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
|
// Copyright Vespa.ai. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#include <vespa/eval/eval/tensor_spec.h>
#include <vespa/searchlib/features/distancefeature.h>
#include <vespa/searchlib/fef/test/dummy_dependency_handler.h>
#include <vespa/searchlib/fef/test/labels.h>
#include <vespa/searchlib/test/features/distance_closeness_fixture.h>
#include <vespa/vespalib/stllike/asciistream.h>
#include <vespa/vespalib/gtest/gtest.h>
#include <vespa/vespalib/util/stringfmt.h>
using search::feature_t;
using namespace search::features::test;
using namespace search::features;
using namespace search::fef::test;
using namespace search::fef;
using vespalib::eval::TensorSpec;
const vespalib::string labelFeatureName("distance(label,nns)");
const vespalib::string fieldFeatureName("distance(bar)");
using RankFixture = DistanceClosenessFixture;
TEST(NnsDistanceTest, require_that_blueprint_can_be_created_from_factory)
{
BlueprintFactoryFixture f;
Blueprint::SP bp = f.factory.createBlueprint("distance");
EXPECT_TRUE(bp.get() != 0);
EXPECT_TRUE(dynamic_cast<DistanceBlueprint*>(bp.get()) != 0);
}
TEST(NnsDistanceTest, require_that_no_features_are_dumped)
{
DistanceBlueprint f1;
IndexEnvironmentFixture f2;
FeatureDumpFixture f3;
f1.visitDumpFeatures(f2.indexEnv, f3);
}
TEST(NnsDistanceTest, require_that_setup_can_be_done_on_random_label)
{
DistanceBlueprint f1;
IndexEnvironmentFixture f2;
DummyDependencyHandler deps(f1);
f1.setName(vespalib::make_string("%s(label,random_label)", f1.getBaseName().c_str()));
EXPECT_TRUE(static_cast<Blueprint&>(f1).setup(f2.indexEnv, std::vector<vespalib::string>{"label", "random_label"}));
}
TEST(NnsDistanceTest, require_that_setup_with_unknown_field_fails)
{
DistanceBlueprint f1;
IndexEnvironmentFixture f2;
DummyDependencyHandler deps(f1);
f1.setName(vespalib::make_string("%s(field,random_fieldname)", f1.getBaseName().c_str()));
EXPECT_FALSE(static_cast<Blueprint&>(f1).setup(f2.indexEnv, std::vector<vespalib::string>{"field", "random_fieldname"}));
}
TEST(NnsDistanceTest, require_that_no_label_gives_max_double_distance)
{
NoLabel f1;
RankFixture f2(2, 2, f1, labelFeatureName);
ASSERT_FALSE(f2.failed());
EXPECT_EQ(std::numeric_limits<feature_t>::max(), f2.getScore(10));
}
TEST(NnsDistanceTest, require_that_unrelated_label_gives_max_double_distance)
{
SingleLabel f1("unrelated", 1);
RankFixture f2(2, 2, f1, labelFeatureName);
ASSERT_FALSE(f2.failed());
EXPECT_EQ(std::numeric_limits<feature_t>::max(), f2.getScore(10));
}
TEST(NnsDistanceTest, require_that_labeled_item_raw_score_can_be_obtained)
{
SingleLabel f1("nns", 1);
RankFixture f2(2, 2, f1, labelFeatureName);
ASSERT_FALSE(f2.failed());
f2.setFooScore(0, 10, 5.0);
EXPECT_EQ(5.0, f2.getScore(10));
}
TEST(NnsDistanceTest, require_that_field_raw_score_can_be_obtained)
{
NoLabel f1;
RankFixture f2(2, 2, f1, fieldFeatureName);
ASSERT_FALSE(f2.failed());
f2.setBarScore(0, 10, 5.0);
EXPECT_EQ(5.0, f2.getScore(10));
}
TEST(NnsDistanceTest, require_that_other_raw_scores_are_ignored)
{
SingleLabel f1("nns", 2);
RankFixture f2(2, 2, f1, labelFeatureName);
ASSERT_FALSE(f2.failed());
f2.setFooScore(0, 10, 1.0);
f2.setFooScore(1, 10, 2.0);
f2.setBarScore(0, 10, 5.0);
f2.setBarScore(1, 10, 6.0);
EXPECT_EQ(2.0, f2.getScore(10));
}
TEST(NnsDistanceTest, require_that_the_correct_raw_score_is_used)
{
NoLabel f1;
RankFixture f2(2, 2, f1, fieldFeatureName);
ASSERT_FALSE(f2.failed());
f2.setFooScore(0, 10, 3.0);
f2.setFooScore(1, 10, 4.0);
f2.setBarScore(0, 10, 8.0);
f2.setBarScore(1, 10, 7.0);
EXPECT_EQ(7.0, f2.getScore(10));
}
TEST(NnsDistanceTest, require_that_stale_data_is_ignored)
{
SingleLabel f1("nns", 2);
RankFixture f2(2, 2, f1, labelFeatureName);
ASSERT_FALSE(f2.failed());
f2.setFooScore(0, 10, 1.0);
f2.setFooScore(1, 5, 2.0);
EXPECT_EQ(std::numeric_limits<feature_t>::max(), f2.getScore(10));
}
void
expect_raw_score_calculated_on_the_fly(RankFixture& f)
{
f.setBarScore(0, 8, 13.0);
f.set_attribute_tensor(9, TensorSpec::from_expr("tensor(x[2]):[5,11]"));
f.set_attribute_tensor(10, TensorSpec::from_expr("tensor(x[2]):[7,11]"));
// For docids 9 and 10 the raw score is calculated on the fly
// using a distance calculator over the attribute and query tensors.
EXPECT_EQ(13.0, f.getScore(8));
EXPECT_EQ((5-3), f.getScore(9));
EXPECT_EQ((7-3), f.getScore(10));
}
TEST(NnsDistanceTest, raw_score_is_calculated_on_the_fly_using_field_setup)
{
NoLabel f1;
RankFixture f2(0, 1, f1, fieldFeatureName, "tensor(x[2]):[3,11]");
ASSERT_FALSE(f2.failed());
expect_raw_score_calculated_on_the_fly(f2);
}
TEST(NnsDistanceTest, raw_score_is_calculated_on_the_fly_using_label_setup)
{
SingleLabel f1("nns", 1);
RankFixture f2(0, 1, f1, labelFeatureName, "tensor(x[2]):[3,11]");
ASSERT_FALSE(f2.failed());
expect_raw_score_calculated_on_the_fly(f2);
}
GTEST_MAIN_RUN_ALL_TESTS()
|
