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
|
//===- CodegenEnv.cpp - Code generation environment class ----------------===//
//
// 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 "CodegenEnv.h"
#include <optional>
using namespace mlir;
using namespace mlir::sparse_tensor;
//===----------------------------------------------------------------------===//
// Code generation environment constructor and general methods
//===----------------------------------------------------------------------===//
CodegenEnv::CodegenEnv(linalg::GenericOp linop, SparsificationOptions opts,
unsigned numTensors, unsigned numLoops,
unsigned numFilterLoops)
: linalgOp(linop), sparseOptions(opts),
latticeMerger(numTensors, numLoops, numFilterLoops), loopEmitter(),
topSort(), sparseOut(nullptr), outerParNest(-1u), insChain(), expValues(),
expFilled(), expAdded(), expCount(), redVal(), redExp(-1u),
redCustom(-1u) {}
void CodegenEnv::startEmit(OpOperand *so, unsigned lv) {
assert(sparseOut == nullptr && insChain == nullptr &&
"must only start emitting once");
sparseOut = so;
outerParNest = lv;
if (sparseOut) {
insChain = sparseOut->get();
latticeMerger.setHasSparseOut(true);
}
// Initialize loop emitter.
SmallVector<Value> tensors;
for (OpOperand &t : linalgOp->getOpOperands())
tensors.push_back(t.get());
loopEmitter.initialize(tensors,
StringAttr::get(linalgOp.getContext(),
linalg::GenericOp::getOperationName()),
/*hasOutput=*/true,
/*isSparseOut=*/sparseOut != nullptr, topSort);
}
std::optional<Operation *> CodegenEnv::genLoopBoundary(
function_ref<std::optional<Operation *>(MutableArrayRef<Value> parameters)>
callback) {
SmallVector<Value> params;
if (isReduc())
params.push_back(redVal);
if (isExpand())
params.push_back(expCount);
if (insChain != nullptr)
params.push_back(insChain);
auto r = callback(params); // may update parameters
unsigned i = 0;
if (isReduc())
updateReduc(params[i++]);
if (isExpand())
updateExpandCount(params[i++]);
if (insChain != nullptr)
updateInsertionChain(params[i]);
return r;
}
//===----------------------------------------------------------------------===//
// Code generation environment topological sort methods
//===----------------------------------------------------------------------===//
ArrayRef<unsigned> CodegenEnv::getTopSortSlice(size_t n, size_t m) const {
return ArrayRef<unsigned>(topSort).slice(n, m);
}
ArrayRef<unsigned> CodegenEnv::getLoopCurStack() const {
return getTopSortSlice(0, loopEmitter.getCurrentDepth());
}
Value CodegenEnv::getLoopIdxValue(size_t loopIdx) const {
for (unsigned lv = 0, lve = topSort.size(); lv < lve; lv++)
if (topSort[lv] == loopIdx)
return loopEmitter.getLoopIV(lv);
llvm_unreachable("invalid loop index");
}
//===----------------------------------------------------------------------===//
// Code generation environment sparse tensor output and expansion methods
//===----------------------------------------------------------------------===//
void CodegenEnv::updateInsertionChain(Value chain) {
assert(sparseOut != nullptr && insChain != nullptr);
insChain = chain;
}
bool CodegenEnv::atExpandLevel(OpOperand *o, unsigned rank, unsigned lv) const {
return sparseOut == o && outerParNest == rank - 1 && outerParNest == lv;
}
void CodegenEnv::startExpand(Value values, Value filled, Value added,
Value count) {
assert(sparseOut != nullptr && expValues == nullptr);
expValues = values;
expFilled = filled;
expAdded = added;
expCount = count;
}
void CodegenEnv::updateExpandCount(Value count) {
assert(sparseOut != nullptr && expValues != nullptr);
expCount = count;
}
void CodegenEnv::endExpand() {
assert(sparseOut != nullptr && expValues != nullptr);
expValues = expFilled = expAdded = expCount = Value();
}
//===----------------------------------------------------------------------===//
// Code generation environment reduction methods
//===----------------------------------------------------------------------===//
void CodegenEnv::startReduc(unsigned exp, Value val) {
assert(redExp == -1u && exp != -1u);
redExp = exp;
updateReduc(val);
}
void CodegenEnv::updateReduc(Value val) {
assert(redExp != -1u);
redVal = exp(redExp).val = val;
}
Value CodegenEnv::endReduc() {
Value val = redVal;
updateReduc(Value());
redExp = -1u;
return val;
}
void CodegenEnv::startCustomReduc(unsigned exp) {
assert(redCustom == -1u && exp != -1u);
redCustom = exp;
}
Value CodegenEnv::getCustomRedId() {
assert(redCustom != -1u);
return dyn_cast<sparse_tensor::ReduceOp>(exp(redCustom).op).getIdentity();
}
void CodegenEnv::endCustomReduc() {
assert(redCustom != -1u);
redCustom = -1u;
}
|
