[ONNX] Introduce GraphIterator interface in frontend

src/frontends/onnx/frontend/include/openvino/frontend/onnx/decoder.hpp

@@ -0,0 +1,117 @@
+// Copyright (C) 2018-2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+#pragma once
+
+#include "openvino/core/partial_shape.hpp"
+#include "openvino/core/type/element_type.hpp"
+#include "openvino/frontend/decoder.hpp"
+#include "openvino/frontend/onnx/visibility.hpp"
+
+namespace ov {
+namespace frontend {
+namespace onnx {
+
+struct ONNX_FRONTEND_API TensorMetaInfo {
+    ov::PartialShape m_partial_shape;
+    ov::element::Type m_element_type;
+    const uint8_t* m_tensor_data;
+    size_t m_tensor_data_size;
+    const std::string* m_tensor_name;
+    std::shared_ptr<std::string> m_external_location;
+    bool m_is_raw;
+};
+
+class ONNX_FRONTEND_API DecoderBase : public ov::frontend::DecoderBase {
+public:
+    using Ptr = std::shared_ptr<DecoderBase>;
+    ~DecoderBase() override;
+};
+
+struct ONNX_FRONTEND_API SparseTensorInfo {
+    ov::PartialShape m_partial_shape;
+    ov::frontend::onnx::DecoderBase::Ptr m_values, m_indices;
+};
+
+// DecoderBaseOperation corresponds to operation node to retrieve its attributes and information about input and output
+// tensors
+class ONNX_FRONTEND_API DecoderBaseOperation : public ov::frontend::onnx::DecoderBase {
+public:
+    /// \brief Get input tensor name by index
+    /// Operation nodes are connected between each other by tensors.
+    /// Each tensor must have unique name in a graph.
+    /// The tensor name uniqueness is provided by developer during GraphIterator construction.
+    /// This method returns tensor name that comes to this operation node by input index idx
+    /// If idx is out-of-range, it throws std::exception inherited exception
+    virtual const std::string& get_input_tensor_name(size_t idx) const = 0;
+
+    /// \brief Get input tensor type by index
+    /// If idx is out-of-range, it throws std::exception inherited exception
+    virtual ov::element::Type get_input_tensor_type(size_t idx) const = 0;
+
+    /// \brief Get output tensor name by index
+    /// Operation nodes are connected between each other by tensors.
+    /// Each tensor must have unique name in a graph.
+    /// The tensor name uniqueness is provided by developer during GraphIterator construction.
+    /// This method returns tensor name that outputs by output index idx from this operation
+    /// If idx is out-of-range, it throws std::exception inherited exception
+    virtual const std::string& get_output_tensor_name(size_t idx) const = 0;
+
+    /// \brief Get output tensor type by index
+    /// If idx is out-of-range, it throws std::exception inherited exception
+    virtual ov::element::Type get_output_tensor_type(size_t idx) const = 0;
+
+    /// \brief Get input tensor info
+    /// returns TensorInfo by input idx index that corresponds to a tensor
+    /// (it can correspond to Constant, Parameter or  intermediate tensor connecting a producer and this current node)
+    /// If idx is out-of-range, it throws std::exception inherited exception
+    virtual const TensorMetaInfo& get_input_tensor_info(size_t idx) const = 0;
+
+    /// \brief Get output tensor info
+    /// returns TensorInfo by output idx index that corresponds to a tensor
+    /// (it can correspond to intermediate tensor connecting this current node and a consumer)
+    /// If idx is out-of-range, it throws std::exception inherited exception
+    virtual const TensorMetaInfo& get_output_tensor_info(size_t idx) const = 0;
+
+    /// \brief Get a number of outputs
+    virtual size_t get_output_size() const = 0;
+
+    /// \brief Returns operation's opset version
+    virtual uint64_t get_op_set() const = 0;
+
+    /// \brief Returns operation's domain
+    virtual const std::string& get_domain() const = 0;
+
+    /// \brief Returns true if node has attribute
+    virtual bool has_attribute(const std::string& name) const = 0;
+
+    virtual void experimental_get_internal_structures(const void** node_def) const = 0;
+
+    ~DecoderBaseOperation() override;
+};
+
+// DecoderBaseTensor corresponds to tensor node to retrieve information about type, shapem quantization and sparsity
+// information
+class ONNX_FRONTEND_API DecoderBaseTensor : public ov::frontend::onnx::DecoderBase {
+public:
+    /// \brief Get tensor info
+    virtual const TensorMetaInfo& get_tensor_info() const = 0;
+
+    /// \brief Get input index for tensor
+    /// returns index of this input in the list of inputs in the model
+    /// it must be from 0 to n-1, where n - number of inputs in the model
+    /// if it is not input, returns  -1
+    virtual int64_t get_input_idx() const = 0;
+
+    /// \brief Get output index for tensor
+    /// returns index of this output in the list of outputs in the model
+    /// it must be from 0 to m-1, where m - number of outputs in the model
+    /// if it is not input, returns  -1
+    virtual int64_t get_output_idx() const = 0;
+
+    ~DecoderBaseTensor() override;
+};
+
+}  // namespace onnx
+}  // namespace frontend
+}  // namespace ov

