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// Copyright 2023 The Chromium Authors
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
#include "components/segmentation_platform/embedder/default_model/optimization_target_segmentation_dummy.h"
#include <memory>
#include "base/task/sequenced_task_runner.h"
#include "components/segmentation_platform/internal/metadata/metadata_writer.h"
#include "components/segmentation_platform/public/config.h"
#include "components/segmentation_platform/public/proto/aggregation.pb.h"
#include "components/segmentation_platform/public/proto/model_metadata.pb.h"
namespace segmentation_platform {
BASE_FEATURE(kSegmentationPlatformOptimizationTargetSegmentationDummy,
"SegmentationPlatformOptimizationTargetSegmentationDummy",
base::FEATURE_DISABLED_BY_DEFAULT);
namespace {
using proto::SegmentId;
// Default parameters for OptimizationTargetSegmentationDummy model.
constexpr SegmentId kSegmentId =
SegmentId::OPTIMIZATION_TARGET_SEGMENTATION_DUMMY;
constexpr int64_t kModelVersion = 1;
// Store 28 buckets of input data (28 days).
constexpr int64_t kSignalStorageLength = 28;
// Wait until we have 7 days of data.
constexpr int64_t kMinSignalCollectionLength = 7;
// Refresh the result every 7 days.
constexpr int64_t kResultTTLDays = 7;
// InputFeatures.
constexpr std::array<MetadataWriter::UMAFeature, 1> kUMAFeatures = {
// Total amount of times user action was recorded in last 14 days.
MetadataWriter::UMAFeature::FromUserAction("UserActionName", 14),
};
} // namespace
// static
std::unique_ptr<Config> OptimizationTargetSegmentationDummy::GetConfig() {
if (!base::FeatureList::IsEnabled(
kSegmentationPlatformOptimizationTargetSegmentationDummy)) {
return nullptr;
}
auto config = std::make_unique<Config>();
config->segmentation_key = kOptimizationTargetSegmentationDummyKey;
config->segmentation_uma_name = kOptimizationTargetSegmentationDummyUmaName;
config->AddSegmentId(kSegmentId,
std::make_unique<OptimizationTargetSegmentationDummy>());
config->auto_execute_and_cache = false;
return config;
}
OptimizationTargetSegmentationDummy::OptimizationTargetSegmentationDummy()
: DefaultModelProvider(kSegmentId) {}
std::unique_ptr<DefaultModelProvider::ModelConfig>
OptimizationTargetSegmentationDummy::GetModelConfig() {
proto::SegmentationModelMetadata metadata;
MetadataWriter writer(&metadata);
writer.SetDefaultSegmentationMetadataConfig(kMinSignalCollectionLength,
kSignalStorageLength);
// Set output config.
const char kNegativeLabel[] = "Not_OptimizationTargetSegmentationDummy";
writer.AddOutputConfigForBinaryClassifier(
0.5,
/*positive_label=*/kOptimizationTargetSegmentationDummyUmaName,
kNegativeLabel);
writer.AddPredictedResultTTLInOutputConfig(
/*top_label_to_ttl_list=*/{},
/*default_ttl=*/kResultTTLDays, proto::TimeUnit::DAY);
// Set input features.
writer.AddUmaFeatures(kUMAFeatures.data(), kUMAFeatures.size());
// Set output features.
writer.AddUmaFeatures(kUMAFeatures.data(), kUMAFeatures.size(),
/*is_output=*/true);
// Set ondemand model with a trigger.
writer.AddDelayTrigger(0);
return std::make_unique<ModelConfig>(std::move(metadata), kModelVersion);
}
void OptimizationTargetSegmentationDummy::ExecuteModelWithInput(
const ModelProvider::Request& inputs,
ExecutionCallback callback) {
// Invalid inputs.
if (inputs.size() != kUMAFeatures.size()) {
base::SequencedTaskRunner::GetCurrentDefault()->PostTask(
FROM_HERE, base::BindOnce(std::move(callback), std::nullopt));
return;
}
float result = 1;
base::SequencedTaskRunner::GetCurrentDefault()->PostTask(
FROM_HERE,
base::BindOnce(std::move(callback), ModelProvider::Response(1, result)));
}
} // namespace segmentation_platform
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