//*****************************************************************************
// Copyright 2017-2020 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 v0
        {
            // clang-format off
            /// \brief Axis-reverse operation.
            ///
            /// Reverses the direction of zero or more axes in a tensor, where "reversing" an axis means
            /// that at the output tensor.
            ///
            /// ## Parameters
            ///
            /// |                 | Description              |
            /// | --------------- | ------------------------ |
            /// | `reversed_axes` | The axes to be reversed. |
            ///
            /// ## Inputs
            ///
            /// |       | Type                              | Description                            |
            /// | ----- | --------------------------------- | -------------------------------------- |
            /// | `arg` | \f$E[d_1,\dots,d_n]~(n \geq 0)\f$ | An input tensor of any type and shape. |
            ///
            /// ## Output
            ///
            /// | Type                   | Description                                                                                                                                                               |
            /// | ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
            /// | \f$E[d_1,\dots,d_n]\f$ | The tensor \f$T\f$, where \f$T[i_1,\dots,i_n] = \texttt{arg}[j_1,\dots,j_n]\f$ and \f$j_k = d_k - i_k - 1\f$ if axis \f$k\f$ is in the reverse set; else \f$j_k = i_k\f$. |
            // clang-format on
            class NGRAPH_API Reverse : public Op
            {
            public:
                static constexpr NodeTypeInfo type_info{"Reverse", 0};
                const NodeTypeInfo& get_type_info() const override { return type_info; }
                Reverse() = default;
                /// \brief Constructs a reverse operation.
                ///
                /// \param arg The input tensor, some of whose axes are to be reversed.
                /// \param reversed_axes The axes to reverse.
                Reverse(const Output<Node>& arg, const AxisSet& reversed_axes);

                void validate_and_infer_types() override;

                virtual std::shared_ptr<Node>
                    copy_with_new_args(const NodeVector& new_args) const override;

                /// \return The set of axes to reverse.
                const AxisSet& get_reversed_axes() const { return m_reversed_axes; }
                void set_reversed_axes(const AxisSet& reversed_axes)
                {
                    m_reversed_axes = reversed_axes;
                }

            protected:
                virtual void generate_adjoints(autodiff::Adjoints& adjoints,
                                               const OutputVector& deltas) override;

                AxisSet m_reversed_axes;
            };
        }

        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);

                void validate_and_infer_types() override;

                virtual std::shared_ptr<Node>
                    copy_with_new_args(const NodeVector& 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; }
            protected:
                virtual void generate_adjoints(autodiff::Adjoints& adjoints,
                                               const OutputVector& deltas) override;

                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;
            };
        }
        // default opset version
        using v0::Reverse;
    }
}
