50 lines
1.6 KiB
C++
50 lines
1.6 KiB
C++
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// Copyright (C) 2018-2025 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#pragma once
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#include <memory>
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#include <vector>
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#include "openvino/pass/pass.hpp"
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namespace ov {
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namespace pass {
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/**
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* @brief The transformation finds all TensorIterator/Loop layers in the network,
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* processes all back edges that describe a connection between Result and Parameter
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* of the TensorIterator/Loop bodies,and inserts ReadValue and Assign layers at the
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* input and output corresponding to this back edge.
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* Supported platform: CPU.
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*
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* The example below describes the changes made by the transformation
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* [] - TensorIterator body
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* () - new layer
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* BE - back-edge
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*
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* before applying the transformation:
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* -> input1[BE_1 -> Parameter -> Layers ... -> Result -> BE_1 ]output1->
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*
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* after applying the transformation:
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* ->(ReadValue)-> input1[BE_1 ->Parameter->Layers ...->Result->BE_1]output1 ->(Assign)
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* \
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* ->...
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* After applying the transformation, the resulting network can be inferred
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* step by step, the states will store between inferences.
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* @ingroup ov_pass_cpp_api
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*/
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class OPENVINO_API LowLatency2 : public ModelPass {
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public:
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OPENVINO_MODEL_PASS_RTTI("LowLatency2");
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explicit LowLatency2(bool use_const_initializer = true) : m_use_const_initializer(use_const_initializer) {}
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bool run_on_model(const std::shared_ptr<ov::Model>& m) override;
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private:
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bool m_use_const_initializer;
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};
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} // namespace pass
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} // namespace ov
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