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// Copyright Vespa.ai. 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/searchlib/attribute/attributefactory.h>
#include <vespa/searchlib/attribute/attributevector.h>
#include <vespa/searchlib/features/setup.h>
#include <vespa/searchlib/fef/fef.h>
#include <vespa/searchlib/fef/test/ftlib.h>
#include <vespa/searchlib/fef/test/indexenvironment.h>
#include <vespa/searchlib/tensor/tensor_attribute.h>
#include <vespa/searchlib/tensor/direct_tensor_attribute.h>
#include <vespa/searchcommon/attribute/config.h>
#include <vespa/eval/eval/function.h>
#include <vespa/eval/eval/simple_value.h>
#include <vespa/eval/eval/tensor_spec.h>
#include <vespa/eval/eval/value.h>
#include <vespa/eval/eval/value_codec.h>
#include <vespa/eval/eval/test/value_compare.h>
#include <vespa/vespalib/objects/nbostream.h>
using search::feature_t;
using namespace search::fef;
using namespace search::fef::indexproperties;
using namespace search::fef::test;
using namespace search::features;
using search::AttributeFactory;
using search::tensor::TensorAttribute;
using search::tensor::DirectTensorAttribute;
using search::AttributeVector;
using vespalib::eval::Function;
using vespalib::eval::SimpleValue;
using vespalib::eval::TensorSpec;
using vespalib::eval::Value;
using vespalib::eval::ValueType;
using vespalib::eval::spec_from_value;
using AVC = search::attribute::Config;
using AVBT = search::attribute::BasicType;
using AVCT = search::attribute::CollectionType;
using AttributePtr = search::AttributeVector::SP;
using FTA = FtTestApp;
using CollectionType = FieldInfo::CollectionType;
namespace
{
Value::UP make_empty(const vespalib::string &type) {
return SimpleValue::from_spec(TensorSpec(type));
}
}
struct ExecFixture
{
BlueprintFactory factory;
FtFeatureTest test;
ExecFixture(const vespalib::string &feature)
: factory(),
test(factory, feature)
{
setup_search_features(factory);
setupAttributeVectors();
setupQueryEnvironment();
ASSERT_TRUE(test.setup());
}
void addAttributeField(const vespalib::string &attrName) {
test.getIndexEnv().getBuilder().addField(FieldType::ATTRIBUTE, CollectionType::SINGLE, attrName);
}
AttributeVector::SP createStringAttribute(const vespalib::string &attrName) {
addAttributeField(attrName);
return AttributeFactory::createAttribute(attrName, AVC(AVBT::STRING, AVCT::SINGLE));
}
AttributeVector::SP createTensorAttribute(const vespalib::string &attrName,
const vespalib::string &type,
bool direct = false)
{
addAttributeField(attrName);
AVC config(AVBT::TENSOR, AVCT::SINGLE);
config.setTensorType(ValueType::from_spec(type));
config.setFastSearch(direct);
return AttributeFactory::createAttribute(attrName, config);
}
void setAttributeTensorType(const vespalib::string &attrName, const vespalib::string &type) {
type::Attribute::set(test.getIndexEnv().getProperties(), attrName, type);
}
void setQueryTensorType(const vespalib::string &queryFeatureName, const vespalib::string &type) {
type::QueryFeature::set(test.getIndexEnv().getProperties(), queryFeatureName, type);
}
void setQueryTensorDefault(const vespalib::string &tensorName, const vespalib::string &expr) {
vespalib::string key = "query(" + tensorName + ")";
test.getIndexEnv().getProperties().add(key, expr);
}
void setupAttributeVectors() {
std::vector<AttributePtr> attrs;
attrs.push_back(createTensorAttribute("tensorattr", "tensor(x{})"));
attrs.push_back(createTensorAttribute("directattr", "tensor(x{})", true));
attrs.push_back(createStringAttribute("singlestr"));
attrs.push_back(createTensorAttribute("wrongtype", "tensor(y{})"));
addAttributeField("null");
setAttributeTensorType("tensorattr", "tensor(x{})");
setAttributeTensorType("directattr", "tensor(x{})");
setAttributeTensorType("wrongtype", "tensor(x{})");
setAttributeTensorType("null", "tensor(x{})");
for (const auto &attr : attrs) {
attr->addReservedDoc();
attr->addDocs(2);
attr->clearDoc(1);
