// Copyright (C) 2018-2021 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//

#pragma once

#include <memory>

#include "ngraph/op/util/binary_elementwise_arithmetic.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;

                size_t get_version() const override { return 1; }
                bool evaluate(const HostTensorVector& outputs,
                              const HostTensorVector& inputs) const override;
                bool has_evaluate() const override;
            };
        } // namespace v1
    }     // namespace op
} // namespace ngraph
