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
|
//===- QuantizationUtilsTest.cpp - unit tests for quantization utils ------===//
//
// 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/Quant/QuantOps.h"
#include "mlir/Dialect/Quant/QuantizeUtils.h"
#include "mlir/Dialect/Quant/UniformSupport.h"
#include "mlir/IR/Attributes.h"
#include "mlir/IR/StandardTypes.h"
#include "gmock/gmock.h"
#include "gtest/gtest.h"
using namespace mlir;
using namespace mlir::quant;
// Load the quant dialect
static DialectRegistration<QuantizationDialect> QuantOpsRegistration;
namespace {
// Test UniformQuantizedValueConverter converts all APFloat to a magic number 5.
class TestUniformQuantizedValueConverter
: public UniformQuantizedValueConverter {
public:
TestUniformQuantizedValueConverter(UniformQuantizedType type)
: UniformQuantizedValueConverter(type), qtype(type) {}
APInt quantizeFloatToInt(APFloat expressedValue) const {
return APInt(qtype.getStorageType().cast<IntegerType>().getWidth(), 5L);
}
private:
UniformQuantizedType qtype;
};
Attribute getTestFloatAttr(double value, MLIRContext *ctx) {
return FloatAttr::get(FloatType::getF32(ctx), value);
}
template <typename ConcreteAttrClass, typename... Arg>
ConcreteAttrClass getTestElementsAttr(MLIRContext *ctx, ArrayRef<int64_t> shape,
Arg... value) {
auto eleType = FloatType::getF32(ctx);
ShapedType tensorType;
if (shape.size() == 1 && shape[0] == -1) {
tensorType = UnrankedTensorType::get(eleType);
} else {
tensorType = RankedTensorType::get(shape, eleType);
}
return ConcreteAttrClass::get(tensorType, value...);
}
ElementsAttr getTestSparseElementsAttr(MLIRContext *ctx,
ArrayRef<int64_t> shape) {
auto eleType = FloatType::getF32(ctx);
ShapedType tensorType;
if (shape.size() == 1 && shape[0] == -1) {
tensorType = UnrankedTensorType::get(eleType);
} else {
tensorType = RankedTensorType::get(shape, eleType);
}
auto indicesType = RankedTensorType::get({1, 2}, IntegerType::get(64, ctx));
auto indices =
DenseIntElementsAttr::get(indicesType, {APInt(64, 0), APInt(64, 0)});
auto valuesType = RankedTensorType::get({1}, eleType);
auto values = DenseFPElementsAttr::get(valuesType, {APFloat(0.0f)});
return SparseElementsAttr::get(tensorType, indices, values);
}
UniformQuantizedType getTestQuantizedType(Type storageType, MLIRContext *ctx) {
return UniformQuantizedType::get(/*flags=*/false, storageType,
FloatType::getF32(ctx), /*scale=*/1.0,
/*zeroPoint=*/0, /*storageTypeMin=*/0,
/*storageTypeMax=*/255);
}
TEST(QuantizationUtilsTest, convertFloatAttrUniform) {
MLIRContext ctx;
IntegerType convertedType = IntegerType::get(8, &ctx);
auto quantizedType = getTestQuantizedType(convertedType, &ctx);
TestUniformQuantizedValueConverter converter(quantizedType);
auto realValue = getTestFloatAttr(1.0, &ctx);
Type typeResult;
auto valueResult =
quantizeAttrUniform(realValue, quantizedType, converter, typeResult);
EXPECT_EQ(valueResult.cast<IntegerAttr>().getInt(), 5);
EXPECT_EQ(
valueResult.cast<IntegerAttr>().getType().cast<IntegerType>().getWidth(),
convertedType.getWidth());
}
TEST(QuantizationUtilsTest, convertRankedDenseAttrUniform) {
MLIRContext ctx;
IntegerType convertedType = IntegerType::get(8, &ctx);
auto quantizedType = getTestQuantizedType(convertedType, &ctx);
TestUniformQuantizedValueConverter converter(quantizedType);
auto realValue = getTestElementsAttr<DenseElementsAttr, ArrayRef<Attribute>>(
&ctx, {1, 2}, {getTestFloatAttr(1.0, &ctx), getTestFloatAttr(2.0, &ctx)});
Type returnedType;
auto returnedValue =
quantizeAttrUniform(realValue, quantizedType, converter, returnedType);
// Check Elements attribute shape and kind are not changed.
auto tensorType = returnedType.cast<TensorType>();
auto expectedTensorType = realValue.getType().cast<TensorType>();
EXPECT_EQ(tensorType.getShape(), expectedTensorType.getShape());
EXPECT_EQ(tensorType.getElementType(), convertedType);
EXPECT_TRUE(returnedValue.isa<DenseIntElementsAttr>());
// Check Elements attribute element value is expected.
auto firstValue = returnedValue.cast<ElementsAttr>().getValue({0, 0});
EXPECT_EQ(firstValue.cast<IntegerAttr>().getInt(), 5);
}
TEST(QuantizationUtilsTest, convertRankedSplatAttrUniform) {
MLIRContext ctx;
IntegerType convertedType = IntegerType::get(8, &ctx);
auto quantizedType = getTestQuantizedType(convertedType, &ctx);
TestUniformQuantizedValueConverter converter(quantizedType);
auto realValue = getTestElementsAttr<DenseElementsAttr, Attribute>(
&ctx, {1, 2}, getTestFloatAttr(1.0, &ctx));
Type returnedType;
auto returnedValue =
quantizeAttrUniform(realValue, quantizedType, converter, returnedType);
// Check Elements attribute shape and kind are not changed.
auto tensorType = returnedType.cast<TensorType>();
auto expectedTensorType = realValue.getType().cast<TensorType>();
EXPECT_EQ(tensorType.getShape(), expectedTensorType.getShape());
EXPECT_EQ(tensorType.getElementType(), convertedType);
EXPECT_TRUE(returnedValue.isa<SplatElementsAttr>());
// Check Elements attribute element value is expected.
auto firstValue = returnedValue.cast<ElementsAttr>().getValue({0, 0});
EXPECT_EQ(firstValue.cast<IntegerAttr>().getInt(), 5);
}
TEST(QuantizationUtilsTest, convertRankedSparseAttrUniform) {
MLIRContext ctx;
IntegerType convertedType = IntegerType::get(8, &ctx);
auto quantizedType = getTestQuantizedType(convertedType, &ctx);
TestUniformQuantizedValueConverter converter(quantizedType);
auto realValue = getTestSparseElementsAttr(&ctx, {1, 2});
Type returnedType;
auto returnedValue =
quantizeAttrUniform(realValue, quantizedType, converter, returnedType);
// Check Elements attribute shape and kind are not changed.
auto tensorType = returnedType.cast<TensorType>();
auto expectedTensorType = realValue.getType().cast<TensorType>();
EXPECT_EQ(tensorType.getShape(), expectedTensorType.getShape());
EXPECT_EQ(tensorType.getElementType(), convertedType);
EXPECT_EQ(returnedValue.getKind(), StandardAttributes::SparseElements);
// Check Elements attribute element value is expected.
auto firstValue = returnedValue.cast<ElementsAttr>().getValue({0, 0});
EXPECT_EQ(firstValue.cast<IntegerAttr>().getInt(), 5);
}
} // end namespace
|
