Moved operations G-L to ov namespace

ngraph/core/include/ngraph/graph_util.hpp

@@ -18,11 +18,18 @@
 #include "ngraph/function.hpp"
 #include "ngraph/node.hpp"
 
+namespace ov {
+namespace op {
+namespace v0 {
+class Parameter;
+}
+}  // namespace op
+}  // namespace ov
 namespace ngraph {
 
 namespace op {
 namespace v0 {
-class Parameter;
+using ov::op::v0::Parameter;
 }
 }  // namespace op
 

ngraph/core/include/ngraph/node.hpp

@@ -38,6 +38,13 @@
 #include "ngraph/variant.hpp"
 #include "openvino/core/node.hpp"
 
+namespace ov {
+namespace op {
+namespace v0 {
+class Result;
+}
+}  // namespace op
+}  // namespace ov
 namespace ngraph {
 
 using ov::Node;
@@ -52,7 +59,7 @@ using HostTensorVector = std::vector<HostTensorPtr>;
 namespace op {
 
 namespace v0 {
-class Result;
+using ov::op::v0::Result;
 }
 }  // namespace op
 

ngraph/core/include/ngraph/op/gather.hpp

@@ -5,76 +5,18 @@
 #pragma once
 
 #include "ngraph/op/util/gather_base.hpp"
+#include "openvino/op/gather.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v1 {
-/// \brief Gather slices from axis of data according to indices
-class NGRAPH_API Gather : public op::util::GatherBase {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    static const int64_t AXIS_NOT_SET_VALUE = std::numeric_limits<int64_t>::max();
-    Gather() = default;
-    /// \param data The tensor from which slices are gathered
-    /// \param indices Tensor with indexes to gather
-    /// \param axis The tensor is a dimension index to gather data from
-    Gather(const Output<Node>& params, const Output<Node>& indices, const Output<Node>& axis);
-
-    bool visit_attributes(AttributeVisitor& visitor) override;
-    int64_t get_axis() const override;
-
-    std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-};
+using ov::op::v1::Gather;
 }  // namespace v1
-
 namespace v7 {
-/// \brief Gather slices from axis of data according to indices
-class NGRAPH_API Gather : public op::util::GatherBase {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    Gather() = default;
-
-    /// \param data The tensor from which slices are gathered
-    /// \param indices Tensor with indexes to gather
-    /// \param axis The tensor is a dimension index to gather data from
-    /// \param batch_dims The number of batch dimension in data and indices tensors.
-    /// If batch_dims = 0 Gather v7 is identical to Gather v1.
-    Gather(const Output<Node>& data,
-           const Output<Node>& indices,
-           const Output<Node>& axis,
-           const int64_t batch_dims = 0);
-
-    bool visit_attributes(AttributeVisitor& visitor) override;
-    void validate_and_infer_types() override;
-    int64_t get_batch_dims() const;
-
-    std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-};
+using ov::op::v7::Gather;
 }  // namespace v7
-
 namespace v8 {
-/// \brief Gather slices from axis of data according to indices. Negative indices
-/// are supported and indicate reverse indexing from the end
-class NGRAPH_API Gather : public op::util::GatherBase {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    Gather() = default;
-
-    /// \param data The tensor from which slices are gathered
-    /// \param indices Tensor with indexes to gather
-    /// \param axis The tensor is a dimension index to gather data from
-    /// \param batch_dims The number of batch dimension in data and indices tensors.
-    Gather(const Output<Node>& data,
-           const Output<Node>& indices,
-           const Output<Node>& axis,
-           const int64_t batch_dims = 0);
-
-    bool visit_attributes(AttributeVisitor& visitor) override;
-    void validate_and_infer_types() override;
-    int64_t get_batch_dims() const;
-
-    std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-};
+using ov::op::v8::Gather;
 }  // namespace v8
 }  // namespace op
 }  // namespace ngraph