src/frontends/onnx/frontend/include/openvino/frontend/onnx/frontend.hpp

@@ -18,17 +18,25 @@ namespace onnx {
 class ONNX_FRONTEND_API FrontEnd : public ov::frontend::FrontEnd {
 public:
     using Ptr = std::shared_ptr<FrontEnd>;
-    std::shared_ptr<ov::Model> convert(const InputModel::Ptr& model) const override;
+    std::shared_ptr<ov::Model> convert(const ov::frontend::InputModel::Ptr& model) const override;
     void convert(const std::shared_ptr<ov::Model>& partially_converted) const override;
-    std::shared_ptr<ov::Model> convert_partially(const InputModel::Ptr& input_model) const override;
-    std::shared_ptr<ov::Model> decode(const InputModel::Ptr& input_model) const override;
+    std::shared_ptr<ov::Model> convert_partially(const ov::frontend::InputModel::Ptr& input_model) const override;
+    std::shared_ptr<ov::Model> decode(const ov::frontend::InputModel::Ptr& input_model) const override;
     std::string get_name() const override;
     bool supported_impl(const std::vector<ov::Any>& variants) const override;
     void add_extension(const std::shared_ptr<ov::Extension>& extension) override;
     void normalize(const std::shared_ptr<ov::Model>& model) const override;
 
 protected:
-    InputModel::Ptr load_impl(const std::vector<ov::Any>& params) const override;
+    ov::frontend::InputModel::Ptr load_impl(const std::vector<ov::Any>& params) const override;
+
+    void translate_graph(const InputModel::Ptr& model,
+                         bool fail_fast,
+                         bool /* no_conversion */,  // future use
+                         std::shared_ptr<ov::Model>& ov_model) const;
+    std::shared_ptr<ov::Model> convert_unify(const InputModel::Ptr& model) const;
+    std::shared_ptr<ov::Model> convert_partially_unify(const InputModel::Ptr& input_model) const;
+    std::shared_ptr<ov::Model> decode_unify(const InputModel::Ptr& input_model) const;
 
     // m_other_extensions should be the first member here,
     // m_other_extensions can contain SO Extension (holder for other Extensions),