attr->clearDoc(2);
attr->commit();
test.getIndexEnv().getAttributeMap().add(attr);
}
TensorAttribute *tensorAttr =
dynamic_cast<TensorAttribute *>(attrs[0].get());
DirectTensorAttribute *directAttr =
dynamic_cast<DirectTensorAttribute *>(attrs[1].get());
auto doc_tensor = SimpleValue::from_spec(TensorSpec("tensor(x{})")
.add({{"x", "a"}}, 3)
.add({{"x", "b"}}, 5)
.add({{"x", "c"}}, 7));
tensorAttr->setTensor(1, *doc_tensor);
directAttr->setTensor(1, *doc_tensor);
for (const auto &attr : attrs) {
attr->commit();
}
}
void setQueryTensor(const vespalib::string &tensorName,
const vespalib::string &tensorTypeSpec,
std::unique_ptr<Value> tensor)
{
vespalib::nbostream stream;
encode_value(*tensor, stream);
test.getQueryEnv().getProperties().add(tensorName,
vespalib::stringref(stream.peek(), stream.size()));
setQueryTensorType(tensorName, tensorTypeSpec);
}
void setupQueryEnvironment() {
setQueryTensor("tensorquery",
"tensor(q{})",
SimpleValue::from_spec(TensorSpec("tensor(q{})")
.add({{"q", "d"}}, 11 )
.add({{"q", "e"}}, 13 )
.add({{"q", "f"}}, 17 )));
setQueryTensor("mappedtensorquery",
"tensor(x[2])",
SimpleValue::from_spec(TensorSpec("tensor(x{},y{})")
.add({{"x", "0"},{"y", "0"}}, 11 )
.add({{"x", "0"},{"y", "1"}}, 13 )
.add({{"x", "1"},{"y", "0"}}, 17 )));
setQueryTensorType("null", "tensor(q{})");
setQueryTensorType("with_default", "tensor(x[3])");
setQueryTensorDefault("with_default", "tensor(x[3])(x+1)");
}
const Value &extractTensor(uint32_t docid) {
Value::CREF value = test.resolveObjectFeature(docid);
ASSERT_TRUE(value.get().type().has_dimensions());
return value.get();
}
const Value &execute(uint32_t docId = 1) {
return extractTensor(docId);
}
};
TEST_F("require that tensor attribute can be extracted as tensor in attribute feature",
ExecFixture("attribute(tensorattr)"))
{
EXPECT_EQUAL(TensorSpec("tensor(x{})")
.add({{"x", "b"}}, 5)
.add({{"x", "c"}}, 7)
.add({{"x", "a"}}, 3), spec_from_value(f.execute()));
}
TEST_F("require that direct tensor attribute can be extracted in attribute feature",
ExecFixture("attribute(directattr)"))
{
EXPECT_EQUAL(TensorSpec("tensor(x{})")
.add({{"x", "b"}}, 5)
.add({{"x", "c"}}, 7)
.add({{"x", "a"}}, 3), spec_from_value(f.execute()));
}
TEST_F("require that tensor from query can be extracted as tensor in query feature",
ExecFixture("query(tensorquery)"))
{
EXPECT_EQUAL(TensorSpec("tensor(q{})")
.add({{"q", "f"}}, 17)
.add({{"q", "d"}}, 11)
.add({{"q", "e"}}, 13), spec_from_value(f.execute()));
}
TEST_F("require that tensor from query can have default value",
ExecFixture("query(with_default)"))
{
EXPECT_EQUAL(TensorSpec("tensor(x[3])")
.add({{"x", 0}}, 1)
.add({{"x", 1}}, 2)
.add({{"x", 2}}, 3), spec_from_value(f.execute()));
}
TEST_F("require that empty tensor is created if attribute does not exists",
ExecFixture("attribute(null)"))
{
EXPECT_EQUAL(*make_empty("tensor(x{})"), f.execute());
}
TEST_F("require that empty tensor is created if tensor type is wrong",
ExecFixture("attribute(wrongtype)"))
{
EXPECT_EQUAL(*make_empty("tensor(x{})"), f.execute());
}
TEST_F("require that empty tensor is created if query parameter is not found",
ExecFixture("query(null)"))
{
EXPECT_EQUAL(*make_empty("tensor(q{})"), f.execute());
}
TEST_F("require that empty tensor with correct type is created if document has no tensor",
ExecFixture("attribute(tensorattr)")) {
EXPECT_EQUAL(*make_empty("tensor(x{})"), f.execute(2));
}
TEST_F("require that empty tensor with correct type is returned by direct tensor attribute",
ExecFixture("attribute(directattr)")) {
EXPECT_EQUAL(*make_empty("tensor(x{})"), f.execute(2));
}
TEST_F("require that wrong tensor type from query tensor gives empty tensor",
ExecFixture("query(mappedtensorquery)")) {
EXPECT_EQUAL(TensorSpec("tensor(x[2])")
.add({{"x", 0}}, 0)
.add({{"x", 1}}, 0), spec_from_value(f.execute()));
}
TEST_MAIN() { TEST_RUN_ALL(); }
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