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[GPU] Use ov::Tensor intead of ngraph::HostTensor (openvinotoolkit#18925
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89 changes: 89 additions & 0 deletions
89
src/plugins/intel_gpu/include/intel_gpu/runtime/tensor_accessor.hpp
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,89 @@ | ||
| // Copyright (C) 2018-2023 Intel Corporation | ||
| // SPDX-License-Identifier: Apache-2.0 | ||
| // | ||
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| #pragma once | ||
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| #include "openvino/runtime/tensor.hpp" | ||
| #include "tensor_data_accessor.hpp" | ||
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| #include "memory.hpp" | ||
| #include "layout.hpp" | ||
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| namespace cldnn { | ||
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| inline ov::Tensor make_tensor(const layout& l, void* memory_pointer) { | ||
| ov::element::Type et = data_type_to_element_type(l.data_type); | ||
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| return ov::Tensor(et, l.get_shape(), memory_pointer); | ||
| } | ||
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| struct TensorsContainer final { | ||
| using MemoryMap = std::unordered_map<size_t, cldnn::memory::ptr>; | ||
| using TensorsMap = std::unordered_map<size_t, ov::Tensor>; | ||
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| TensorsContainer(const cldnn::stream* stream, const std::map<size_t, cldnn::memory::ptr>& deps_map = {}) | ||
| : m_stream(stream) | ||
| , m_memories(deps_map.begin(), deps_map.end()) { } | ||
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| ~TensorsContainer() { | ||
| for (auto& port : m_locked_memories) { | ||
| m_memories.at(port)->unlock(*m_stream); | ||
| } | ||
| } | ||
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| void emplace(size_t port, cldnn::memory::ptr mem) { | ||
| m_memories.emplace(port, mem); | ||
| } | ||
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| void emplace(size_t port, const ov::Tensor& tensor) { | ||
| auto res = m_tensors.emplace(port, tensor); | ||
| OPENVINO_ASSERT(res.first != m_tensors.end()); | ||
| } | ||
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| template<typename ElementType> | ||
| void emplace(size_t port, std::vector<ElementType>& vector, data_types dt = data_types::i64) { | ||
| ov::Shape shape{vector.size()}; | ||
| auto tensor = make_tensor({shape, dt, format::bfyx}, static_cast<void*>(vector.data())); | ||
| m_tensors.emplace(port, tensor); | ||
| } | ||
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| size_t size() const { return m_tensors.size(); } | ||
| ov::Tensor operator[](std::size_t port) const { | ||
| if (m_memories.count(port) > 0) { | ||
| m_locked_memories.insert(port); | ||
| auto mem = m_memories.at(port); | ||
| auto ptr = mem->lock(*m_stream, cldnn::mem_lock_type::read); | ||
| return make_tensor(mem->get_layout(), ptr); | ||
| } else if (m_tensors.count(port) > 0) { | ||
| return m_tensors.at(port); | ||
| } else { | ||
| OPENVINO_THROW("[GPU] Can't get tensor for ", port, " port!\n"); | ||
| } | ||
| } | ||
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| private: | ||
| const cldnn::stream* m_stream; | ||
| MemoryMap m_memories; | ||
| TensorsMap m_tensors; | ||
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| mutable std::set<size_t> m_locked_memories = {}; | ||
| }; | ||
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| class TensorAccessor final : public ov::ITensorAccessor { | ||
| public: | ||
| explicit TensorAccessor(const TensorsContainer& container) : m_container(container) { } | ||
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| ov::Tensor operator()(size_t port) const override { | ||
| return m_container[port]; | ||
| } | ||
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| private: | ||
| const TensorsContainer& m_container; | ||
| }; | ||
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| inline cldnn::TensorAccessor make_tensor_accessor(const TensorsContainer& c) { | ||
| return cldnn::TensorAccessor(c); | ||
| } | ||
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| } // namespace cldnn |
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