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
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
|
//===- EmptyTensorElimination.cpp - tensor.empty op elimination -----------===//
//
// 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 "mlir/Dialect/Bufferization/Transforms/Passes.h"
#include "mlir/Dialect/Bufferization/IR/BufferizableOpInterface.h"
#include "mlir/Dialect/Bufferization/IR/Bufferization.h"
#include "mlir/Dialect/Bufferization/Transforms/OneShotAnalysis.h"
#include "mlir/Dialect/Bufferization/Transforms/Transforms.h"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/IR/Dominance.h"
#include "mlir/Pass/Pass.h"
namespace mlir {
namespace bufferization {
#define GEN_PASS_DEF_EMPTYTENSORELIMINATION
#include "mlir/Dialect/Bufferization/Transforms/Passes.h.inc"
} // namespace bufferization
} // namespace mlir
using namespace mlir;
using namespace mlir::bufferization;
/// Return true if all `neededValues` are in scope at the given
/// `insertionPoint`.
static bool
neededValuesDominateInsertionPoint(const DominanceInfo &domInfo,
Operation *insertionPoint,
const SmallVector<Value> &neededValues) {
for (Value val : neededValues) {
if (auto bbArg = val.dyn_cast<BlockArgument>()) {
Block *owner = bbArg.getOwner();
if (!owner->findAncestorOpInBlock(*insertionPoint))
return false;
} else {
auto opResult = val.cast<OpResult>();
if (!domInfo.dominates(opResult.getOwner(), insertionPoint))
return false;
}
}
return true;
}
/// Return true if the given `insertionPoint` dominates all uses of
/// `emptyTensorOp`.
static bool insertionPointDominatesUses(const DominanceInfo &domInfo,
Operation *insertionPoint,
Operation *emptyTensorOp) {
for (Operation *user : emptyTensorOp->getUsers())
if (!domInfo.dominates(insertionPoint, user))
return false;
return true;
}
/// Find a valid insertion point for a replacement of `emptyTensorOp`, assuming
/// that the replacement may use any value from `neededValues`.
static Operation *
findValidInsertionPoint(Operation *emptyTensorOp,
const SmallVector<Value> &neededValues) {
DominanceInfo domInfo;
// Gather all possible insertion points: the location of `emptyTensorOp` and
// right after the definition of each value in `neededValues`.
SmallVector<Operation *> insertionPointCandidates;
insertionPointCandidates.push_back(emptyTensorOp);
for (Value val : neededValues) {
// Note: The anchor op is using all of `neededValues`, so:
// * in case of a block argument: There must be at least one op in the block
// (the anchor op or one of its parents).
// * in case of an OpResult: There must be at least one op right after the
// defining op (the anchor op or one of its
// parents).
if (auto bbArg = val.dyn_cast<BlockArgument>()) {
insertionPointCandidates.push_back(
&bbArg.getOwner()->getOperations().front());
} else {
insertionPointCandidates.push_back(val.getDefiningOp()->getNextNode());
}
}
// Select first matching insertion point.
for (Operation *insertionPoint : insertionPointCandidates) {
// Check if all needed values are in scope.
if (!neededValuesDominateInsertionPoint(domInfo, insertionPoint,
neededValues))
continue;
// Check if the insertion point is before all uses.
if (!insertionPointDominatesUses(domInfo, insertionPoint, emptyTensorOp))
continue;
return insertionPoint;
}
// No suitable insertion point was found.
return nullptr;
}
/// Try to eliminate tensor::EmptyOps inside `op`. A tensor::EmptyOp is replaced
/// with the result of `rewriteFunc` if it is anchored on a matching
/// OpOperand. "Anchored" means that there is a path on the reverse SSA use-def
/// chain, starting from the OpOperand and always following the aliasing
/// OpOperand, that eventually ends at the tensor::EmptyOp.
///
/// E.g.:
/// %0 = tensor.empty() : tensor<10xf32>
/// %1 = linalg.fill ... outs(%0 : tensor<10xf32>)
/// %2 = tensor.insert_slice %0 into %t ...
///
/// In the above example, the anchor is the source operand of the insert_slice
/// op. When tracing back the reverse use-def chain, we end up at a
/// tensor.empty op.
LogicalResult mlir::bufferization::eliminateEmptyTensors(
RewriterBase &rewriter, Operation *op, OneShotAnalysisState &state,
AnchorMatchFn anchorMatchFunc, RewriteFn rewriteFunc) {
OpBuilder::InsertionGuard g(rewriter);
op->walk([&](Operation *op) {
for (OpOperand &operand : op->getOpOperands()) {
// Skip operands that do not bufferize inplace.
if (!state.isInPlace(operand))
continue;
// All values that are needed to create the replacement op.
SmallVector<Value> neededValues;
// Is this an anchor?
if (!anchorMatchFunc(operand, neededValues))
continue;
// Find tensor.empty ops on the reverse SSA use-def chain. Only follow
// equivalent tensors. I.e., stop when there are ops such as extract_slice
// on the path.
SetVector<Value> emptyTensors = state.findValueInReverseUseDefChain(
operand.get(), /*condition=*/
[&](Value val) { return val.getDefiningOp<tensor::EmptyOp>(); },
/*followEquivalentOnly=*/true, /*alwaysIncludeLeaves=*/false);
for (Value v : emptyTensors) {
Operation *emptyTensorOp = v.getDefiningOp();
// Replace only if the types match. We do not support slices or casts.
