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// Copyright 2017 Yahoo Holdings. 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/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/eval/eval/function.h>
#include <vespa/eval/eval/tensor_spec.h>
#include <vespa/eval/tensor/default_tensor.h>
#include <vespa/eval/tensor/default_tensor_engine.h>
#include <vespa/eval/tensor/tensor_factory.h>
using search::feature_t;
using namespace search::fef;
using namespace search::fef::indexproperties;
using namespace search::fef::test;
using namespace search::features;
using vespalib::eval::Function;
using vespalib::eval::Value;
using vespalib::eval::DoubleValue;
using vespalib::eval::TensorValue;
using vespalib::eval::TensorSpec;
using vespalib::eval::ValueType;
using vespalib::tensor::DefaultTensorEngine;
using vespalib::tensor::DenseTensorCells;
using vespalib::tensor::Tensor;
using vespalib::tensor::TensorCells;
using vespalib::tensor::TensorDimensions;
using vespalib::tensor::TensorFactory;
namespace
{
Tensor::UP createTensor(const TensorCells &cells,
const TensorDimensions &dimensions) {
vespalib::tensor::DefaultTensor::builder builder;
return TensorFactory::create(cells, dimensions, builder);
}
Tensor::UP make_tensor(const TensorSpec &spec) {
auto tensor = DefaultTensorEngine::ref().create(spec);
return Tensor::UP(dynamic_cast<Tensor*>(tensor.release()));
}
}
struct ExecFixture
{
BlueprintFactory factory;
FtFeatureTest test;
ExecFixture(const vespalib::string &feature)
: factory(),
test(factory, feature)
{
setup_search_features(factory);
}
bool setup() { return test.setup(); }
const Tensor &extractTensor(uint32_t docid) {
Value::CREF value = test.resolveObjectFeature(docid);
ASSERT_TRUE(value.get().is_tensor());
return static_cast<const Tensor &>(*value.get().as_tensor());
}
const Tensor &executeTensor(uint32_t docId = 1) {
return extractTensor(docId);
}
double extractDouble(uint32_t docid) {
Value::CREF value = test.resolveObjectFeature(docid);
ASSERT_TRUE(value.get().is_double());
return value.get().as_double();
}
double executeDouble(uint32_t docId = 1) {
return extractDouble(docId);
}
void addTensor(const vespalib::string &name,
const TensorCells &cells,
const TensorDimensions &dimensions)
{
Tensor::UP tensor = createTensor(cells, dimensions);
ValueType type(tensor->getType());
test.getIndexEnv().addConstantValue(name,
std::move(type),
std::make_unique<TensorValue>(std::move(tensor)));
}
void addDouble(const vespalib::string &name, const double value) {
test.getIndexEnv().addConstantValue(name,
ValueType::double_type(),
std::make_unique<DoubleValue>(value));
}
};
TEST_F("require that missing constant is detected",
ExecFixture("constant(foo)"))
{
EXPECT_TRUE(!f.setup());
}
TEST_F("require that existing tensor constant is detected",
ExecFixture("constant(foo)"))
{
f.addTensor("foo",
{ {{{"x", "a"}}, 3},
{{{"x", "b"}}, 5},
{{{"x", "c"}}, 7} },
{ "x" });
EXPECT_TRUE(f.setup());
auto expect = make_tensor(TensorSpec("tensor(x{})")
.add({{"x","b"}}, 5)
.add({{"x","c"}}, 7)
.add({{"x","a"}}, 3));
EXPECT_EQUAL(*expect, f.executeTensor());
}
TEST_F("require that existing double constant is detected",
ExecFixture("constant(foo)"))
{
f.addDouble("foo", 42.0);
EXPECT_TRUE(f.setup());
EXPECT_EQUAL(42.0, f.executeDouble());
}
TEST_MAIN() { TEST_RUN_ALL(); }
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