Moved operations R-Z to ov namespace (#7365)

* Moved operations M-P to ov namespace * Fixed code style * Fixed build * Fixed comments * Moved operations R-Z to ov namespace * Fixed build * Fixed comments Co-authored-by: y <[email protected]>
openvinotoolkit · Sep 7, 2021 · 9e68a67 · 9e68a67
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diff --git a/ngraph/core/include/ngraph/op/random_uniform.hpp b/ngraph/core/include/ngraph/op/random_uniform.hpp
@@ -6,80 +6,12 @@
 
 #include "ngraph/node.hpp"
 #include "ngraph/op/op.hpp"
+#include "openvino/op/random_uniform.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v8 {
-/// \brief Tensor RandomUniform operation.
-class NGRAPH_API RandomUniform : public Op {
-public:
-    NGRAPH_RTTI_DECLARATION;
-
-    RandomUniform() = default;
-
-    ///
-    /// \brief      Constructs a RandomUniform operation.
-    ///
-    /// \param      out_shape         Node producing the tensor with output shape.
-    /// \param      min_val           Node producing the tensor with minimum value.
-    /// \param      max_val           Node producing the tensor with maximum value.
-    /// \param      out_type          Output type of the tensor.
-    /// \param      global_seed       Global seed value.
-    /// \param      op_seed           Operational seed value.
-    RandomUniform(const Output<Node>& out_shape,
-                  const Output<Node>& min_val,
-                  const Output<Node>& max_val,
-                  const ngraph::element::Type& out_type,
-                  uint64_t global_seed = 0,
-                  uint64_t op_seed = 0);
-
-    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;
-
-    /// \return Turns off constant folding for RandomUniform operation.
-    bool constant_fold(OutputVector& output_values, const OutputVector& inputs_values) override {
-        return false;
-    }
-
-    /// \return The output tensor type.
-    const ngraph::element::Type& get_out_type() const {
-        return m_output_type;
-    }
-    void set_out_type(const ngraph::element::Type& output_type) {
-        m_output_type = output_type;
-    }
-
-    /// \return The global seed value.
-    uint64_t get_global_seed() const {
-        return m_global_seed;
-    }
-    void set_global_seed(uint64_t seed) {
-        m_global_seed = seed;
-    }
-
-    /// \return The operational seed value.
-    uint64_t get_op_seed() const {
-        return m_op_seed;
-    }
-    void set_op_seed(uint64_t seed2) {
-        m_op_seed = seed2;
-    }
-
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-
-    bool has_evaluate() const override;
-
-protected:
-    ngraph::element::Type m_output_type;
-    uint64_t m_global_seed;
-    uint64_t m_op_seed;
-
-    mutable std::mutex m_state_mutex;
-    mutable std::pair<uint64_t, uint64_t> m_state;
-};
+using ov::op::v8::RandomUniform;
 }  // namespace v8
 }  // namespace op
 }  // namespace ngraph
diff --git a/ngraph/core/include/ngraph/op/range.hpp b/ngraph/core/include/ngraph/op/range.hpp
@@ -6,70 +6,15 @@
 
 #include "ngraph/node.hpp"
 #include "ngraph/op/op.hpp"
+#include "openvino/op/range.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v4 {
-/// \brief Range operation, analogous to `arange()` in Numpy.
-class NGRAPH_API Range : public Op {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    /// \brief Constructs an unitialized range operation.
-    Range() = default;
-
-    /// \brief Constructs a range operation.
-    ///
-    /// \param start The tensor producing the start value. Must be a scalar of numeric
-    ///              element type.
-    /// \param stop The tensor producing the stop value. Must be a scalar of numeric
-    ///             element type.
-    /// \param step The tensor producing the step value. Must be a scalar of numeric
-    ///             element type.
-    /// \param output_type The type of the output.
-    Range(const Output<Node>& start, const Output<Node>& stop, const Output<Node>& step, element::Type output_type);
-
-    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;
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    bool has_evaluate() const override;
-    void set_output_type(element::Type output_type) {
-        m_output_type = output_type;
-    }
-    // Overload collision with method on Node
-    using Node::set_output_type;
-
-private:
-    element::Type m_output_type;
-};
+using ov::op::v4::Range;
 }  // namespace v4
 namespace v0 {
-/// \brief Range operation, analogous to `range()` in Python.
-class NGRAPH_API Range : public Op {
-public:
-    NGRAPH_RTTI_DECLARATION;
-
-    /// \brief Constructs an unitialized range operation.
-    Range() = default;
-
-    /// \brief Constructs a range operation.
-    ///
-    /// \param start The tensor producing the start value. Must be a scalar of integer
-    ///              element type, and same element type as `stop` and `step`.
-    /// \param stop The tensor producing the stop value. Must be a scalar of integer
-    ///             element type, and same element type as `start` and `step`.
-    /// \param step The tensor producing the step value. Must be a scalar of integer
-    ///             element type, and same element type as `start` and `stop`.
-    Range(const Output<Node>& start, const Output<Node>& stop, const Output<Node>& step);
-
-    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;
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    bool has_evaluate() const override;
-};
+using ov::op::v0::Range;
 }  // namespace v0
 using v0::Range;
 }  // namespace op

