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media / learning / mojo / mojo_learning_task_controller_service_unittest.cc [blame]
// Copyright 2019 The Chromium Authors
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
#include <memory>
#include <utility>
#include "base/functional/bind.h"
#include "base/memory/ptr_util.h"
#include "base/memory/raw_ptr.h"
#include "base/test/task_environment.h"
#include "base/threading/thread.h"
#include "media/learning/mojo/mojo_learning_task_controller_service.h"
#include "testing/gtest/include/gtest/gtest.h"
namespace {
// Meaningless, but non-empty, source id.
ukm::SourceId kSourceId{123};
} // namespace
namespace media {
namespace learning {
class MojoLearningTaskControllerServiceTest : public ::testing::Test {
public:
class FakeLearningTaskController : public LearningTaskController {
public:
void BeginObservation(
base::UnguessableToken id,
const FeatureVector& features,
const std::optional<TargetValue>& default_target,
const std::optional<ukm::SourceId>& source_id) override {
begin_args_.id_ = id;
begin_args_.features_ = features;
begin_args_.default_target_ = default_target;
begin_args_.source_id_ = source_id;
}
void CompleteObservation(base::UnguessableToken id,
const ObservationCompletion& completion) override {
complete_args_.id_ = id;
complete_args_.completion_ = completion;
}
void CancelObservation(base::UnguessableToken id) override {
cancel_args_.id_ = id;
}
void UpdateDefaultTarget(
base::UnguessableToken id,
const std::optional<TargetValue>& default_target) override {
update_default_args_.id_ = id;
update_default_args_.default_target_ = default_target;
}
const LearningTask& GetLearningTask() override {
return LearningTask::Empty();
}
void PredictDistribution(const FeatureVector& features,
PredictionCB callback) override {
predict_distribution_args_.features_ = features;
predict_distribution_args_.callback_ = std::move(callback);
}
struct {
base::UnguessableToken id_;
FeatureVector features_;
std::optional<TargetValue> default_target_;
std::optional<ukm::SourceId> source_id_;
} begin_args_;
struct {
base::UnguessableToken id_;
ObservationCompletion completion_;
} complete_args_;
struct {
base::UnguessableToken id_;
} cancel_args_;
struct {
base::UnguessableToken id_;
std::optional<TargetValue> default_target_;
} update_default_args_;
struct {
FeatureVector features_;
PredictionCB callback_;
} predict_distribution_args_;
};
public:
MojoLearningTaskControllerServiceTest() = default;
~MojoLearningTaskControllerServiceTest() override = default;
void SetUp() override {
std::unique_ptr<FakeLearningTaskController> controller =
std::make_unique<FakeLearningTaskController>();
controller_raw_ = controller.get();
// Add two features.
task_.feature_descriptions.push_back({});
task_.feature_descriptions.push_back({});
// Tell |learning_controller_| to forward to the fake learner impl.
service_ = std::make_unique<MojoLearningTaskControllerService>(
task_, kSourceId, std::move(controller));
}
LearningTask task_;
// Mojo stuff.
base::test::TaskEnvironment task_environment_;
// The learner under test. Must outlive `controller_raw_`
std::unique_ptr<MojoLearningTaskControllerService> service_;
// Raw controller. Owned by `service_`.
raw_ptr<FakeLearningTaskController> controller_raw_ = nullptr;
};
TEST_F(MojoLearningTaskControllerServiceTest, BeginComplete) {
base::UnguessableToken id = base::UnguessableToken::Create();
FeatureVector features = {FeatureValue(123), FeatureValue(456)};
service_->BeginObservation(id, features, std::nullopt);
EXPECT_EQ(id, controller_raw_->begin_args_.id_);
EXPECT_EQ(features, controller_raw_->begin_args_.features_);
EXPECT_FALSE(controller_raw_->begin_args_.default_target_);
EXPECT_TRUE(controller_raw_->begin_args_.source_id_);
EXPECT_EQ(*controller_raw_->begin_args_.source_id_, kSourceId);
ObservationCompletion completion(TargetValue(1234));
service_->CompleteObservation(id, completion);
EXPECT_EQ(id, controller_raw_->complete_args_.id_);
EXPECT_EQ(completion.target_value,
controller_raw_->complete_args_.completion_.target_value);
}
TEST_F(MojoLearningTaskControllerServiceTest, BeginCancel) {
base::UnguessableToken id = base::UnguessableToken::Create();
FeatureVector features = {FeatureValue(123), FeatureValue(456)};
service_->BeginObservation(id, features, std::nullopt);
EXPECT_EQ(id, controller_raw_->begin_args_.id_);
EXPECT_EQ(features, controller_raw_->begin_args_.features_);
EXPECT_FALSE(controller_raw_->begin_args_.default_target_);
service_->CancelObservation(id);
EXPECT_EQ(id, controller_raw_->cancel_args_.id_);
}
TEST_F(MojoLearningTaskControllerServiceTest, BeginWithDefaultTarget) {
base::UnguessableToken id = base::UnguessableToken::Create();
FeatureVector features = {FeatureValue(123), FeatureValue(456)};
TargetValue default_target(987);
service_->BeginObservation(id, features, default_target);
EXPECT_EQ(id, controller_raw_->begin_args_.id_);
EXPECT_EQ(features, controller_raw_->begin_args_.features_);
EXPECT_EQ(default_target, controller_raw_->begin_args_.default_target_);
EXPECT_TRUE(controller_raw_->begin_args_.source_id_);
EXPECT_EQ(*controller_raw_->begin_args_.source_id_, kSourceId);
}
TEST_F(MojoLearningTaskControllerServiceTest, TooFewFeaturesIsIgnored) {
// A FeatureVector with too few elements should be ignored.
