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[CPU] StringMemory for the output tensor in the InferRequest #21746

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merged 1 commit into from
Dec 19, 2023
Merged

[CPU] StringMemory for the output tensor in the InferRequest #21746

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18 changes: 18 additions & 0 deletions src/plugins/intel_cpu/src/cpu_memory.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -60,6 +60,9 @@ Memory::Memory(const dnnl::engine& eng, MemoryDescPtr desc, const void* data, bo
m_pMemDesc(desc),
m_mgrHandle(std::make_shared<DnnlMemoryMngr>(make_unique<MemoryMngrWithReuse>()), this),
dnnlMemHandle(this) {
if (desc->getPrecision() == element::string) {
OPENVINO_THROW("[CPU] Memory object cannot be created for string data.");
}
create(m_pMemDesc, data, pads_zeroing);
}

Expand All @@ -68,6 +71,9 @@ Memory::Memory(const dnnl::engine& eng, const MemoryDesc& desc, const void* data

Memory::Memory(const dnnl::engine& eng, MemoryDescPtr desc, MemoryMngrPtr mngr) :
m_eng(eng), m_pMemDesc(desc), m_mgrHandle(mngr, this), dnnlMemHandle(this) {
if (desc->getPrecision() == element::string) {
OPENVINO_THROW("[CPU] Memory object can't be created for string data.");
}
bool memAllocated = m_mgrHandle->getRawPtr();

create(desc, nullptr, !memAllocated);
Expand Down Expand Up @@ -105,6 +111,9 @@ void Memory::create(MemoryDescPtr desc, const void* data, bool pads_zeroing) {
}

void Memory::load(const IMemory& src, bool ftz) const {
if (src.getDesc().getPrecision() == element::string) {
OPENVINO_THROW("[CPU] Memory object cannot load string data.");
}
transferData(src, *this, ftz);
}

Expand All @@ -115,6 +124,9 @@ void Memory::nullify() {
}

void Memory::redefineDesc(MemoryDescPtr desc) {
if (desc->getPrecision() == element::string) {
OPENVINO_THROW("[CPU] Memory object cannot accept a descriptor with a string type.");
}
if (!desc->hasDefinedMaxSize()) {
OPENVINO_THROW("Can not reset descriptor, memory upper bound is unknown.");
}
Expand Down Expand Up @@ -445,6 +457,9 @@ void DnnlMemoryMngr::notifyUpdate() {

StaticMemory::StaticMemory(const dnnl::engine& eng, MemoryDescPtr desc, const void* data, bool pads_zeroing) :
m_eng(eng), m_pMemDesc(desc) {
if (desc->getPrecision() == element::string) {
OPENVINO_THROW("[CPU] StaticMemory object cannot be created for string data.");
}
if (!m_pMemDesc->isDefined()) {
OPENVINO_THROW("Can not create StaticMemory object. The memory desc is undefined");
}
Expand Down Expand Up @@ -511,6 +526,9 @@ void StaticMemory::redefineDesc(MemoryDescPtr desc) {
}

void StaticMemory::load(const IMemory& src, bool ftz) const {
if (src.getDesc().getPrecision() == element::string) {
OPENVINO_THROW("[CPU] StaticMemory cannot load string data.");
}
transferData(src, *this, ftz);
}

Expand Down
57 changes: 36 additions & 21 deletions src/plugins/intel_cpu/src/infer_request.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -175,14 +175,15 @@ std::vector<ov::ProfilingInfo> SyncInferRequest::get_profiling_info() const {
}

static inline void change_edge_ptr(const EdgePtr& edge, ov::SoPtr<ov::ITensor>& tensor) {
auto& mem = edge->getMemory();
auto mem = edge->getMemoryPtr();
OPENVINO_ASSERT(mem != nullptr, "Edge with name '", edge->name(), "' doesn't have allocated memory object.");

if (tensor->get_element_type() == element::string) {
auto memMngr = dynamic_cast<const StringMemory &>(mem).getStringMemoryMngrPtr();
auto memMngr = dynamic_cast<StringMemory *>(mem.get())->getStringMemoryMngrPtr();
OPENVINO_ASSERT(memMngr);
memMngr->setExtBuff(tensor->data<OvString>(), tensor->get_size());
memMngr->setExtBuff(tensor->data<StringMemory::OvString>(), tensor->get_size());
} else {
auto memMngr = mem.getMemoryMngr();
auto memMngr = mem->getMemoryMngr();
OPENVINO_ASSERT(memMngr);
memMngr->setExtBuff(tensor->data(), tensor->get_byte_size());
}
Expand Down Expand Up @@ -546,26 +547,40 @@ void SyncInferRequest::init_tensor(const std::string& name) {

if (!tensor) {
ov::Shape tensor_shape;
const auto model_prec = port.get_element_type();
if (isDynamic) {
const auto model_prec = port.get_element_type();
const auto graph_prec =
output->second->getParentEdgesAtPort(0)[0]->getMemory().getDesc().getPrecision();
OutputControlBlock control_block{model_prec, Shape{shape}};

DEBUG_LOG(name,
", tensor ",
control_block.tensor(),
", memmngr ",
control_block.tensor()->get_memory()->getMemoryMngr(),
"memory object ",
control_block.tensor()->get_memory().get());

tensor = control_block.tensor();
if (model_prec == graph_prec)
m_outputControlBlocks.emplace(std::make_pair(name, std::move(control_block)));
if (model_prec == element::string) {
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It looks like we need to incapsulate this logic into OutputControlBlock ctor to have unified code here.
Anyway since current solution solves the issue we can refactor in follow-up PR

VectorDims memDims;
auto c_shape = Shape{shape};
for (auto&& dim : c_shape.getDims()) {
memDims.push_back(dim != Shape::UNDEFINED_DIM ? dim : 0);
}

dnnl::engine eng(dnnl::engine::kind::cpu, 0);
CpuBlockedMemoryDescPtr desc = std::make_shared<CpuBlockedMemoryDesc>(model_prec, Shape{memDims});
auto memory = std::make_shared<StringMemory>(eng, desc);

tensor = std::make_shared<Tensor>(memory);
} else {
const auto graph_prec =
output->second->getParentEdgesAtPort(0)[0]->getMemory().getDesc().getPrecision();
OutputControlBlock control_block{model_prec, Shape{shape}};

DEBUG_LOG(name,
", tensor ",
control_block.tensor(),
", memmngr ",
control_block.tensor()->get_memory()->getMemoryMngr(),
"memory object ",
control_block.tensor()->get_memory().get());

tensor = control_block.tensor();
if (model_prec == graph_prec)
m_outputControlBlocks.emplace(std::make_pair(name, std::move(control_block)));
}
} else {
tensor_shape = shape.to_shape();
tensor = ov::make_tensor(port.get_element_type(), tensor_shape);
tensor = ov::make_tensor(model_prec, tensor_shape);
}
ov::ISyncInferRequest::set_tensor(port, tensor);
} else {
Expand Down
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