/*
 * Copyright (c) 2017 ARM Limited.
 *
 * SPDX-License-Identifier: MIT
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to
 * deal in the Software without restriction, including without limitation the
 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
 * sell copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */
#ifndef __ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H__
#define __ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H__

#include "arm_compute/core/NEON/INEKernel.h"

namespace arm_compute
{
class ITensor;

/** Interface for the batch normalization layer kernel.
 */
class NEBatchNormalizationLayerKernel : public INEKernel
{
public:
    /** Default constructor */
    NEBatchNormalizationLayerKernel();
    /** Prevent instances of this class from being copied (As this class contains pointers) */
    NEBatchNormalizationLayerKernel(const NEBatchNormalizationLayerKernel &) = delete;
    /** Prevent instances of this class from being copied (As this class contains pointers) */
    NEBatchNormalizationLayerKernel &operator=(const NEBatchNormalizationLayerKernel &) = delete;
    /** Default Move Constructor. */
    NEBatchNormalizationLayerKernel(NEBatchNormalizationLayerKernel &&) = default;
    /** Default move assignment operator. */
    NEBatchNormalizationLayerKernel &operator=(NEBatchNormalizationLayerKernel &&) = default;
    /** Default destructor */
    ~NEBatchNormalizationLayerKernel() = default;
    /** Set the input and output tensors.
     *
     * @note If the output tensor is a nullptr, the batch normalization function will be performed in-place
     *
     * @param[in, out] input   Source tensor. In case of @p output tensor = nullptr, this tensor will store the result.
     *                         3 lower dimensions represent a single input with dimensions [width, height, FM].
     *                         The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
     * @param[out]     output  Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
     * @param[in]      mean    Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
     * @param[in]      var     Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
     * @param[in]      beta    Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
     * @param[in]      gamma   Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
     * @param[in]      epsilon Small value to avoid division with zero.
     */
    void configure(ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, float epsilon);
    /** Static function to check if given info will lead to a valid configuration of @ref NEBatchNormalizationLayerKernel
     *
     * @param[in] input   Source tensor info. In case of @p output tensor = nullptr, this tensor will store the result.
     *                    3 lower dimensions represent a single input with dimensions [width, height, FM].
     *                    The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
     * @param[in] output  Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input
     * @param[in] mean    Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
     * @param[in] var     Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
     * @param[in] beta    Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
     * @param[in] gamma   Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
     * @param[in] epsilon Small value to avoid division with zero.
     *
     * @return a status
     */
    static Status validate(const ITensorInfo *input, const ITensorInfo *output,
                           const ITensorInfo *mean, const ITensorInfo *var,
                           const ITensorInfo *beta, const ITensorInfo *gamma,
                           float epsilon);

    // Inherited methods overridden:
    void run(const Window &window, const ThreadInfo &info) override;

private:
    using BatchNormFunction = void(ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, float epsilon, const Window &window);
    BatchNormFunction *_func;
    ITensor           *_input;
    ITensor           *_output;
    const ITensor     *_mean;
    const ITensor     *_var;
    const ITensor     *_gamma;
    const ITensor     *_beta;
    float              _epsilon;
};
} // namespace arm_compute
#endif /*__ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H__ */