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// Copyright (C) 2018-2025 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#pragma once
#include "openvino/frontend/extension/conversion.hpp"
#include "openvino/frontend/extension/telemetry.hpp"
#include "openvino/frontend/frontend.hpp"
#include "openvino/frontend/pytorch/node_context.hpp"
#include "openvino/frontend/pytorch/visibility.hpp"
namespace ov {
namespace frontend {
namespace pytorch {
class PYTORCH_FRONTEND_API FrontEnd : public ov::frontend::FrontEnd {
public:
using Ptr = std::shared_ptr<FrontEnd>;
FrontEnd();
/// \brief Completely convert and normalize entire Model, throws if it is not possible
/// \param model Input model
/// \return fully converted OV Model
std::shared_ptr<Model> convert(const ov::frontend::InputModel::Ptr& model) const override;
/// \brief Completely convert the remaining, not converted part of a Model.
/// \param partiallyConverted partially converted OV Model
void convert(const std::shared_ptr<Model>& partiallyConverted) const override;
/// \brief Convert only those parts of the model that can be converted leaving others
/// as-is. Converted parts are not normalized by additional transformations; normalize
/// function or another form of convert function should be called to finalize the
/// conversion process.
/// \param model Input model
/// \return partially converted OV Model
std::shared_ptr<Model> convert_partially(const InputModel::Ptr& model) const override;
/// \brief Convert operations with one-to-one mapping with decoding nodes.
/// Each decoding node is an OV node representing a single FW operation node with
/// all attributes represented in FW-independent way.
/// \param model Input model
/// \return OV Model after decoding
std::shared_ptr<Model> decode(const InputModel::Ptr& model) const override;
/// \brief Runs normalization passes on Model that was loaded with partial conversion
/// \param Model partially converted OV Model
void normalize(const std::shared_ptr<ov::Model>& model) const override;
/// \brief Gets name of this FrontEnd. Can be used by clients
/// if frontend is selected automatically by FrontEndManager::load_by_model
/// \return Paddle frontend name.
std::string get_name() const override {
return "pytorch";
}
/// \brief Register base extension in the FrontEnd
/// \param extension base extension
void add_extension(const std::shared_ptr<ov::Extension>& extension) override;
protected:
bool supported_impl(const std::vector<ov::Any>& variants) const override;
ov::frontend::InputModel::Ptr load_impl(const std::vector<ov::Any>& variants) const override;
std::unordered_map<std::string, CreatorFunction> get_supported_ops(
const ov::frontend::InputModel::Ptr& model) const;
std::map<std::string, CreatorFunction> m_op_extension_translators;
std::vector<ConversionExtensionBase::Ptr> m_conversion_extensions;
TelemetryExtension::Ptr m_telemetry;
};
} // namespace pytorch
} // namespace frontend
} // namespace ov