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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 "content/browser/preloading/preloading_prediction.h"
#include "base/metrics/histogram_functions.h"
#include "base/strings/strcat.h"
#include "content/public/browser/page.h"
#include "services/metrics/public/cpp/metrics_utils.h"
#include "services/metrics/public/cpp/ukm_builders.h"
#include "services/metrics/public/cpp/ukm_recorder.h"
namespace content {
PreloadingPrediction::PreloadingPrediction(
PreloadingPredictor predictor,
PreloadingConfidence confidence,
ukm::SourceId triggered_primary_page_source_id,
PreloadingURLMatchCallback url_match_predicate)
: predictor_type_(predictor),
triggered_primary_page_source_id_(triggered_primary_page_source_id),
url_match_predicate_(std::move(url_match_predicate)),
confidence_(confidence) {}
PreloadingPrediction::~PreloadingPrediction() = default;
PreloadingPrediction::PreloadingPrediction(PreloadingPrediction&&) = default;
PreloadingPrediction& PreloadingPrediction::operator=(PreloadingPrediction&&) =
default;
void PreloadingPrediction::RecordPreloadingPredictionUKMs(
ukm::SourceId navigated_page_source_id,
std::optional<double> sampling_likelihood) {
ukm::UkmRecorder* ukm_recorder = ukm::UkmRecorder::Get();
const int sampling_likelihood_per_million =
sampling_likelihood ? static_cast<int>(1'000'000 * *sampling_likelihood)
: 1'000'000;
constexpr double kBucketSpacing = 1.3;
const int sampling_amount_bucket = ukm::GetExponentialBucketMin(
1'000'000 - sampling_likelihood_per_million, kBucketSpacing);
// Don't log when the source id is invalid.
if (navigated_page_source_id != ukm::kInvalidSourceId) {
ukm::builders::Preloading_Prediction builder(navigated_page_source_id);
builder.SetPreloadingPredictor(predictor_type_.ukm_value())
.SetConfidence(static_cast<int>(confidence_))
.SetAccuratePrediction(is_accurate_prediction_)
.SetSamplingAmount(sampling_amount_bucket);
if (time_to_next_navigation_) {
builder.SetTimeToNextNavigation(ukm::GetExponentialBucketMinForCounts1000(
time_to_next_navigation_->InMilliseconds()));
}
builder.Record(ukm_recorder);
}
if (triggered_primary_page_source_id_ != ukm::kInvalidSourceId) {
ukm::builders::Preloading_Prediction_PreviousPrimaryPage builder(
triggered_primary_page_source_id_);
builder.SetPreloadingPredictor(predictor_type_.ukm_value())
.SetConfidence(static_cast<int>(confidence_))
.SetAccuratePrediction(is_accurate_prediction_)
.SetSamplingAmount(sampling_amount_bucket);
if (time_to_next_navigation_) {
builder.SetTimeToNextNavigation(ukm::GetExponentialBucketMinForCounts1000(
time_to_next_navigation_->InMilliseconds()));
}
builder.Record(ukm_recorder);
}
}
void PreloadingPrediction::SetIsAccuratePrediction(const GURL& navigated_url) {
DCHECK(url_match_predicate_);
// `PreloadingAttemptImpl::SetIsAccurateTriggering` is called during
// `WCO::DidStartNavigation`.
if (!time_to_next_navigation_) {
time_to_next_navigation_ = elapsed_timer_.Elapsed();
}
// Use the predicate to match the URLs as the matching logic varies for each
// predictor.
is_accurate_prediction_ |= url_match_predicate_.Run(navigated_url);
}
ExperimentalPreloadingPrediction::ExperimentalPreloadingPrediction(
std::string_view name,
PreloadingURLMatchCallback url_match_predicate,
float score,
float min_score,
float max_score,
size_t buckets)
: name_(name),
buckets_(buckets),
normalized_score_((score - min_score) / (max_score - min_score)),
url_match_predicate_(std::move(url_match_predicate)) {
CHECK_GT(max_score, min_score);
CHECK_LT(buckets, 101u);
}
void ExperimentalPreloadingPrediction::SetIsAccuratePrediction(
const GURL& navigated_url) {
is_accurate_prediction_ = url_match_predicate_.Run(navigated_url);
}
ExperimentalPreloadingPrediction::~ExperimentalPreloadingPrediction() = default;
ExperimentalPreloadingPrediction::ExperimentalPreloadingPrediction(
ExperimentalPreloadingPrediction&&) = default;
ExperimentalPreloadingPrediction& ExperimentalPreloadingPrediction::operator=(
ExperimentalPreloadingPrediction&&) = default;
void ExperimentalPreloadingPrediction::RecordToUMA() const {
const auto uma_experimental_prediction =
base::StrCat({"Preloading.Experimental.", PredictorName(), ".",
IsAccuratePrediction() ? "Positive" : "Negative"});
base::UmaHistogramExactLinear(uma_experimental_prediction,
normalized_score_ * buckets_, buckets_ + 1);
}
ModelPredictionTrainingData::ModelPredictionTrainingData(
OutcomeCallback on_record_outcome,
PreloadingURLMatchCallback url_match_predicate)
: on_record_outcome_(std::move(on_record_outcome)),
url_match_predicate_(std::move(url_match_predicate)) {}
ModelPredictionTrainingData::~ModelPredictionTrainingData() = default;
ModelPredictionTrainingData::ModelPredictionTrainingData(
ModelPredictionTrainingData&&) = default;
ModelPredictionTrainingData& ModelPredictionTrainingData::operator=(
ModelPredictionTrainingData&&) = default;
void ModelPredictionTrainingData::SetIsAccuratePrediction(
const GURL& navigated_url) {
is_accurate_prediction_ = url_match_predicate_.Run(navigated_url);
}
void ModelPredictionTrainingData::Record(
std::optional<double> sampling_likelihood) {
std::move(on_record_outcome_)
.Run(sampling_likelihood, is_accurate_prediction_);
}
} // namespace content
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