src/frontends/onnx/frontend/include/openvino/frontend/onnx/graph_iterator.hpp

@@ -0,0 +1,56 @@
+// Copyright (C) 2018-2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "openvino/core/runtime_attribute.hpp"
+#include "openvino/frontend/onnx/decoder.hpp"
+#include "openvino/frontend/onnx/visibility.hpp"
+
+namespace ov {
+namespace frontend {
+namespace onnx {
+
+/// Abstract representation for an input model graph that gives nodes in topologically sorted order
+/// It returns decoders for model inputs and outputs (DecoderBaseTensor objects) and for operation nodes
+/// (DecoderBaseOperation objects) DecoderBaseOperation objects for operation nodes must be sorted in topological order
+/// from producing nodes to consumer nodes when `get_decoder()` is called. DecoderBaseTensor objects for inputs and
+/// outputs must be returned first by `get_decoder()` method. Order of DecoderBaseTensor objects for inputs and outputs
+/// defines their order in the original model, i.e. model input index and model output index.
+/// For example, calling `get_decoder()` during iterating GraphIterator returns
+/// DecoderBaseTensor (for input 0), ..., DecoderBaseTensor (for input n-1),
+/// DecoderBaseTensor (for output 0), ..., DecoderBaseTensor (for output m-1),
+/// DecoderBaseOperation (for op 1), ..., DecoderBaseOperation (for op k),
+/// where n - number of inputs in the model, m - number of outputs in the model k - number of operation nodes.
+/// NOTE: constants are ignored and no decoder object is returned for constant.
+class ONNX_FRONTEND_API GraphIterator : ::ov::RuntimeAttribute {
+public:
+    using Ptr = std::shared_ptr<GraphIterator>;
+
+    /// \brief Get a number of operation nodes in the graph
+    virtual size_t size() const = 0;
+
+    /// \brief Set iterator to the start position
+    virtual void reset() = 0;
+
+    /// \brief Move to the next node in the graph
+    virtual void next() = 0;
+
+    /// \brief Returns true if iterator goes out of the range of available nodes
+    virtual bool is_end() const = 0;
+
+    /// \brief Return a pointer to a decoder of the current node
+    virtual std::shared_ptr<DecoderBase> get_decoder() const = 0;
+
+    /// \brief Returns opset version of requested domain, stored in a ModelProto
+    /// If there are no domain found returns -1
+    virtual int64_t get_opset_version(const std::string& domain) const = 0;
+
+    /// \brief Destructor
+    virtual ~GraphIterator();
+};
+
+}  // namespace onnx
+}  // namespace frontend
+}  // namespace ov

src/frontends/onnx/frontend/src/core/decoder.cpp

@@ -0,0 +1,13 @@
+// Copyright (C) 2018-2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "openvino/frontend/onnx/decoder.hpp"
+
+using namespace ov::frontend::onnx;
+
+DecoderBase::~DecoderBase() = default;
+
+DecoderBaseOperation::~DecoderBaseOperation() = default;
+
+DecoderBaseTensor::~DecoderBaseTensor() = default;

