reverse.hpp

//*****************************************************************************
// Copyright 2017-2021 Intel Corporation
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//*****************************************************************************
 
#pragma once
 
#include "ngraph/op/op.hpp"
 
namespace ngraph
{
    namespace op
    {
        namespace v1
        {
            class NGRAPH_API Reverse : public Op
            {
            public:
                enum class Mode
                {
                    INDEX,
                    MASK
                };
 
                static constexpr NodeTypeInfo type_info{"Reverse", 1};
                const NodeTypeInfo& get_type_info() const override { return type_info; }
                Reverse() = default;
                /// \brief Constructs a reverse operation.
                ///
                /// \param data The input tensor, some of whose axes are to be reversed.
                /// \param reversed_axes The axes to reverse in a form of a set of indices or
                /// boolean mask.
                /// \param mode The way reversed_axes should be interpreted - a set or a mask.
                Reverse(const Output<Node>& data,
                        const Output<Node>& reversed_axes,
                        const std::string& mode);
 
                Reverse(const Output<Node>& data,
                        const Output<Node>& reversed_axes,
                        const Mode mode);
 
                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;
 
                /// \return The second input data interpretation mode.
                Mode get_mode() const { return m_mode; }
                void set_mode(const Mode mode) { m_mode = mode; }
                virtual size_t get_version() const override { return 1; }
                bool evaluate(const HostTensorVector& outputs,
                              const HostTensorVector& inputs) const override;
 
            protected:
                Mode mode_from_string(const std::string& mode) const;
 
                /// \brief Indicates how the values from the second input should be interpreted.
                ///
                /// The second input can contain a set of indices pointing to axes in the data
                /// tensor shape.
                /// Alternatively it can contain a boolean mask that indicates which axes should be
                /// reversed.
                Mode m_mode;
 
            private:
                bool evaluate_reverse(const HostTensorVector& outputs,
                                      const HostTensorVector& inputs) const;
            };
        }
    }
 
    NGRAPH_API
    std::ostream& operator<<(std::ostream& s, const op::v1::Reverse::Mode& type);
 
    template <>
    class NGRAPH_API AttributeAdapter<op::v1::Reverse::Mode>
        : public EnumAttributeAdapterBase<op::v1::Reverse::Mode>
    {
    public:
        AttributeAdapter(op::v1::Reverse::Mode& value)
            : EnumAttributeAdapterBase<op::v1::Reverse::Mode>(value)
        {
        }
 
        static constexpr DiscreteTypeInfo type_info{"AttributeAdapter<op::v1::Reverse::Mode>", 1};
        const DiscreteTypeInfo& get_type_info() const override { return type_info; }
    };
}