// TODO: This could be extended to support IR such as:
// %0 = tensor.empty() : tensor<128xf32>
// %1 = "some_op"(%0) : (tensor<128xf32>) -> (tensor<128xf32>)
// %2 = tensor.expand_shape %1 ...
// %3 = tensor.insert_slice %2 into ...
if (v.getType() != operand.get().getType())
continue;
// Find a suitable insertion point. If no suitable insertion point for
// the replacement can be found, skip this replacement.
Operation *insertionPoint =
findValidInsertionPoint(emptyTensorOp, neededValues);
if (!insertionPoint)
continue;
rewriter.setInsertionPoint(insertionPoint);
Value replacement =
rewriteFunc(rewriter, emptyTensorOp->getLoc(), operand);
if (!replacement)
continue;
// Replace the tensor::EmptyOp.
rewriter.replaceOp(emptyTensorOp, replacement);
state.resetCache();
}
}
});
return success();
}
/// Try to eliminate tensor::EmptyOps inside `op`. An tensor::EmptyOp can be
/// eliminated if it is eventually inserted into another tensor (and some other
/// conditions are met).
///
/// E.g.:
/// %0 = tensor.empty()
/// %1 = linalg.fill(%cst, %0) {inplace = [true]}
/// %2 = tensor.insert_slice %1 into %t[10][20][1]
///
/// tensor::EmptyOp elimination will try to fill %t inplace instead of filling a
/// new allocation %0 and inserting it into %t. This is done by replacing the
/// tensor::EmptyOp with:
///
/// %0 = tensor.extract_slice %t[10][20][1]
///
/// The analysis looks for matching ExtractSliceOp/InsertSliceOp pairs and lets
/// those bufferize inplace in the absence of other conflicts.
///
/// Starting from an InsertSliceOp, an tensor::EmptyOp at the end of the insert
/// source's reverse use-def chain is eliminated if:
/// * On the reverse use-def chain path from the InsertSliceOp to the
/// tensor::EmptyOp, all ops were decided to bufferize inplace and the buffer
/// relation is "equivalent" (TODO: can be relaxed if needed).
/// * The reverse use-def chain has exactly one end, which is the
/// tensor::EmptyOp.
template <typename OpTy>
static LogicalResult insertSliceLikeAnchoredEmptyTensorEliminationStep(
RewriterBase &rewriter, Operation *op, OneShotAnalysisState &state) {
return eliminateEmptyTensors(
rewriter, op, state,
/*anchorMatchFunc=*/
[&](OpOperand &operand, SmallVector<Value> &neededValues) {
auto insertSliceOp = dyn_cast<OpTy>(operand.getOwner());
if (!insertSliceOp)
return false;
if (&operand != &insertSliceOp->getOpOperand(0) /*source*/)
return false;
// Collect all values that are needed to construct the replacement op.
neededValues.append(insertSliceOp.getOffsets().begin(),
insertSliceOp.getOffsets().end());
neededValues.append(insertSliceOp.getSizes().begin(),
insertSliceOp.getSizes().end());
neededValues.append(insertSliceOp.getStrides().begin(),
insertSliceOp.getStrides().end());
neededValues.push_back(insertSliceOp.getDest());
return true;
},
/*rewriteFunc=*/
[](OpBuilder &b, Location loc, OpOperand &operand) {
auto insertOp = cast<OpTy>(operand.getOwner());
auto extractOp = b.create<tensor::ExtractSliceOp>(
loc, insertOp.getSourceType(), insertOp.getDest(),
insertOp.getMixedOffsets(), insertOp.getMixedSizes(),
insertOp.getMixedStrides());
return extractOp.getResult();
});
}
LogicalResult
mlir::bufferization::insertSliceAnchoredEmptyTensorEliminationStep(
RewriterBase &rewriter, Operation *op, OneShotAnalysisState &state) {
if (failed(insertSliceLikeAnchoredEmptyTensorEliminationStep<
tensor::InsertSliceOp>(rewriter, op, state)))
return failure();
if (failed(insertSliceLikeAnchoredEmptyTensorEliminationStep<
tensor::ParallelInsertSliceOp>(rewriter, op, state)))
return failure();
return success();
}
namespace {
struct EmptyTensorElimination
: public bufferization::impl::EmptyTensorEliminationBase<
EmptyTensorElimination> {
EmptyTensorElimination() = default;
void runOnOperation() override;
void getDependentDialects(DialectRegistry ®istry) const override {
registry
.insert<bufferization::BufferizationDialect, tensor::TensorDialect>();
}
};
} // namespace
void EmptyTensorElimination::runOnOperation() {
Operation *op = getOperation();
OneShotBufferizationOptions options;
options.allowReturnAllocs = true;
OneShotAnalysisState state(op, options);
if (failed(analyzeOp(op, state))) {
signalPassFailure();
return;
}
IRRewriter rewriter(op->getContext());
if (failed(bufferization::insertSliceAnchoredEmptyTensorEliminationStep(
rewriter, op, state)))
signalPassFailure();
}
std::unique_ptr<Pass> mlir::bufferization::createEmptyTensorEliminationPass() {
return std::make_unique<EmptyTensorElimination>();
}
|