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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "ArmnnDriver.hpp"
#include "ArmnnDriverImpl.hpp"
#include "RequestThread.hpp"
#include <NeuralNetworks.h>
#include <armnn/ArmNN.hpp>
#include <string>
#include <vector>
namespace armnn_driver
{
template <typename HalVersion>
class ArmnnPreparedModel : public V1_0::IPreparedModel
{
public:
using HalModel = typename HalVersion::Model;
ArmnnPreparedModel(armnn::NetworkId networkId,
armnn::IRuntime* runtime,
const HalModel& model,
const std::string& requestInputsAndOutputsDumpDir,
const bool gpuProfilingEnabled);
virtual ~ArmnnPreparedModel();
virtual Return<ErrorStatus> execute(const Request& request,
const ::android::sp<V1_0::IExecutionCallback>& callback) override;
/// execute the graph prepared from the request
void ExecuteGraph(std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>>& pMemPools,
std::shared_ptr<armnn::InputTensors>& pInputTensors,
std::shared_ptr<armnn::OutputTensors>& pOutputTensors,
const ::android::sp<V1_0::IExecutionCallback>& callback);
/// Executes this model with dummy inputs (e.g. all zeroes).
/// \return false on failure, otherwise true
bool ExecuteWithDummyInputs();
private:
template <typename TensorBindingCollection>
void DumpTensorsIfRequired(char const* tensorNamePrefix, const TensorBindingCollection& tensorBindings);
armnn::NetworkId m_NetworkId;
armnn::IRuntime* m_Runtime;
HalModel m_Model;
// There must be a single RequestThread for all ArmnnPreparedModel objects to ensure serial execution of workloads
// It is specific to this class, so it is declared as static here
static RequestThread<HalVersion> m_RequestThread;
uint32_t m_RequestCount;
const std::string& m_RequestInputsAndOutputsDumpDir;
const bool m_GpuProfilingEnabled;
};
}
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