Move all a ops to ov

ngraph/core/include/ngraph/op/abs.hpp

@@ -7,37 +7,12 @@
 #include <memory>
 
 #include "ngraph/op/util/unary_elementwise_arithmetic.hpp"
+#include "openvino/op/abs.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v0 {
-/// \brief Elementwise absolute value operation.
-///
-class NGRAPH_API Abs : public util::UnaryElementwiseArithmetic {
-public:
-    static constexpr NodeTypeInfo type_info{"Abs", 0};
-    const NodeTypeInfo& get_type_info() const override {
-        return type_info;
-    }
-    /// \brief Constructs an absolute value operation.
-    Abs() = default;
-    bool visit_attributes(AttributeVisitor&) override {
-        return true;
-    }
-    /// \brief Constructs an absolute value operation.
-    ///
-    /// \param arg Output that produces the input tensor.<br>
-    /// `[d1, ...]`
-    ///
-    /// Output `[d1, ...]`
-    ///
-    Abs(const Output<Node>& arg);
-
-    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::v0::Abs;
 }  // namespace v0
 using v0::Abs;
 }  // namespace op

ngraph/core/include/ngraph/op/acos.hpp

@@ -7,35 +7,12 @@
 #include <memory>
 
 #include "ngraph/op/util/unary_elementwise_arithmetic.hpp"
+#include "openvino/op/acos.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v0 {
-/// \brief Elementwise inverse cosine (arccos) operation.
-///
-class NGRAPH_API Acos : public util::UnaryElementwiseArithmetic {
-public:
-    static constexpr NodeTypeInfo type_info{"Acos", 0};
-    const NodeTypeInfo& get_type_info() const override {
-        return type_info;
-    }
-    /// \brief Constructs an arccos operation.
-    Acos() = default;
-    /// \brief Constructs an arccos operation.
-    ///
-    /// \param arg Output that produces the input tensor.<br>
-    /// `[d1, ...]`
-    ///
-    /// Output `[d1, ...]`
-    ///
-    Acos(const Output<Node>& arg);
-    bool visit_attributes(AttributeVisitor&) override {
-        return true;
-    }
-    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::v0::Acos;
 }  // namespace v0
 using v0::Acos;
 }  // namespace op

ngraph/core/include/ngraph/op/acosh.hpp

@@ -7,34 +7,12 @@
 #include <memory>
 
 #include "ngraph/op/util/unary_elementwise_arithmetic.hpp"
+#include "openvino/op/acosh.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v3 {
-/// \brief Elementwise inverse hyperbolic cos operation.
-///
-class NGRAPH_API Acosh : public util::UnaryElementwiseArithmetic {
-public:
-    NGRAPH_RTTI_DECLARATION;
-
-    /// \brief Constructs an Acosh operation.
-    Acosh() = default;
-    /// \brief Constructs an Acosh operation.
-    ///
-    /// \param arg Output that produces the input tensor.<br>
-    /// `[d1, ...]`
-    ///
-    /// Output `[d1, ...]`
-    ///
-    Acosh(const Output<Node>& arg);
-
-    virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-    bool visit_attributes(AttributeVisitor&) override {
-        return true;
-    }
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    bool has_evaluate() const override;
-};
+using ov::op::v3::Acosh;
 }  // namespace v3
 using v3::Acosh;
 }  // namespace op

ngraph/core/include/ngraph/op/adaptive_avg_pool.hpp

@@ -6,33 +6,12 @@
 
 #include "ngraph/op/op.hpp"
 #include "ngraph/op/util/attr_types.hpp"
+#include "openvino/op/adaptive_avg_pool.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v8 {
-/// \brief Adaptive average pooling operation.
-///
-class NGRAPH_API AdaptiveAvgPool : public Op {
-public:
-    NGRAPH_RTTI_DECLARATION;
-
-    AdaptiveAvgPool() = default;
-
-    ///
-    /// \brief    Constructs adaptive average pooling operation.
-    ///
-    /// \param    data            Input data
-    ///
-    /// \param    output_shape    1D tensor describing output shape for spatial
-    ///                           dimensions.
-    ///
-    AdaptiveAvgPool(const Output<Node>& data, const Output<Node>& output_shape);
-
-    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;
-};
+using ov::op::v8::AdaptiveAvgPool;
 }  // namespace v8
 }  // namespace op
 }  // namespace ngraph

ngraph/core/include/ngraph/op/adaptive_max_pool.hpp

@@ -6,45 +6,12 @@
 
 #include "ngraph/op/op.hpp"
 #include "ngraph/op/util/attr_types.hpp"
+#include "openvino/op/adaptive_max_pool.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v8 {
-/// \brief Adaptive max pooling operation.
-///
-class NGRAPH_API AdaptiveMaxPool : public Op {
-public:
-    NGRAPH_RTTI_DECLARATION;
-
-    AdaptiveMaxPool() = default;
-
-    ///
-    /// \brief    Constructs adaptive max pooling operation.
-    ///
-    /// \param    data                  Input data
-    ///
-    /// \param    output_shape          1D tensor describing output shape for spatial
-    ///                                 dimensions.
-    ///
-    /// \param    index_element_type    Specifies the output tensor type for indices
-    /// output
-    ///
-    AdaptiveMaxPool(const Output<Node>& data,
-                    const Output<Node>& output_shape,
-                    const ngraph::element::Type& index_element_type = ngraph::element::i64);
-
-    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;
-
-    element::Type get_index_element_type() const {
-        return m_index_element_type;
-    }
-
-protected:
-    ngraph::element::Type m_index_element_type = ngraph::element::i64;
-};
+using ov::op::v8::AdaptiveMaxPool;
 }  // namespace v8
 }  // namespace op
 }  // namespace ngraph

