//*****************************************************************************
// Copyright 2017-2019 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 <cstddef>
#include <memory>

#include "ngraph/axis_set.hpp"
#include "ngraph/node.hpp"

namespace ngraph
{
    namespace builder
    {
        /// \brief      Specyfies method of bias application to avoid numerical problems
        enum class BiasMode
        {
            // Add bias to intermediate result
            ADD,
            // Calculate max of intermediate result and bias
            MAX
        };

        /// \brief      Calculates L-0 norm of input tensor.
        ///
        /// \note       The L-0 norm represents the cardinality of elements different
        ///             from zero. This actually is not a "true" norm.
        ///
        /// \param[in]  value           The input tensor.
        /// \param[in]  reduction_axes  The axes along which we calculate norm.
        ///
        /// \return     L-0 norm of value.
        ///
        std::shared_ptr<Node> l0_norm(const Output<Node>& value, const AxisSet& reduction_axes);

        /// \brief      Calculates L-1 norm of a value.
        ///
        /// \note       The L-1 norm represents the sum of absolute values.
        ///
        /// \param[in]  value           The input tensor.
        /// \param[in]  reduction_axes  The axes along which we calculate norm.
        /// \param[in]  bias            The bias added to the calculated sum.
        ///
        /// \return     L-1 norm of value.
        ///
        std::shared_ptr<Node>
            l1_norm(const Output<Node>& value, const AxisSet& reduction_axes, float bias = 0.f);

        /// \brief      Calculates L-2 norm of input tensor.
        ///
        /// \note       The L-2 norm represents the square root of sum of squares of each
        ///             individual element.
        ///
        /// \param[in]  value           The input tensor.
        /// \param[in]  reduction_axes  The axes along which we calculate norm.
        /// \param[in]  bias            The bias combined with calculated sum.
        /// \param[in]  bias_mode       The method of bias application.
        ///
        /// \return     L-2 norm of value.
        ///
        std::shared_ptr<Node> l2_norm(const Output<Node>& value,
                                      const AxisSet& reduction_axes,
                                      float bias = 0.f,
                                      BiasMode bias_mode = BiasMode::ADD);

        /// \brief      Creates node which calculates L-p norm on input tensor.
        ///
        /// \param[in]  value           The input tensor.
        /// \param[in]  reduction_axes  The axes along which we calculate norm.
        /// \param[in]  p_norm          The p norm to calculate.
        /// \param[in]  bias            The bias added to the calculated sum.
        ///
        /// \return     L-p norm of value.
        ///
        std::shared_ptr<Node> lp_norm(const Output<Node>& value,
                                      const AxisSet& reduction_axes,
                                      std::size_t p_norm = 2,
                                      float bias = 0.f);
    } // namespace builder
} // namespace ngraph
