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+/*
+ * Copyright (c) 2016, 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_NECONVOLUTIONKERNEL_H__
+#define __ARM_COMPUTE_NECONVOLUTIONKERNEL_H__
+
+#include "arm_compute/core/NEON/INEKernel.h"
+#include "arm_compute/core/NEON/INESimpleKernel.h"
+
+#include <array>
+#include <cstdint>
+#include <vector>
+
+namespace arm_compute
+{
+class ITensor;
+
+/****************************************************************************************\
+ *                                    Square Convolution                                *
+\****************************************************************************************/
+
+/** Interface for the kernel to run an arbitrary size convolution on a tensor. (Currently supports 3x3, 5x5, 7x7 and 9x9).
+ * The client can supply a convolution matrix \f$ C_{m,n} \f$.
+ * @f{eqnarray}{
+ *  k_0 &=& \frac{m}{2}  \\
+ *  l_0 &=& \frac{n}{2}  \\
+ *  sum &=& \sum_{k=0,l=0}^{k=m-1,l=n-1} input(x+k-k_0, y+l-l_0) C_{k,l}
+ *  @f}
+ *
+ * @note The above equation for this function is similar to the default OpenCV Filter2D function,
+ *       which actually computes a correlation and not a convolution.
+ *       In case of a real convolution the convolution matrix should be flipped both horizontally and vertically.
+ */
+template <unsigned int matrix_size>
+class NEConvolutionKernel : public INESimpleKernel
+{
+public:
+    /** Default constructor */
+    NEConvolutionKernel();
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]  input            Source tensor. Data type supported: U8.
+     * @param[out] output           Destination tensor. Data types supported: U8, S16.
+     * @param[in]  conv             Convolution matrix to apply to the input tensor.
+     * @param[in]  scale            Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(const ITensor *input, ITensor *output, const int16_t *conv, uint32_t scale, bool border_undefined);
+
+    // Inherited methods overridden:
+    void run(const Window &window) override;
+    BorderSize border_size() const override;
+
+private:
+    template <typename OutputType>
+    void convolution(const Window &win);
+
+protected:
+    uint32_t _scale;                                             /**< scale of the convolution */
+    std::array<int16_t, matrix_size *matrix_size> _convolution;  /**< convolution matrix */
+};
+
+/** Interface for the kernel which applied a 3x3 convolution to a tensor.*/
+using NEConvolution3x3Kernel = NEConvolutionKernel<3>;
+/** Interface for the kernel which applied a 5x5 convolution to a tensor.*/
+using NEConvolution5x5Kernel = NEConvolutionKernel<5>;
+/** Interface for the kernel which applied a 7x7 convolution to a tensor.*/
+using NEConvolution7x7Kernel = NEConvolutionKernel<7>;
+///** Interface for the kernel which applied a 9x9 convolution to a tensor.*/
+using NEConvolution9x9Kernel = NEConvolutionKernel<9>;
+
+/****************************************************************************************\
+ *                              Separable Square Convolution                            *
+\****************************************************************************************/
+
+/** Kernel for the Horizontal pass of a Separable Convolution */
+template <unsigned int matrix_size>
+class NESeparableConvolutionHorKernel : public INESimpleKernel
+{
+public:
+    /** Default constructor */
+    NESeparableConvolutionHorKernel();
+
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]  input            Source tensor. Data type supported: U8.
+     * @param[out] output           Destination tensor. Data types supported: U16, S16, S32.
+     * @param[in]  conv_row         Convolution matrix to apply to the input tensor.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(const ITensor *input, ITensor *output, const int16_t *conv_row, bool border_undefined);
+
+    // Inherited methods overridden:
+    void run(const Window &window) override;
+    BorderSize border_size() const override;
+
+private:
+    /** Apply the object's convolution to the given window of the input tensor..
+     *
+     * @param[in] window Window to apply the convolution on.
+     */
+    template <typename OutputType>
+    void convolve(const Window &window);
+
+    std::array<int16_t, matrix_size> _conv_row; /**< Convolution coefficients */
+    BorderSize _border_size;                    /**< Border size */
+};
+
+/** Interface for the kernel which applied a 5x1 horizontal convolution to a tensor.*/
+using NESeparableConvolution5x5HorKernel = NESeparableConvolutionHorKernel<5>;
+/** Interface for the kernel which applied a 7x1 horizontal convolution to a tensor.*/
+using NESeparableConvolution7x7HorKernel = NESeparableConvolutionHorKernel<7>;
+/** Interface for the kernel which applied a 9x1 horizontal convolution to a tensor.*/
+using NESeparableConvolution9x9HorKernel = NESeparableConvolutionHorKernel<9>;
+
+/** Kernel for the Vertical pass of a Separable Convolution */
+template <unsigned int matrix_size>
+class NESeparableConvolutionVertKernel : public INESimpleKernel
+{
+public:
+    /** Default constructor */
+    NESeparableConvolutionVertKernel();
+
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]  input            Source tensor. Data type supported: U16, S16, S32.