src/frontends/onnx/frontend/src/core/decoder_proto.cpp

@@ -0,0 +1,130 @@
+// Copyright (C) 2018-2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "decoder_proto.hpp"
+
+#include <onnx/onnx_pb.h>
+
+#include <fstream>
+#include <openvino/frontend/graph_iterator.hpp>
+
+#include "graph_iterator_proto.hpp"
+#include "openvino/frontend/onnx/graph_iterator.hpp"
+#include "openvino/util/wstring_convert_util.hpp"
+
+namespace ov {
+namespace frontend {
+namespace onnx {
+
+const std::string empty_name = "";
+const std::string DEFAULT_DOMAIN = "";
+const std::string EMPTY_NAME = "";
+const std::string EMPTY_OP_TYPE = "";
+
+ov::Any DecoderProto::get_attribute(const std::string& name) const {
+    for (const auto& attr : m_node->attribute()) {
+        if (!attr.has_name() || attr.name() != name)
+            continue;
+        if (!attr.has_type()) {
+            throw std::runtime_error("Attribute \"" + name + "\" doesn't have a type");
+        }
+        switch (attr.type()) {
+        case AttributeProto_AttributeType::AttributeProto_AttributeType_FLOAT:
+            if (attr.has_f())
+                return attr.f();
+            else
+                throw std::runtime_error("Attribute doesn't have value");
+            break;
+        case AttributeProto_AttributeType::AttributeProto_AttributeType_FLOATS:
+            return std::vector<float>{attr.floats().begin(), attr.floats().end()};
+        case AttributeProto_AttributeType::AttributeProto_AttributeType_INT:
+            if (attr.has_i())
+                return attr.i();
+            else
+                throw std::runtime_error("Attribute doesn't have value");
+            break;
+        case AttributeProto_AttributeType::AttributeProto_AttributeType_INTS:
+            return std::vector<int64_t>{attr.ints().begin(), attr.ints().end()};
+        case AttributeProto_AttributeType::AttributeProto_AttributeType_STRING:
+            if (attr.has_s())
+                return attr.s();
+            else
+                throw std::runtime_error("Attribute doesn't have value");
+            break;
+        case AttributeProto_AttributeType::AttributeProto_AttributeType_STRINGS:
+            return std::vector<std::string>{attr.strings().begin(), attr.strings().end()};
+        case AttributeProto_AttributeType::AttributeProto_AttributeType_GRAPH:
+            if (attr.has_g())
+                return static_cast<ov::frontend::onnx::GraphIterator::Ptr>(
+                    std::make_shared<GraphIteratorProto>(m_parent, &attr.g()));
+            else
+                throw std::runtime_error("Attribute doesn't have value");
+            break;
+        case AttributeProto_AttributeType::AttributeProto_AttributeType_TENSOR:
+            return static_cast<ov::frontend::onnx::DecoderBase::Ptr>(
+                std::make_shared<DecoderProtoTensor>(&attr.t(), m_parent, 0, 0));
+        case AttributeProto_AttributeType::AttributeProto_AttributeType_SPARSE_TENSOR: {
+            ov::frontend::onnx::SparseTensorInfo sparse_tensor_info{};
+            auto& sparse_tensor = attr.sparse_tensor();
+            sparse_tensor_info.m_partial_shape =
+                ov::PartialShape{std::vector<int64_t>(sparse_tensor.dims().begin(), sparse_tensor.dims().end())};
+            if (sparse_tensor.has_values()) {
+                sparse_tensor_info.m_values = static_cast<ov::frontend::onnx::DecoderBase::Ptr>(
+                    std::make_shared<DecoderProtoTensor>(&sparse_tensor.values(), m_parent, 0, 0));
+            }
+            if (sparse_tensor.has_indices()) {
+                sparse_tensor_info.m_indices = static_cast<ov::frontend::onnx::DecoderBase::Ptr>(
+                    std::make_shared<DecoderProtoTensor>(&sparse_tensor.indices(), m_parent, 0, 0));
+            }
+            return sparse_tensor_info;
+        }
+        default:
+            throw std::runtime_error("Unsupported attribute type " +
+                                     ::ONNX_NAMESPACE::AttributeProto_AttributeType_Name(attr.type()));
+        }
+    }
+    return nullptr;
+}
+
+size_t DecoderProto::get_input_size() const {
+    return m_input_info.size();
+}
+
+size_t DecoderProto::get_output_size() const {
+    return m_output_info.size();
+}
+
+void DecoderProto::get_input_node(size_t input_port_idx,
+                                  std::string& producer_name,
+                                  std::string& producer_output_port_name,
+                                  size_t& producer_output_port_index) const {}
+
+const std::string& DecoderProto::get_op_type() const {
+    if (m_node->has_op_type()) {
+        return m_node->op_type();
+    } else {
+        return EMPTY_OP_TYPE;
+    }
+}
+
+const std::string& DecoderProto::get_op_name() const {
+    if (m_node->has_name()) {
+        return m_node->name();
+    } else {
+        return EMPTY_NAME;
+    }
+}
+
+bool DecoderProto::has_attribute(const std::string& name) const {
+    for (const auto& attr : m_node->attribute()) {
+        if (attr.has_name() && attr.name() == name) {
+            return true;
+        }
+    }
+    return false;
+}
+
+}  // namespace onnx
+}  // namespace frontend
+}  // namespace ov