75 lines
2.4 KiB
C++
75 lines
2.4 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 "openvino/op/util/assign_base.hpp"
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#include "openvino/op/util/variable.hpp"
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namespace ov {
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namespace op {
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namespace v3 {
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/// \brief Assign operation sets an input value to the variable with `variable_id`
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/// \ingroup ov_ops_cpp_api
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class OPENVINO_API Assign : public util::AssignBase {
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public:
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OPENVINO_OP("Assign", "opset3", util::AssignBase);
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Assign() = default;
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/// \brief Constructs an Assign operation.
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///
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/// \param new_value Node that produces the input tensor.
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/// \param variable_id identifier of the variable to be updated.
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Assign(const Output<Node>& new_value, const std::string& variable_id);
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void validate_and_infer_types() override;
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std::string get_variable_id() const override {
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return m_variable_id;
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}
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std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
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bool visit_attributes(AttributeVisitor& visitor) override;
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private:
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std::string m_variable_id;
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};
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} // namespace v3
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namespace v6 {
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/// \brief Assign operation sets an input value to the variable with `variable_id`
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/// \ingroup ov_ops_cpp_api
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class OPENVINO_API Assign : public util::AssignBase {
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public:
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OPENVINO_OP("Assign", "opset6", util::AssignBase);
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Assign() = default;
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/// \brief Constructs an Assign operation.
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///
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/// \param new_value Node that produces the input tensor.
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/// \param variable Class for storing and synchronizing element types, shapes and
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/// identifiers
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/// between pairs of Assign/ReadValue nodes.
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Assign(const Output<Node>& new_value, const std::shared_ptr<util::Variable>& variable);
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void validate_and_infer_types() override;
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std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
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bool visit_attributes(AttributeVisitor& visitor) override;
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std::string get_variable_id() const override {
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OPENVINO_ASSERT(m_variable, "Variable is not initialized. Variable_id is unavailable");
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return m_variable->get_info().variable_id;
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}
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bool evaluate(TensorVector& outputs,
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const TensorVector& inputs,
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const EvaluationContext& evaluation_context) const override;
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bool has_evaluate() const override;
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bool can_constant_fold(const OutputVector& inputs_values) const override;
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};
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} // namespace v6
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} // namespace op
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} // namespace ov
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