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
|
// Copyright 2016 Yahoo Inc. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#include <vespa/vespalib/testkit/test_kit.h>
#include <vespa/eval/tensor/sparse/sparse_tensor_builder.h>
#include <vespa/vespalib/test/insertion_operators.h>
using namespace vespalib::tensor;
using vespalib::eval::TensorSpec;
using vespalib::eval::ValueType;
void
assertCellValue(double expValue, const TensorAddress &address,
const ValueType &type,
const SparseTensor::Cells &cells)
{
SparseTensorAddressBuilder addressBuilder;
auto dimsItr = type.dimensions().cbegin();
auto dimsItrEnd = type.dimensions().cend();
for (const auto &element : address.elements()) {
while ((dimsItr < dimsItrEnd) && (dimsItr->name < element.dimension())) {
addressBuilder.add("");
++dimsItr;
}
assert((dimsItr != dimsItrEnd) && (dimsItr->name == element.dimension()));
addressBuilder.add(element.label());
++dimsItr;
}
while (dimsItr < dimsItrEnd) {
addressBuilder.add("");
++dimsItr;
}
SparseTensorAddressRef addressRef(addressBuilder.getAddressRef());
auto itr = cells.find(addressRef);
EXPECT_FALSE(itr == cells.end());
EXPECT_EQUAL(expValue, itr->second);
}
Tensor::UP
buildTensor()
{
SparseTensorBuilder builder;
builder.define_dimension("c");
builder.define_dimension("d");
builder.define_dimension("a");
builder.define_dimension("b");
builder.add_label(builder.define_dimension("a"), "1").
add_label(builder.define_dimension("b"), "2").add_cell(10).
add_label(builder.define_dimension("c"), "3").
add_label(builder.define_dimension("d"), "4").add_cell(20);
return builder.build();
}
TEST("require that tensor can be constructed")
{
Tensor::UP tensor = buildTensor();
const SparseTensor &sparseTensor = dynamic_cast<const SparseTensor &>(*tensor);
const ValueType &type = sparseTensor.type();
const SparseTensor::Cells &cells = sparseTensor.cells();
EXPECT_EQUAL(2u, cells.size());
assertCellValue(10, TensorAddress({{"a","1"},{"b","2"}}),
type, cells);
assertCellValue(20, TensorAddress({{"c","3"},{"d","4"}}),
type, cells);
}
TEST("require that tensor can be converted to tensor spec")
{
Tensor::UP tensor = buildTensor();
TensorSpec expSpec("tensor(a{},b{},c{},d{})");
expSpec.add({{"a", "1"}, {"b", "2"}, {"c", ""}, {"d", ""}}, 10).
add({{"a", ""},{"b",""},{"c", "3"}, {"d", "4"}}, 20);
TensorSpec actSpec = tensor->toSpec();
EXPECT_EQUAL(expSpec, actSpec);
}
TEST("require that dimensions are extracted")
{
SparseTensorBuilder builder;
builder.define_dimension("c");
builder.define_dimension("a");
builder.define_dimension("b");
builder.
add_label(builder.define_dimension("a"), "1").
add_label(builder.define_dimension("b"), "2").add_cell(10).
add_label(builder.define_dimension("b"), "3").
add_label(builder.define_dimension("c"), "4").add_cell(20);
Tensor::UP tensor = builder.build();
const SparseTensor &sparseTensor = dynamic_cast<const SparseTensor &>(*tensor);
const auto &dims = sparseTensor.type().dimensions();
EXPECT_EQUAL(3u, dims.size());
EXPECT_EQUAL("a", dims[0].name);
EXPECT_EQUAL("b", dims[1].name);
EXPECT_EQUAL("c", dims[2].name);
EXPECT_EQUAL("tensor(a{},b{},c{})", sparseTensor.getType().to_spec());
}
TEST_MAIN() { TEST_RUN_ALL(); }
|
