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//
// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "ArmnnDriver.hpp"
#include "ArmnnDriverImpl.hpp"
#include "ModelToINetworkTransformer.hpp"
#include <armnn/ArmNN.hpp>
#include <BufferTracker.h>
#include <CpuExecutor.h>
#include <nnapi/IExecution.h>
#include <nnapi/IPreparedModel.h>
#include <nnapi/Result.h>
#include <nnapi/Types.h>
#include <memory>
#include <tuple>
#include <utility>
#include <vector>
#include <string>
namespace armnn_driver
{
struct CanonicalExecutionContext
{
::android::nn::MeasureTiming measureTimings =
::android::nn::MeasureTiming::NO;
android::nn::TimePoint driverStart;
android::nn::TimePoint driverEnd;
android::nn::TimePoint deviceStart;
android::nn::TimePoint deviceEnd;
};
class ArmnnPreparedModel final : public IPreparedModel,
public std::enable_shared_from_this<ArmnnPreparedModel>
{
public:
ArmnnPreparedModel(armnn::NetworkId networkId,
armnn::IRuntime* runtime,
const Model& model,
const std::string& requestInputsAndOutputsDumpDir,
const bool gpuProfilingEnabled,
Priority priority = Priority::MEDIUM);
ArmnnPreparedModel(armnn::NetworkId networkId,
armnn::IRuntime* runtime,
const std::string& requestInputsAndOutputsDumpDir,
const bool gpuProfilingEnabled,
Priority priority = Priority::MEDIUM,
const bool prepareModelFromCache = false);
virtual ~ArmnnPreparedModel();
ExecutionResult<std::pair<std::vector<OutputShape>, Timing>> execute(
const Request& request,
MeasureTiming measureTiming,
const OptionalTimePoint& deadline,
const OptionalDuration& loopTimeoutDuration) const override;
GeneralResult<std::pair<SyncFence, ExecuteFencedInfoCallback>> executeFenced(
const Request& request,
const std::vector<SyncFence>& waitFor,
MeasureTiming measureTiming,
const OptionalTimePoint& deadline,
const OptionalDuration& loopTimeoutDuration,
const OptionalDuration& timeoutDurationAfterFence) const override;
GeneralResult<android::nn::SharedExecution> createReusableExecution(
const Request& request,
MeasureTiming measureTiming,
const OptionalDuration& loopTimeoutDuration) const override;
GeneralResult<SharedBurst> configureExecutionBurst() const override;
std::any getUnderlyingResource() const override;
/// execute the graph prepared from the request
ErrorStatus ExecuteGraph(
std::shared_ptr<std::vector<android::nn::RunTimePoolInfo>>& pMemPools,
armnn::InputTensors& inputTensors,
armnn::OutputTensors& outputTensors,
CanonicalExecutionContext callback) const;
Priority GetModelPriority() const;
/// Executes this model with dummy inputs (e.g. all zeroes).
/// \return false on failure, otherwise true
bool ExecuteWithDummyInputs(unsigned int numInputs, unsigned int numOutputs) const;
private:
void Init();
ErrorStatus PrepareMemoryForInputs(
armnn::InputTensors& inputs,
const Request& request,
const std::vector<android::nn::RunTimePoolInfo>& memPools) const;
ErrorStatus PrepareMemoryForOutputs(
armnn::OutputTensors& outputs,
std::vector<OutputShape> &outputShapes,
const Request& request,
const std::vector<android::nn::RunTimePoolInfo>& memPools) const;
std::tuple<ErrorStatus, std::vector<OutputShape>, Timing, std::string> PrepareMemoryForIO(
armnn::InputTensors& inputs,
armnn::OutputTensors& outputs,
std::vector<android::nn::RunTimePoolInfo>& memPools,
const Request& request) const;
template <typename TensorBindingCollection>
void DumpTensorsIfRequired(char const* tensorNamePrefix, const TensorBindingCollection& tensorBindings) const;
/// schedule the graph prepared from the request for execution
armnn::NetworkId m_NetworkId;
armnn::IRuntime* m_Runtime;
const Model m_Model;
const std::string& m_RequestInputsAndOutputsDumpDir;
const bool m_GpuProfilingEnabled;
Priority m_ModelPriority;
const bool m_PrepareFromCache;
};
}
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