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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 <iostream>
#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/simple_value.h>
#include <vespa/eval/eval/node_types.h>
#include <vespa/eval/eval/tensor_spec.h>
#include <vespa/eval/eval/value.h>
#include <vespa/eval/eval/test/value_compare.h>
#include <vespa/vespalib/util/stringfmt.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::DoubleValue;
using vespalib::eval::Function;
using vespalib::eval::SimpleValue;
using vespalib::eval::NodeTypes;
using vespalib::eval::TensorSpec;
using vespalib::eval::Value;
using vespalib::eval::ValueType;
using vespalib::make_string_short::fmt;
namespace
{
Value::UP make_tensor(const TensorSpec &spec) {
return SimpleValue::from_spec(spec);
}
}
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 Value &extractTensor(uint32_t docid) {
Value::CREF value = test.resolveObjectFeature(docid);
ASSERT_TRUE(value.get().type().has_dimensions());
return value.get();
}
const Value &executeTensor(uint32_t docId = 1) {
return extractTensor(docId);
}
double extractDouble(uint32_t docid) {
Value::CREF value = test.resolveObjectFeature(docid);
ASSERT_TRUE(value.get().type().is_double());
return value.get().as_double();
}
double executeDouble(uint32_t docId = 1) {
return extractDouble(docId);
}
void addTensor(const vespalib::string &name,
const TensorSpec &spec)
{
Value::UP tensor = make_tensor(spec);
ValueType type(tensor->type());
test.getIndexEnv().addConstantValue(name,
std::move(type),
std::move(tensor));
}
void addDouble(const vespalib::string &name, const double value) {
test.getIndexEnv().addConstantValue(name,
ValueType::double_type(),
std::make_unique<DoubleValue>(value));
}
void addTypeValue(const vespalib::string &name, const vespalib::string &type, const vespalib::string &value) {
auto &props = test.getIndexEnv().getProperties();
auto type_prop = fmt("constant(%s).type", name.c_str());
auto value_prop = fmt("constant(%s).value", name.c_str());
props.add(type_prop, type);
props.add(value_prop, 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",
TensorSpec("tensor(x{})")
.add({{"x","a"}}, 3)
.add({{"x","b"}}, 5)
.add({{"x","c"}}, 7));
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_F("require that constants can be functional", ExecFixture("constant(foo)")) {
f.addTypeValue("foo", "tensor(x{})", "tensor(x{}):{a:3,b:5,c:7}");
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 functional constant type must match the expression result", ExecFixture("constant(foo)")) {
f.addTypeValue("foo", "tensor<float>(x{})", "tensor(x{}):{a:3,b:5,c:7}");
EXPECT_TRUE(!f.setup());
}
TEST_F("require that functional constant must parse without errors", ExecFixture("constant(foo)")) {
f.addTypeValue("foo", "double", "this is parse error");
EXPECT_TRUE(!f.setup());
}
TEST_F("require that non-const functional constant is not allowed", ExecFixture("constant(foo)")) {
f.addTypeValue("foo", "tensor(x{})", "tensor(x{}):{a:a,b:5,c:7}");
EXPECT_TRUE(!f.setup());
}
TEST_F("require that functional constant must have non-error type", ExecFixture("constant(foo)")) {
f.addTypeValue("foo", "error", "impossible to create value with error type");
EXPECT_TRUE(!f.setup());
}
//-----------------------------------------------------------------------------
TEST_MAIN() { TEST_RUN_ALL(); }
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