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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.
#ifndef COMPONENTS_OMNIBOX_BROWSER_AUTOCOMPLETE_SCORING_MODEL_EXECUTOR_H_
#define COMPONENTS_OMNIBOX_BROWSER_AUTOCOMPLETE_SCORING_MODEL_EXECUTOR_H_
#include <optional>
#include <vector>
#include "components/optimization_guide/core/inference/base_model_executor.h"
#include "third_party/tflite/src/tensorflow/lite/c/common.h"
// Implements BaseModelExecutor to execute models with float vector input and
// output. Input represents scoring signals associated one autocomplete match
// candidate. Output is between 0 and 1, which represents the probability for
// the match candidate to be clicked. Preprocesses input float vectors for model
// executor. Postprocesses model executor output as float vectors.
class AutocompleteScoringModelExecutor
: public optimization_guide::BaseModelExecutor<std::vector<float>,
const std::vector<float>&> {
public:
using ModelInput = const std::vector<float>&;
using ModelOutput = std::vector<float>;
AutocompleteScoringModelExecutor();
~AutocompleteScoringModelExecutor() override;
// Disallow copy/assign.
AutocompleteScoringModelExecutor(const AutocompleteScoringModelExecutor&) =
delete;
AutocompleteScoringModelExecutor& operator=(
const AutocompleteScoringModelExecutor&) = delete;
protected:
// optimization_guide::BaseModelExecutor:
//
// The autocomplete scoring model has multiple inputs, one for each input
// signal, and each should be added to a separate input tensor.
bool Preprocess(const std::vector<TfLiteTensor*>& input_tensors,
ModelInput input) override;
std::optional<ModelOutput> Postprocess(
const std::vector<const TfLiteTensor*>& output_tensors) override;
};
#endif // COMPONENTS_OMNIBOX_BROWSER_AUTOCOMPLETE_SCORING_MODEL_EXECUTOR_H_
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