/*
 * Copyright (c) 2017-2021, 2023-2024 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
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 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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 */
#ifndef ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLBATCHNORMALIZATIONLAYER_H
#define ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLBATCHNORMALIZATIONLAYER_H

#include "arm_compute/core/Types.h"
#include "arm_compute/function_info/ActivationLayerInfo.h"
#include "arm_compute/runtime/IFunction.h"

#include <memory>

namespace arm_compute
{
class CLCompileContext;
class ICLTensor;
class ITensorInfo;
class CLBatchNormalizationLayerKernel;

/** Basic function to run CLNormalizationLayerKernel and simulate a batch normalization layer.
 *
 * Batch normalization is calculated by:
 * @f[ out_i = \gamma * (\frac{in_i - \mu_{B}}{\sqrt{\sigma^2_{B} + \epsilon}}) + \beta \equiv BN_{\gamma,\beta}(in_i) @f]
 *
 */
class CLBatchNormalizationLayer : public IFunction
{
public:
    /** Default constructor */
    CLBatchNormalizationLayer();
    /** Prevent instances of this class from being copied */
    CLBatchNormalizationLayer(const CLBatchNormalizationLayer &) = delete;
    /** Prevent instances of this class from being copied */
    CLBatchNormalizationLayer &operator=(const CLBatchNormalizationLayer &) = delete;
    /** Prevent instances of this class to be moved */
    CLBatchNormalizationLayer(CLBatchNormalizationLayer &&) = delete;
    /** Prevent instances of this class to be moved */
    CLBatchNormalizationLayer &operator=(CLBatchNormalizationLayer &&) = delete;
    /** Default destructor */
    ~CLBatchNormalizationLayer();
    /** Set the input and output tensors.
     *
     * Valid data layouts:
     * - NHWC
     * - NCHW
     *
     * Valid data type configurations:
     * |src            |dst            |
     * |:--------------|:--------------|
     * |F32            |F32            |
     * |F16            |F16            |
     *
     * @note If the output tensor is a nullptr or is equal to the input, 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: F16/F32. Data layouts supported: NCHW/NHWC.
     * @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     (Optional) Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for beta is 0. Data types supported: Same as @p input
     * @param[in]      gamma    (Optional) Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for gamma is 1. Data types supported: Same as @p input
     * @param[in]      epsilon  (Optional) Small value to avoid division with zero. Default value is 0.001f.
     * @param[in]      act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
     */
    void configure(ICLTensor          *input,
                   ICLTensor          *output,
                   const ICLTensor    *mean,
                   const ICLTensor    *var,
                   const ICLTensor    *beta     = nullptr,
                   const ICLTensor    *gamma    = nullptr,
                   float               epsilon  = 0.001f,
                   ActivationLayerInfo act_info = ActivationLayerInfo());
    /** Set the input and output tensors.
     *
     * @note If the output tensor is a nullptr or is equal to the input, the batch normalization function will be performed in-place
     *
     * @param[in]      compile_context The compile context to be used.
     * @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: F16/F32. Data layouts supported: NCHW/NHWC.
     * @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            (Optional) Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for beta is 0. Data types supported: Same as @p input
     * @param[in]      gamma           (Optional) Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for gamma is 1. Data types supported: Same as @p input
     * @param[in]      epsilon         (Optional) Small value to avoid division with zero. Default value is 0.001f.
     * @param[in]      act_info        (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
     */
    void configure(const CLCompileContext &compile_context,
                   ICLTensor              *input,
                   ICLTensor              *output,
                   const ICLTensor        *mean,
                   const ICLTensor        *var,
                   const ICLTensor        *beta     = nullptr,
                   const ICLTensor        *gamma    = nullptr,
                   float                   epsilon  = 0.001f,
                   ActivationLayerInfo     act_info = ActivationLayerInfo());
    /** Static function to check if given info will lead to a valid configuration of @ref CLBatchNormalizationLayer
     *
     * @param[in] input    Source tensor info. In case of @p output tensor info = 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: F16/F32. Data layouts supported: NCHW/NHWC.
     * @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     (Optional) Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for beta is 0. Data types supported: Same as @p input
     * @param[in] gamma    (Optional) Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for gamma is 1. Data types supported: Same as @p input
     * @param[in] epsilon  (Optional) Small value to avoid division with zero. Default value is 0.001f.
     * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
     *
     * @return a status
     */
    static Status validate(const ITensorInfo  *input,
                           const ITensorInfo  *output,
                           const ITensorInfo  *mean,
                           const ITensorInfo  *var,
                           const ITensorInfo  *beta     = nullptr,
                           const ITensorInfo  *gamma    = nullptr,
                           float               epsilon  = 0.001f,
                           ActivationLayerInfo act_info = ActivationLayerInfo());

    // Inherited methods overridden:
    void run() override;

private:
    std::unique_ptr<CLBatchNormalizationLayerKernel> _norm_kernel; /**< BatchNormalization layer kernel to run */
};
} // namespace arm_compute
#endif // ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLBATCHNORMALIZATIONLAYER_H
