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// Copyright 2022 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/contextual_page_actions_model.h"
#include "base/feature_list.h"
#include "base/task/sequenced_task_runner.h"
#include "components/segmentation_platform/internal/metadata/metadata_writer.h"
#include "components/segmentation_platform/public/constants.h"
#include "components/segmentation_platform/public/features.h"
#include "components/segmentation_platform/public/model_provider.h"
#include "components/segmentation_platform/public/proto/model_metadata.pb.h"
namespace segmentation_platform {
namespace {
using proto::SegmentId;
// Label input size
constexpr int kLabelInputSize = 5;
// Default parameters for contextual page actions model.
constexpr SegmentId kSegmentId =
SegmentId::OPTIMIZATION_TARGET_CONTEXTUAL_PAGE_ACTION_PRICE_TRACKING;
constexpr int64_t kOneDayInSeconds = 86400;
constexpr std::array<const char*, kLabelInputSize>
kContextualPageActionModelLabels = {
kContextualPageActionModelLabelDiscounts,
kContextualPageActionModelLabelPriceInsights,
kContextualPageActionModelLabelPriceTracking,
kContextualPageActionModelLabelReaderMode,
kContextualPageActionModelLabelTabGrouping};
MetadataWriter::CustomInput CreateCustomInput(std::string name) {
return MetadataWriter::CustomInput{
.tensor_length = 1,
.fill_policy = proto::CustomInput::FILL_FROM_INPUT_CONTEXT,
.name = name.c_str()};
}
} // namespace
ContextualPageActionsModel::ContextualPageActionsModel()
: DefaultModelProvider(kSegmentId) {}
std::unique_ptr<DefaultModelProvider::ModelConfig>
ContextualPageActionsModel::GetModelConfig() {
proto::SegmentationModelMetadata metadata;
MetadataWriter writer(&metadata);
writer.SetSegmentationMetadataConfig(
proto::TimeUnit::SECOND, /*bucket_duration=*/1,
/*signal_storage_length=*/kOneDayInSeconds,
/*min_signal_collection_length=*/kOneDayInSeconds,
/*result_time_to_live=*/kOneDayInSeconds);
// Add discounts custom input.
proto::CustomInput* discounts_input =
writer.AddCustomInput(CreateCustomInput("discounts_input"));
(*discounts_input->mutable_additional_args())["name"] =
kContextualPageActionModelInputDiscounts;
// Add price insights custom input.
proto::CustomInput* price_insights_input =
writer.AddCustomInput(CreateCustomInput("price_insights_input"));
(*price_insights_input->mutable_additional_args())["name"] =
kContextualPageActionModelInputPriceInsights;
// Add price tracking custom input.
proto::CustomInput* price_tracking_input =
writer.AddCustomInput(CreateCustomInput("price_tracking_input"));
(*price_tracking_input->mutable_additional_args())["name"] =
kContextualPageActionModelInputPriceTracking;
// Add reader mode custom input.
proto::CustomInput* reader_mode_input =
writer.AddCustomInput(CreateCustomInput("reader_mode_input"));
(*reader_mode_input->mutable_additional_args())["name"] =
kContextualPageActionModelInputReaderMode;
// Add tab grouping cusotm input.
proto::CustomInput* tab_grouping_input =
writer.AddCustomInput(CreateCustomInput("tab_grouping_input"));
(*tab_grouping_input->mutable_additional_args())["name"] =
kContextualPageActionModelInputTabGrouping;
// A threshold used to differentiate labels with score zero from non-zero
// values.
const float threshold = 0.1f;
// Set output config, labels, and classifier.
writer.AddOutputConfigForMultiClassClassifier(
kContextualPageActionModelLabels,
/*top_k_outputs=*/1, threshold);
constexpr int kModelVersion = 1;
return std::make_unique<ModelConfig>(std::move(metadata), kModelVersion);
}
void ContextualPageActionsModel::ExecuteModelWithInput(
const ModelProvider::Request& inputs,
ExecutionCallback callback) {
// Invalid inputs.
if (inputs.size() != kLabelInputSize) {
base::SequencedTaskRunner::GetCurrentDefault()->PostTask(
FROM_HERE, base::BindOnce(std::move(callback), std::nullopt));
return;
}
// TODO(haileywang): Use input[4] to input[9] to show share button.
bool has_discounts = inputs[0];
bool has_price_insights = inputs[1];
bool can_track_price = inputs[2];
bool has_reader_mode = inputs[3];
bool has_tab_grouping_suggestions = inputs[4];
// Create response.
ModelProvider::Response response(kLabelInputSize, 0);
response[0] = has_discounts;
response[1] = has_price_insights;
response[2] = can_track_price;
response[3] = has_reader_mode;
response[4] = has_tab_grouping_suggestions;
// TODO(crbug.com/40249852): Set a classifier threshold.
// TODO(shaktisahu): This class needs some rethinking to correctly associate
// the labeled outputs to the flattened vector. Maybe have this method return
// a map of labeled outputs which callls a superclass method internally to
// flatten to the vector. Similar association is needed for the inputs as
// well, but a different topic. Should have same kind of utility in python /
// server side as well.
base::SequencedTaskRunner::GetCurrentDefault()->PostTask(
FROM_HERE, base::BindOnce(std::move(callback), response));
}
} // namespace segmentation_platform
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