ngraph/core/include/ngraph/op/gather_elements.hpp

@@ -5,35 +5,12 @@
 #pragma once
 
 #include "ngraph/op/op.hpp"
+#include "openvino/op/gather_elements.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v6 {
-/// \brief GatherElements operation
-///
-class NGRAPH_API GatherElements : public Op {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    GatherElements() = default;
-
-    /// \brief Constructs a GatherElements operation.
-    ///
-    /// \param data Node producing data that are gathered
-    /// \param indices Node producing indices by which the operation gathers elements
-    /// \param axis specifies axis along which indices are specified
-    GatherElements(const Output<Node>& data, const Output<Node>& indices, const int64_t axis);
-
-    void validate_and_infer_types() override;
-    bool visit_attributes(AttributeVisitor& visitor) override;
-    std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-
-    int64_t get_axis() const {
-        return m_axis;
-    }
-
-private:
-    int64_t m_axis;
-};
+using ov::op::v6::GatherElements;
 }  // namespace v6
 }  // namespace op
 }  // namespace ngraph

ngraph/core/include/ngraph/op/gather_nd.hpp

@@ -5,36 +5,12 @@
 #pragma once
 
 #include "ngraph/op/op.hpp"
+#include "openvino/op/gather_nd.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v5 {
-/// \brief GatherND operation
-///
-class NGRAPH_API GatherND : public Op {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    GatherND() = default;
-
-    /// \brief Constructs a GatherND operation.
-    ///
-    /// \param data Node producing data that are gathered
-    /// \param indices Node producing indices by which the operation gathers elements
-    /// or slices from data
-    /// \param batch_dims Specifies a number of batch dimensions
-    GatherND(const Output<Node>& data, const Output<Node>& indices, const size_t batch_dims = 0);
-
-    void validate_and_infer_types() override;
-    bool visit_attributes(AttributeVisitor& visitor) override;
-    virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-
-    size_t get_batch_dims() const {
-        return m_batch_dims;
-    }
-
-private:
-    size_t m_batch_dims;
-};
+using ov::op::v5::GatherND;
 }  // namespace v5
 }  // namespace op
 }  // namespace ngraph

ngraph/core/include/ngraph/op/gather_tree.hpp

@@ -5,34 +5,12 @@
 #pragma once
 
 #include "ngraph/op/op.hpp"
+#include "openvino/op/gather_tree.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v1 {
-/// \brief Generates the complete beams from the ids per each step and the parent beam
-/// ids.
-class NGRAPH_API GatherTree : public Op {
-public:
-    NGRAPH_RTTI_DECLARATION;
-
-    GatherTree() = default;
-    /// \param step_ids     Tensor of shape [MAX_TIME, BATCH_SIZE, BEAM_WIDTH] with
-    ///                     indices from per each step
-    /// \param parent_idx   Tensor of shape [MAX_TIME, BATCH_SIZE, BEAM_WIDTH] with
-    ///                     parent beam indices
-    /// \param max_seq_len  Tensor of shape [BATCH_SIZE] with maximum lengths for each
-    ///                     sequence in the batch
-    /// \param end_token    Tensor of shape [MAX_TIME, BATCH_SIZE, BEAM_WIDTH]
-    GatherTree(const Output<Node>& step_ids,
-               const Output<Node>& parent_idx,
-               const Output<Node>& max_seq_len,
-               const Output<Node>& end_token);
-
-    bool visit_attributes(AttributeVisitor& visitor) override;
-    void validate_and_infer_types() override;
-
-    virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-};
+using ov::op::v1::GatherTree;
 }  // namespace v1
 }  // namespace op
 }  // namespace ngraph

ngraph/core/include/ngraph/op/gelu.hpp

@@ -7,81 +7,19 @@
 #include "ngraph/node.hpp"
 #include "ngraph/op/op.hpp"
 #include "ngraph/op/util/unary_elementwise_arithmetic.hpp"
+#include "openvino/op/gelu.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v0 {
-/// \brief Gaussian Error Linear Unit
-/// f(x) = 0.5 * x * (1 + erf( x / sqrt(2) )
-class NGRAPH_API Gelu : public Op {
-public:
-    NGRAPH_RTTI_DECLARATION;
-
-    Gelu();
-    /// \brief Constructs a Gelu operation.
-    ///
-    /// \param data Input tensor
-    Gelu(const Output<Node>& data);
-
-    bool visit_attributes(AttributeVisitor& visitor) override;
-
-    void validate_and_infer_types() override;
-
-    std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-};
+using ov::op::v0::Gelu;
 }  // namespace v0
 using v0::Gelu;
 
