgNamedOpConversionPassBase< |
147 | LinalgNamedOpConversionPass> { |
148 | using impl::LinalgNamedOpConversionPassBase< |
149 | LinalgNamedOpConversionPass>::LinalgNamedOpConversionPassBase; |
150 | |
151 | void runOnOperation() override { |
152 | Operation *op = getOperation(); |
153 | RewritePatternSet patterns(op->getContext()); |
154 | populateLinalgNamedOpConversionPatterns(patterns); |
155 | if (failed(applyPatternsAndFoldGreedily(op, std::move(patterns)))) |
156 | return signalPassFailure(); |
157 | } |
158 | }; |
159 | } // namespace |
160 | |
161 | void mlir::linalg::populateLinalgNamedOpConversionPatterns( |
162 | RewritePatternSet &patterns) { |
163 | patterns.add<SimplifyDepthwiseConvOp, SimplifyDepthwiseConvQOp>( |
164 | arg: patterns.getContext()); |
165 | } |
166 | |