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/**
* Copyright (c) 2019 Samsung Electronics Co., Ltd All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef __INFERENCE_ENGINE_IMPL_TFLite_H__
#define __INFERENCE_ENGINE_IMPL_TFLite_H__
#include <inference_engine_common.h>
#include "tensorflow2/lite/delegates/gpu/delegate.h"
#include "tensorflow2/lite/kernels/register.h"
#include "tensorflow2/lite/model.h"
#include "tensorflow2/lite/optional_debug_tools.h"
#include <memory>
#include <dlog.h>
/**
* @file inference_engine_tflite_private.h
* @brief This file contains the InferenceTFLite class which
* provide Tensorflow-lite based inference functionality
*/
#ifdef LOG_TAG
#undef LOG_TAG
#endif
#define LOG_TAG "INFERENCE_ENGINE_TFLITE"
using namespace InferenceEngineInterface::Common;
namespace InferenceEngineImpl
{
namespace TFLiteImpl
{
class InferenceTFLite : public IInferenceEngineCommon
{
public:
InferenceTFLite();
~InferenceTFLite();
int SetPrivateData(void *data) override;
int SetTargetDevices(int types) override;
int SetCLTuner(const inference_engine_cltuner *cltuner) final;
int Load(std::vector<std::string> model_paths,
inference_model_format_e model_format) override;
int GetInputTensorBuffers(
std::map<std::string, inference_engine_tensor_buffer> &buffers) override;
int GetOutputTensorBuffers(
std::map<std::string, inference_engine_tensor_buffer> &buffers) override;
int GetInputLayerProperty(
inference_engine_layer_property &property) override;
int GetOutputLayerProperty(
inference_engine_layer_property &property) override;
int SetInputLayerProperty(
inference_engine_layer_property &property) override;
int SetOutputLayerProperty(
inference_engine_layer_property &property) override;
int GetBackendCapacity(inference_engine_capacity *capacity) override;
int Run(std::map<std::string, inference_engine_tensor_buffer> &input_buffers,
std::map<std::string, inference_engine_tensor_buffer> &output_buffers)
override;
private:
int SetInterpreterInfo();
void FillLayerId(std::map<std::string, int>& layerId,
std::map<std::string, inference_engine_tensor_info>& layers,
const std::vector<int>& buffer);
int FillLayer(std::map<std::string, inference_engine_tensor_info>& layers,
std::map<std::string, int>& layerId);
std::unique_ptr<tflite::Interpreter> mInterpreter;
std::unique_ptr<tflite::FlatBufferModel> mFlatBuffModel;
std::vector<void *> mInputData;
std::map<std::string, inference_engine_tensor_info> mInputLayers;
std::map<std::string, inference_engine_tensor_info> mOutputLayers;
std::map<std::string, int> mInputLayerId;
std::map<std::string, int> mOutputLayerId;
std::string mConfigFile;
std::string mWeightFile;
int mTargetTypes;
};
} /* InferenceEngineImpl */
} /* TFLiteImpl */
#endif /* __INFERENCE_ENGINE_IMPL_TFLite_H__ */
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