-/// \brief Specifies the approximation to calculate Gelu
-enum class GeluApproximationMode { TANH, ERF };
-NGRAPH_API std::ostream& operator<<(std::ostream& s, const GeluApproximationMode& type);
+using ov::op::GeluApproximationMode;
 
 namespace v7 {
-/// \brief Gaussian Error Linear Unit
-/// f(x) = 0.5 * x * (1 + erf( x / sqrt(2) ) for "approximation" = "erf"
-/// f(x) = 0.5 * x * (1 + tanh([sqrt(2 / pi)] * [x + 0.044715^3]) for "approximation" =
-/// "tanh"
-class NGRAPH_API Gelu : public util::UnaryElementwiseArithmetic {
-public:
-    NGRAPH_RTTI_DECLARATION;
-
-    Gelu() = default;
-    /// \brief Constructs a Gelu operation.
-    ///
-    /// \param data Input tensor
-    /// \param mode Approximation mode
-    Gelu(const Output<Node>& data, GeluApproximationMode mode = GeluApproximationMode::ERF);
-
-    bool visit_attributes(AttributeVisitor& visitor) override;
-
-    void validate_and_infer_types() override;
-
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    bool has_evaluate() const override;
-
-    std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-
-    GeluApproximationMode get_approximation_mode() const;
-
-private:
-    GeluApproximationMode m_approximation_mode = GeluApproximationMode::ERF;
-};
+using ov::op::v7::Gelu;
 }  // namespace v7
 }  // namespace op
 }  // namespace ngraph
-
-namespace ov {
-template <>
-class NGRAPH_API AttributeAdapter<ngraph::op::GeluApproximationMode>
-    : public EnumAttributeAdapterBase<ngraph::op::GeluApproximationMode> {
-public:
-    AttributeAdapter(ngraph::op::GeluApproximationMode& value)
-        : EnumAttributeAdapterBase<ngraph::op::GeluApproximationMode>(value) {}
-
-    static constexpr DiscreteTypeInfo type_info{"AttributeAdapter<op::GeluApproximationMode>", 0};
-    const DiscreteTypeInfo& get_type_info() const override {
-        return type_info;
-    }
-};
-
-}  // namespace ov

ngraph/core/include/ngraph/op/greater.hpp

@@ -5,29 +5,12 @@
 #pragma once
 
 #include "ngraph/op/util/binary_elementwise_comparison.hpp"
+#include "openvino/op/greater.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v1 {
-/// \brief Elementwise greater-than operation.
-class NGRAPH_API Greater : public util::BinaryElementwiseComparison {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    /// \brief Constructs a greater-than operation.
-    Greater() : util::BinaryElementwiseComparison(AutoBroadcastSpec::NUMPY) {}
-    /// \brief Constructs a greater-than operation.
-    ///
-    /// \param arg0 Node that produces the first input tensor.
-    /// \param arg1 Node that produces the second input tensor.
-    /// \param auto_broadcast Auto broadcast specification
-    Greater(const Output<Node>& arg0,
-            const Output<Node>& arg1,
-            const AutoBroadcastSpec& auto_broadcast = AutoBroadcastSpec(AutoBroadcastType::NUMPY));
-
-    virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    bool has_evaluate() const override;
-};
+using ov::op::v1::Greater;
 }  // namespace v1
 }  // namespace op
 }  // namespace ngraph

ngraph/core/include/ngraph/op/greater_eq.hpp

@@ -5,29 +5,12 @@
 #pragma once
 
 #include "ngraph/op/util/binary_elementwise_comparison.hpp"
+#include "openvino/op/greater_eq.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v1 {
-/// \brief Elementwise greater-than-or-equal operation.
-class NGRAPH_API GreaterEqual : public util::BinaryElementwiseComparison {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    /// \brief Constructs a greater-than-or-equal operation.
-    GreaterEqual() : util::BinaryElementwiseComparison(AutoBroadcastSpec::NUMPY) {}
-    /// \brief Constructs a greater-than-or-equal operation.
-    ///
-    /// \param arg0 Node that produces the first input tensor.
-    /// \param arg1 Node that produces the second input tensor.
-    /// \param auto_broadcast Auto broadcast specification
-    GreaterEqual(const Output<Node>& arg0,
-                 const Output<Node>& arg1,
-                 const AutoBroadcastSpec& auto_broadcast = AutoBroadcastSpec(AutoBroadcastType::NUMPY));
-
-    virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    bool has_evaluate() const override;
-};
+using ov::op::v1::GreaterEqual;
 }  // namespace v1
 }  // namespace op
 }  // namespace ngraph