+     * @param[out] output           Destination tensor, Data types supported: U8, S16.
+     * @param[in]  conv_col         Convolution matrix to apply to the input tensor.
+     * @param[in]  scale            Scale of the convolution matrix
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(const ITensor *input, ITensor *output, const int16_t *conv_col, uint32_t scale, bool border_undefined);
+
+    // Inherited methods overridden:
+    void run(const Window &window) override;
+    BorderSize border_size() const override;
+
+private:
+    /** Apply the object's convolution to the given window of the input tensor.
+     *  This function is used if the intermediate values have been stored as U16.
+     *
+     * @param[in] win Window to apply the convolution on.
+     */
+    template <typename OutputType>
+    void convolution_u16(const Window &win);
+    /** Apply the object's convolution to the given window of the input tensor.
+     *  This function is used if the intermediate values have been stored as S16.
+     *
+     * @param[in] win Window to apply the convolution on.
+     */
+    template <typename OutputType>
+    void convolution_s16(const Window &win);
+    /** Apply the object's convolution to the given window of the input tensor.
+     *  This function is used if the intermediate values have been stored as S32.
+     *
+     * @param[in] win Window to apply the convolution on.
+     */
+    template <typename OutputType>
+    void convolution_s32(const Window &win);
+
+    std::array<int16_t, matrix_size> _conv_col; /**< Convolution coefficients */
+    uint32_t _scale;                            /**< Convolution's scale */
+};
+
+/** Interface for the kernel which applied a 1x5 vertical convolution to a tensor.*/
+using NESeparableConvolution5x5VertKernel = NESeparableConvolutionVertKernel<5>;
+/** Interface for the kernel which applied a 1x7 vertical convolution to a tensor.*/
+using NESeparableConvolution7x7VertKernel = NESeparableConvolutionVertKernel<7>;
+/** Interface for the kernel which applied a 1x9 vertical convolution to a tensor.*/
+using NESeparableConvolution9x9VertKernel = NESeparableConvolutionVertKernel<9>;
+
+/****************************************************************************************\
+ *                                 Rectangle Convolution                                *
+\****************************************************************************************/
+
+/** Kernel for the running convolution on a rectangle matrix.
+ *
+ * @note Supports combinations of 3,5,7 and 9.
+ */
+class NEConvolutionRectangleKernel : public INEKernel
+{
+public:
+    /** Default constructor */
+    NEConvolutionRectangleKernel();
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    NEConvolutionRectangleKernel(NEConvolutionRectangleKernel &) = delete;
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    NEConvolutionRectangleKernel &operator=(NEConvolutionRectangleKernel &) = delete;
+    /** Allow instances of this class to be moved */
+    NEConvolutionRectangleKernel(NEConvolutionRectangleKernel &&) = default;
+    /** Allow instances of this class to be moved */
+    NEConvolutionRectangleKernel &operator=(NEConvolutionRectangleKernel &&) = default;
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]  input            Source tensor. Data type supported: U8.
+     * @param[out] output           Destination tensor, Data types supported: U8, S16.
+     * @param[in]  conv             Convolution matrix to apply to the input tensor.
+     * @param[in]  width            Width of convolution matrix (Number of columns)
+     * @param[in]  height           Height of convolution matrix (Number of rows)
+     * @param[in]  scale            Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(const ITensor *input, ITensor *output, const int16_t *conv, uint32_t width, uint32_t height, uint32_t scale, bool border_undefined);
+
+    // Inherited methods overridden:
+    void run(const Window &window) override;
+    BorderSize border_size() const override;
+
+private:
+    unsigned int get_index(uint32_t val);
+    /** Apply the object's convolution to the given window of the input tensor.
+     *
+     * @param[in] win Window to apply the convolution on.
+     */
+    template <typename OutputType, unsigned int rows, unsigned int cols>
+    void convolution(const Window &win);
+
+protected:
+    const ITensor            *_input;       /**< Input tensor */
+    ITensor                  *_output;      /**< Output tensor */
+    uint32_t                  _scale;       /**< Scale of the convolution */
+    std::vector<int16_t>      _convolution; /**< Convolution matrix */
+    BorderSize                _border_size; /**< Calculated border width */
+    uint32_t                  _func_idx;    /**< Index used to specify convolution function to be used */
+    const static unsigned int _nr_supported_sizes
+    {
+        4
+    }; /**< Number of supported permutations */
+};
+}
+#endif /*__ARM_COMPUTE_NECONVOLUTIONKERNEL_H__ */