ngraph/core/include/ngraph/op/add.hpp

@@ -7,41 +7,12 @@
 #include <memory>
 
 #include "ngraph/op/util/binary_elementwise_arithmetic.hpp"
+#include "openvino/op/add.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v1 {
-/// \brief Elementwise addition operation.
-///
-class NGRAPH_API Add : public util::BinaryElementwiseArithmetic {
-public:
-    NGRAPH_RTTI_DECLARATION;
-
-    /// \brief Constructs an uninitialized addition operation
-    Add() : util::BinaryElementwiseArithmetic(AutoBroadcastSpec::NUMPY) {}
-
-    /// \brief Constructs an addition operation.
-    ///
-    /// \param arg0 Output that produces the first input tensor.<br>
-    /// `[d0, ...]`
-    /// \param arg1 Output that produces the second input tensor.<br>
-    /// `[d0, ...]`
-    /// \param auto_broadcast Auto broadcast specification. Default is Numpy-style
-    ///                       implicit broadcasting.
-    ///
-    /// Output `[d0, ...]`
-    ///
-    Add(const Output<Node>& arg0,
-        const Output<Node>& arg1,
-        const AutoBroadcastSpec& auto_broadcast = AutoBroadcastSpec(AutoBroadcastType::NUMPY));
-
-    std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-
-    bool visit_attributes(AttributeVisitor& visitor) override;
-
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    bool has_evaluate() const override;
-};
+using ov::op::v1::Add;
 }  // namespace v1
 }  // namespace op
 }  // namespace ngraph

ngraph/core/include/ngraph/op/and.hpp

@@ -7,37 +7,12 @@
 #include <memory>
 
 #include "ngraph/op/util/binary_elementwise_logical.hpp"
+#include "openvino/op/logical_and.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v1 {
-/// \brief Elementwise logical-and operation.
-///
-class NGRAPH_API LogicalAnd : public util::BinaryElementwiseLogical {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    /// \brief Constructs a logical-and operation.
-    LogicalAnd() = default;
-
-    /// \brief Constructs a logical-and operation.
-    ///
-    /// \param arg0 Output that produces the first input tensor.<br>
-    /// `[d0, ...]`
-    /// \param arg1 Output that produces the second input tensor.<br>
-    /// `[d0, ...]`
-    /// \param auto_broadcast Auto broadcast specification
-    ///
-    /// Output `[d0, ...]`
-    ///
-    LogicalAnd(const Output<Node>& arg0,
-               const Output<Node>& arg1,
-               const AutoBroadcastSpec& auto_broadcast = AutoBroadcastSpec(AutoBroadcastType::NUMPY));
-
-    std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-    bool visit_attributes(AttributeVisitor& visitor) override;
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    bool has_evaluate() const override;
-};
+using ov::op::v1::LogicalAnd;
 }  // namespace v1
 }  // namespace op
 }  // namespace ngraph

ngraph/core/include/ngraph/op/asin.hpp

@@ -7,36 +7,12 @@
 #include <memory>
 
 #include "ngraph/op/util/unary_elementwise_arithmetic.hpp"
+#include "openvino/op/asin.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v0 {
-/// \brief Elementwise inverse sine (arcsin) operation.
-///
-class NGRAPH_API Asin : public util::UnaryElementwiseArithmetic {
-public:
-    static constexpr NodeTypeInfo type_info{"Asin", 0};
-    const NodeTypeInfo& get_type_info() const override {
-        return type_info;
-    }
-    /// \brief Constructs an arcsin operation.
-    Asin() = default;
-    /// \brief Constructs an arcsin operation.
-    ///
-    /// \param arg Output that produces the input tensor.<br>
-    /// `[d1, ...]`
-    ///
-    /// Output `[d1, ...]`
-    ///
-    Asin(const Output<Node>& arg);
-
-    virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-    bool visit_attributes(AttributeVisitor&) override {
-        return true;
-    }
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    bool has_evaluate() const override;
-};
+using ov::op::v0::Asin;
 }  // namespace v0
 using v0::Asin;
 }  // namespace op

ngraph/core/include/ngraph/op/asinh.hpp

@@ -7,34 +7,12 @@
 #include <memory>
 
 #include "ngraph/op/util/unary_elementwise_arithmetic.hpp"
+#include "openvino/op/asinh.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v3 {
-/// \brief Elementwise inverse hyperbolic sin operation.
-///
-class NGRAPH_API Asinh : public util::UnaryElementwiseArithmetic {
-public:
-    NGRAPH_RTTI_DECLARATION;
-
-    /// \brief Constructs an Asinh operation.
-    Asinh() = default;
-    /// \brief Constructs an Asinh operation.
-    ///
-    /// \param arg Output that produces the input tensor.<br>
-    /// `[d1, ...]`
-    ///
-    /// Output `[d1, ...]`
-    ///
-    Asinh(const Output<Node>& arg);
-
-    virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
-    bool visit_attributes(AttributeVisitor&) override {
-        return true;
-    }
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    bool has_evaluate() const override;
-};
+using ov::op::v3::Asinh;
 }  // namespace v3
 using v3::Asinh;
 }  // namespace op