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//
// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "backendsCommon/TensorHandle.hpp"
#include "WorkingMemHandle.hpp"
#include "Network.hpp"
#include <armnn/backends/IMemoryManager.hpp>
#include <fmt/format.h>
namespace armnn
{
namespace experimental
{
WorkingMemHandle::WorkingMemHandle(NetworkId networkId,
std::vector<InputMemDescriptorCoords> inputLayerInfo,
std::vector<OutputMemDescriptorCoords> outputLayerInfo,
std::vector<WorkingMemDescriptor> workingMemDescriptors,
std::unordered_map<LayerGuid, WorkingMemDescriptor> workingMemDescriptorMap,
std::unique_ptr<MemoryManager> memoryManager,
std::vector<std::pair<std::shared_ptr<TensorMemory>, MemorySource>> tensorMemory,
std::vector<std::unique_ptr<ITensorHandle>> managedTensorHandles,
std::vector<std::unique_ptr<ITensorHandle>> unmanagedTensorHandles)
: m_NetworkId(networkId)
, m_WorkingMemDescriptors(workingMemDescriptors)
, m_WorkingMemDescriptorMap(workingMemDescriptorMap)
, m_MemoryManager(std::move(memoryManager))
, m_TensorMemory(std::move(tensorMemory))
, m_ManagedTensorHandles(std::move(managedTensorHandles))
, m_UnmanagedTensorHandles(std::move(unmanagedTensorHandles))
, m_InputSize(numeric_cast<DifferenceType>(inputLayerInfo.size()))
, m_IsAllocated(false)
{
for (const auto& inputInfo : inputLayerInfo)
{
m_InputValidationMap[inputInfo.m_LayerBindingId] = false;
// Map the LayerBindingIds to the corresponding input ITensorHandle*
auto memDesc = m_WorkingMemDescriptors.at(inputInfo.m_InputSlotCoords[0].first);
ITensorHandle* inputTensorHandle = memDesc.m_Inputs[inputInfo.m_InputSlotCoords[0].second];
m_InputHandleMap[inputInfo.m_LayerBindingId] = inputTensorHandle;
// For every input we need to store all locations from which that input's ITensorHandle* is read.
// So we can, at a later point, swap in and out the ITensorHandle* at that location.
for (auto inputSlot : inputInfo.m_InputSlotCoords)
{
WorkingMemDescriptor& workingMemDescriptor = m_WorkingMemDescriptors.at(inputSlot.first);
auto inputPos = workingMemDescriptor.m_Inputs.begin();
// The DifferenceType of a vector can be unsigned int or signed int depending on the std implementation
// This cast removes any conversion warnings
inputPos += numeric_cast<DifferenceType>(inputSlot.second);
m_InputConnectionMap[inputInfo.m_LayerBindingId].push_back(inputPos);
}
}
size_t bindingIdCount = inputLayerInfo.size();
for (const auto& outputInfo : outputLayerInfo)
{
for (auto bindingId : outputInfo.m_LayerBindingIds)
{
m_OutputValidationMap[bindingId] = false;
// Store the outputSlot position of the tensorhandle
auto outputPos = m_WorkingMemDescriptors.at(outputInfo.m_OutputSlotCoords.first).m_Outputs.begin();
outputPos += numeric_cast<DifferenceType>(outputInfo.m_OutputSlotCoords.second);
m_OutputHandleMap[bindingId] = *outputPos;
}
bindingIdCount += outputInfo.m_LayerBindingIds.size();
// More than one layerBinding id means the tensorhandle is connected to more than one OutputLayer.
// Importing in this case would likely cause unexpected behaviour, so we disallow it.
if (outputInfo.m_LayerBindingIds.size() != 1)
{
continue;
}
// Store the inputSlot positions of the tensorhandle
for (auto outputSlot : outputInfo.m_InputSlotCoords)
{
WorkingMemDescriptor& workingMemDescriptor = m_WorkingMemDescriptors.at(outputSlot.first);
auto inputPos = workingMemDescriptor.m_Inputs.begin();
// The DifferenceType of a vector can be unsigned int or signed int depending on the std implementation
// This cast removes any conversion warnings
inputPos += numeric_cast<DifferenceType>(outputSlot.second);
m_OutputConnectionMap[outputInfo.m_LayerBindingIds[0]].push_back(inputPos);
}
}
m_BindingIdVec = std::vector<LayerBindingId>(bindingIdCount);
IgnoreUnused(m_UnmanagedTensorHandles);
}
void WorkingMemHandle::Allocate()
{
if (m_IsAllocated)
{
return;
}
m_IsAllocated = true;
m_MemoryManager->Allocate();
for (unsigned int i = 0; i < m_TensorMemory.size(); ++i)
{
m_ManagedTensorHandles[i]->Import(m_TensorMemory[i].first->m_Data, m_TensorMemory[i].second);
}
}
void WorkingMemHandle::Free()
{
if (!m_IsAllocated)
{
return;
}
m_IsAllocated = false;
m_MemoryManager->Deallocate();
}
void WorkingMemHandle::MemSyncOutputs()
{
for (auto output : m_OutputConnectionMap)
{
(*output.second[0])->Map(true);
(*output.second[0])->Unmap();
}
}
void WorkingMemHandle::ValidateBindingIds()
{
auto resetInputValidationMap = [&]()
{
for (auto& pair: m_InputValidationMap)
{
pair.second = false;
}
};
auto resetOutputValidationMap = [&]()
{
for (auto& pair: m_OutputValidationMap)
{
pair.second = false;
}
};
std::for_each(m_BindingIdVec.begin(), m_BindingIdVec.begin() + m_InputSize, [&](LayerBindingId id)
{
try
{
bool& isUsed = m_InputValidationMap.at(id);
if (isUsed)
{
resetInputValidationMap();
throw InvalidArgumentException(fmt::format("Duplicate Input LayerBindingId: {}", id));
}
isUsed = true;
}
catch (const std::out_of_range&)
{
resetInputValidationMap();
throw InvalidArgumentException(fmt::format("Unknown Input LayerBindingId: {}", id));
}
});
resetInputValidationMap();
std::for_each(m_BindingIdVec.begin() + m_InputSize, m_BindingIdVec.end(), [&](LayerBindingId id)
{
try
{
bool& isUsed = m_OutputValidationMap.at(id);
if (isUsed)
{
resetOutputValidationMap();
throw InvalidArgumentException(fmt::format("Duplicate Output LayerBindingId: {}", id));
}
isUsed = true;
}
catch (const std::out_of_range&)
{
resetOutputValidationMap();
throw InvalidArgumentException(fmt::format("Unknown Output LayerBindingId: {}", id));
}
});
resetOutputValidationMap();
}
} // end experimental namespace
} // end armnn namespace
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