base::UnguessableToken id = base::UnguessableToken::Create();
FeatureVector short_features = {FeatureValue(123)};
service_->BeginObservation(id, short_features, std::nullopt);
EXPECT_NE(id, controller_raw_->begin_args_.id_);
EXPECT_EQ(controller_raw_->begin_args_.features_.size(), 0u);
}
TEST_F(MojoLearningTaskControllerServiceTest, TooManyFeaturesIsIgnored) {
// A FeatureVector with too many elements should be ignored.
base::UnguessableToken id = base::UnguessableToken::Create();
FeatureVector long_features = {FeatureValue(123), FeatureValue(456),
FeatureValue(789)};
service_->BeginObservation(id, long_features, std::nullopt);
EXPECT_NE(id, controller_raw_->begin_args_.id_);
EXPECT_EQ(controller_raw_->begin_args_.features_.size(), 0u);
}
TEST_F(MojoLearningTaskControllerServiceTest, CompleteWithoutBeginFails) {
base::UnguessableToken id = base::UnguessableToken::Create();
ObservationCompletion completion(TargetValue(1234));
service_->CompleteObservation(id, completion);
EXPECT_NE(id, controller_raw_->complete_args_.id_);
}
TEST_F(MojoLearningTaskControllerServiceTest, CancelWithoutBeginFails) {
base::UnguessableToken id = base::UnguessableToken::Create();
service_->CancelObservation(id);
EXPECT_NE(id, controller_raw_->cancel_args_.id_);
}
TEST_F(MojoLearningTaskControllerServiceTest, UpdateDefaultTargetToValue) {
base::UnguessableToken id = base::UnguessableToken::Create();
FeatureVector features = {FeatureValue(123), FeatureValue(456)};
service_->BeginObservation(id, features, std::nullopt);
TargetValue default_target(987);
service_->UpdateDefaultTarget(id, default_target);
EXPECT_EQ(id, controller_raw_->update_default_args_.id_);
EXPECT_EQ(default_target,
controller_raw_->update_default_args_.default_target_);
}
TEST_F(MojoLearningTaskControllerServiceTest, UpdateDefaultTargetToNoValue) {
base::UnguessableToken id = base::UnguessableToken::Create();
FeatureVector features = {FeatureValue(123), FeatureValue(456)};
TargetValue default_target(987);
service_->BeginObservation(id, features, default_target);
service_->UpdateDefaultTarget(id, std::nullopt);
EXPECT_EQ(id, controller_raw_->update_default_args_.id_);
EXPECT_EQ(std::nullopt,
controller_raw_->update_default_args_.default_target_);
}
TEST_F(MojoLearningTaskControllerServiceTest, PredictDistribution) {
FeatureVector features = {FeatureValue(123), FeatureValue(456)};
TargetHistogram observed_prediction;
service_->PredictDistribution(
features, base::BindOnce(
[](TargetHistogram* test_storage,
const std::optional<TargetHistogram>& predicted) {
*test_storage = *predicted;
},
&observed_prediction));
EXPECT_EQ(features, controller_raw_->predict_distribution_args_.features_);
EXPECT_FALSE(controller_raw_->predict_distribution_args_.callback_.is_null());
TargetHistogram expected_prediction;
expected_prediction[TargetValue(1)] = 1.0;
expected_prediction[TargetValue(2)] = 2.0;
expected_prediction[TargetValue(3)] = 3.0;
std::move(controller_raw_->predict_distribution_args_.callback_)
.Run(expected_prediction);
EXPECT_EQ(expected_prediction, observed_prediction);
}
} // namespace learning
} // namespace media