diff --git a/ngraph/core/include/ngraph/op/reduce_l1.hpp b/ngraph/core/include/ngraph/op/reduce_l1.hpp
@@ -5,36 +5,12 @@
 #pragma once
 
 #include "ngraph/op/util/arithmetic_reductions_keep_dims.hpp"
+#include "openvino/op/reduce_l1.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v4 {
-/// \brief Reduction operation using L1 norm: L1(x) = sum(abs(x)) if all dimensions are
-/// specified for the normalisation.
-///
-/// Reduces the tensor, eliminating the specified reduction axes by taking the L1-norm.
-class NGRAPH_API ReduceL1 : public util::ArithmeticReductionKeepDims {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    /// \brief Constructs a reducet L1-norm operation.
-    ReduceL1() = default;
-    /// \brief Constructs a reduce L1-norm operation.
-    ///
-    /// \param arg The tensor to be reduced.
-    /// \param reduction_axes The axis positions (0-based) to be eliminated.
-    /// \param keep_dims If set to true it holds axes that are used for reduction.
-    ReduceL1(const Output<Node>& arg, const Output<Node>& reduction_axes, bool keep_dims = false);
-
-    /// \return The default value for Reduce.
-    NGRAPH_SUPPRESS_DEPRECATED_START
-    virtual std::shared_ptr<Node> get_default_value() const override;
-    NGRAPH_SUPPRESS_DEPRECATED_END
-
-    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::v4::ReduceL1;
 }  // namespace v4
 }  // namespace op
 }  // namespace ngraph
diff --git a/ngraph/core/include/ngraph/op/reduce_l2.hpp b/ngraph/core/include/ngraph/op/reduce_l2.hpp
@@ -5,35 +5,12 @@
 #pragma once
 
 #include "ngraph/op/util/arithmetic_reductions_keep_dims.hpp"
+#include "openvino/op/reduce_l2.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v4 {
-/// \brief Reduction operation using L2 norm:
-///
-/// Reduces the tensor, eliminating the specified reduction axes by taking the L2-norm.
-class NGRAPH_API ReduceL2 : public util::ArithmeticReductionKeepDims {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    /// \brief Constructs a reducet L2-norm operation.
-    ReduceL2() = default;
-    /// \brief Constructs a reduce L2-norm operation.
-    ///
-    /// \param arg The tensor to be reduced.
-    /// \param reduction_axes The axis positions (0-based) to be eliminated.
-    /// \param keep_dims If set to true it holds axes that are used for reduction.
-    ReduceL2(const Output<Node>& arg, const Output<Node>& reduction_axes, bool keep_dims = false);
-
-    /// \return The default value for Reduce.
-    NGRAPH_SUPPRESS_DEPRECATED_START
-    virtual std::shared_ptr<Node> get_default_value() const override;
-    NGRAPH_SUPPRESS_DEPRECATED_END
-
-    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::v4::ReduceL2;
 }  // namespace v4
 }  // namespace op
 }  // namespace ngraph
diff --git a/ngraph/core/include/ngraph/op/reduce_logical_and.hpp b/ngraph/core/include/ngraph/op/reduce_logical_and.hpp
@@ -5,31 +5,12 @@
 #pragma once
 
