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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/omnibox/browser/autocomplete_scoring_model_executor.h"
#include <optional>
#include <vector>
#include "base/check_op.h"
#include "base/metrics/histogram_functions.h"
#include "base/notreached.h"
#include "third_party/tflite/src/tensorflow/lite/c/common.h"
#include "third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h"
AutocompleteScoringModelExecutor::AutocompleteScoringModelExecutor() = default;
AutocompleteScoringModelExecutor::~AutocompleteScoringModelExecutor() = default;
bool AutocompleteScoringModelExecutor::Preprocess(
const std::vector<TfLiteTensor*>& input_tensors,
ModelInput input) {
const bool valid_input_size = input.size() == input_tensors.size();
base::UmaHistogramBoolean(
"Omnibox.URLScoringModelExecuted.Preprocess.ValidInputSize",
valid_input_size);
if (!valid_input_size) {
return false;
}
DCHECK_EQ(kTfLiteFloat32, input_tensors[0]->type);
for (size_t i = 0; i < input.size(); ++i) {
std::vector<float> data = {input[i]};
absl::Status status =
tflite::task::core::PopulateTensor<float>(data, input_tensors[i]);
if (!status.ok()) {
return false;
}
}
return true;
}
std::optional<AutocompleteScoringModelExecutor::ModelOutput>
AutocompleteScoringModelExecutor::Postprocess(
const std::vector<const TfLiteTensor*>& output_tensors) {
DCHECK_EQ(1u, output_tensors.size());
DCHECK_EQ(kTfLiteFloat32, output_tensors[0]->type);
DCHECK_EQ(1u, output_tensors[0]->bytes / sizeof(output_tensors[0]->type));
ModelOutput output;
absl::Status status =
tflite::task::core::PopulateVector<float>(output_tensors[0], &output);
if (!status.ok()) {
NOTREACHED();
}
DCHECK_EQ(1u, output.size());
return output;
}
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