 #include "ngraph/op/util/logical_reduction_keep_dims.hpp"
+#include "openvino/op/reduce_logical_and.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v1 {
-/// \brief Performs a reduction using "logical and"
-///
-/// The reduction is performed over slices of the first input. The slices shape depends
-/// on the values passed to the second input - the axes.
-class NGRAPH_API ReduceLogicalAnd : public util::LogicalReductionKeepDims {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    ReduceLogicalAnd() = default;
-    /// \brief Constructs a ReduceLogicalAnd node.
-    ///
-    /// \param data - The input tensor with data to be reduced
-    /// \param reduction_axes - The input tensor with information about axes over which
-    /// the first tensor should be sliced prior to the reduction operation
-    /// \param keep_dims - Indicates if the axes used for reduction should be held/kept
-    ReduceLogicalAnd(const Output<Node>& data, const Output<Node>& reduction_axes, const bool keep_dims = false);
-
-    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::ReduceLogicalAnd;
 }  // namespace v1
 }  // namespace op
 }  // namespace ngraph
diff --git a/ngraph/core/include/ngraph/op/reduce_logical_or.hpp b/ngraph/core/include/ngraph/op/reduce_logical_or.hpp
@@ -5,31 +5,12 @@
 #pragma once
 
 #include "ngraph/op/util/logical_reduction_keep_dims.hpp"
+#include "openvino/op/reduce_logical_or.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v1 {
-/// \brief Performs a reduction using "logical or"
-///
-/// The reduction is performed over slices of the first input. The slices shape depends
-/// on the values passed to the second input - the axes.
-class NGRAPH_API ReduceLogicalOr : public util::LogicalReductionKeepDims {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    ReduceLogicalOr() = default;
-    /// \brief Constructs a ReduceLogicalOr node.
-    ///
-    /// \param data - The input tensor with data to be reduced
-    /// \param reduction_axes - The input tensor with information about axes over which
-    /// the first tensor should be sliced prior to the reduction operation
-    /// \param keep_dims - Indicates if the axes used for reduction should be held/kept
-    ReduceLogicalOr(const Output<Node>& data, const Output<Node>& reduction_axes, const bool keep_dims = false);
-
-    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::ReduceLogicalOr;
 }  // namespace v1
 }  // namespace op
 }  // namespace ngraph
diff --git a/ngraph/core/include/ngraph/op/reduce_mean.hpp b/ngraph/core/include/ngraph/op/reduce_mean.hpp
@@ -6,25 +6,12 @@
 
 #include "ngraph/axis_set.hpp"
 #include "ngraph/op/util/arithmetic_reductions_keep_dims.hpp"
+#include "openvino/op/reduce_mean.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v1 {
-class NGRAPH_API ReduceMean : public util::ArithmeticReductionKeepDims {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    ReduceMean() = default;
-
-    /// \param arg The tensor to be summed.
-    /// \param reduction_axes The axis positions (0-based) to be eliminated.
-    /// \param keep_dims If set to 1 it holds axes that are used for reduction.
-    ReduceMean(const Output<Node>& arg, const Output<Node>& reduction_axes, bool keep_dims = false);
-
-    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::ReduceMean;
 }  // namespace v1
 }  // namespace op
 }  // namespace ngraph
diff --git a/ngraph/core/include/ngraph/op/reduce_prod.hpp b/ngraph/core/include/ngraph/op/reduce_prod.hpp
@@ -5,37 +5,12 @@
 #pragma once
 
 #include "ngraph/op/util/arithmetic_reductions_keep_dims.hpp"
+#include "openvino/op/reduce_prod.hpp"
 
 namespace ngraph {
 namespace op {
 namespace v1 {
-/// \brief Product reduction operation.
-///
-/// Reduces the tensor, eliminating the specified reduction axes by taking the product.
-class NGRAPH_API ReduceProd : public util::ArithmeticReductionKeepDims {
-public:
-    NGRAPH_RTTI_DECLARATION;
-    /// \brief Constructs a product reduction operation.
-    ReduceProd() = default;
-    /// \brief Constructs a product reduction operation.
-    ///
-    /// \param arg The tensor to be reduced.
-    /// \param reduction_axes The axis positions (0-based) to be eliminated.
-    /// \param keep_dims If set to true it holds axes that are used for reduction.
-    ReduceProd(const Output<Node>& arg, const Output<Node>& reduction_axes, bool keep_dims = false);
-
-    /// \return The default value for Product.
-    NGRAPH_SUPPRESS_DEPRECATED_START
-    virtual std::shared_ptr<Node> get_default_value() const override;
-    NGRAPH_SUPPRESS_DEPRECATED_END
-
-    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;
-    bool evaluate_lower(const HostTensorVector& outputs) const override;
-    bool evaluate_upper(const HostTensorVector& outputs) const override;
-};
+using ov::op::v1::ReduceProd;
 }  // namespace v1
 }  // namespace op
 }  // namespace ngraph