// Copyright 2020-2021 Espressif Systems (Shanghai) PTE LTD
//
// 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

/**
 * @file        Header definitions to include for esp_nn reference functions
 */

#include "esp_nn_defs.h"
/************************** Basic math functions ****************************/

/**
 * @brief       elementwise addition
 *
 * @note        inputs type: int8_t, output: int8_t
 *              input offsets: although int32_t, they are contained in 8 bits [-128, 127]
 *
 *              shift values are expected to be <= 0
 */
void esp_nn_add_elementwise_s8_ansi(const int8_t *input1_data,
                                    const int8_t *input2_data,
                                    const int32_t input1_offset,
                                    const int32_t input2_offset,
                                    const int32_t input1_mult,
                                    const int32_t input2_mult,
                                    const int32_t input1_shift,
                                    const int32_t input2_shift,
                                    const int32_t left_shift,
                                    int8_t *output,
                                    const int32_t out_offset,
                                    const int32_t out_mult,
                                    const int32_t out_shift,
                                    const int32_t activation_min,
                                    const int32_t activation_max,
                                    const int32_t size);
/**
 * @brief       elementwise multiplication
 *
 * @note        inputs type: int8_t, output: int8_t
 *              input offsets: although int32_t, they are contained in 8 bits [-128, 127]
 *
 *              output shift is expected to be <= 0
 */
void esp_nn_mul_elementwise_s8_ansi(const int8_t *input1_data,
                                    const int8_t *input2_data,
                                    const int32_t input1_offset,
                                    const int32_t input2_offset,
                                    int8_t *output,
                                    const int32_t out_offset,
                                    const int32_t out_mult,
                                    const int32_t out_shift,
                                    const int32_t activation_min,
                                    const int32_t activation_max,
                                    const int32_t size);


/************************** Convolution functions *****************************/

/**
 * @brief       depthwise convolution per channel
 *
 * @note        inputs type: int8_t, output: int8_t
 *              Version used in tflite is per channel.
 *              This version follows the same footsprints.
 *              Meaning, it has per out_channel shift and multiplier for
 *              requantization
 *
 *              optimization notes: Though input_offset is int32 type,
 *              offset values are contained in 8 bits [-128, 127]
 */
void esp_nn_depthwise_conv_s8_ansi(const data_dims_t *input_dims,
                                   const int8_t *input_data,
                                   const data_dims_t *filter_dims,
                                   const int8_t *filter_data,
                                   const int32_t *bias,
                                   const data_dims_t *output_dims,
                                   int8_t *out_data,
                                   const dw_conv_params_t *conv_params,
                                   const quant_data_t *quant_data);

/**
 * @brief       2d-convolution channelwise
 *
 * @note        operation: result += (input + offset) * filter
 *
 *              inputs type: int8_t, output: int8_t
 *              input offsets: although int32_t, they are contained in 8 bits [-128, 127]
 */
void esp_nn_conv_s8_ansi(const data_dims_t *input_dims,
                         const int8_t *input_data,
                         const data_dims_t *filter_dims,
                         const int8_t *filter_data,
                         const int32_t *bias,
                         const data_dims_t *output_dims,
                         int8_t *out_data,
                         const conv_params_t *conv_params,
                         const quant_data_t *quant_data);

int esp_nn_get_conv_scratch_size_ansi(const data_dims_t *input_dims,
                                      const data_dims_t *filter_dims,
                                      const data_dims_t *output_dims,
                                      const conv_params_t *conv_params);
void esp_nn_set_conv_scratch_buf_ansi(const void *buf);

int esp_nn_get_depthwise_conv_scratch_size_ansi(const data_dims_t *input_dims,
                                                const data_dims_t *filter_dims,
                                                const data_dims_t *output_dims,
                                                const dw_conv_params_t *conv_params);
void esp_nn_set_depthwise_conv_scratch_buf_ansi(const void *buf);

/************************** Activation functions *****************************/

/**
 * @brief       relu6
 *
 * @note        inout: int8_t
 */
void esp_nn_relu6_s8_ansi(int8_t *data, uint16_t size);

/************************** Pooling functions *****************************/


/**
 * @brief       max_pool
 *
 * @note        inputs type: int8_t, output: int8_t
 *              input offsets: although int32_t, they are contained in 8 bits [-128, 127]
 */
void esp_nn_max_pool_s8_ansi(const int8_t *input,
                             const uint16_t input_wd,
                             const uint16_t input_ht,
                             int8_t *output,
                             const uint16_t output_wd,
                             const uint16_t output_ht,
                             const uint16_t stride_wd,
                             const uint16_t stride_ht,
                             const uint16_t filter_wd,
                             const uint16_t filter_ht,
                             const uint16_t pad_wd,
                             const uint16_t pad_ht,
                             const int32_t activation_min,
                             const int32_t activation_max,
                             const uint16_t channels);

/**
 * @brief       avg_pool
 *
 * @note        inputs type: int8_t, output: int8_t
 *              input offsets: although int32_t, they are contained in 8 bits [-128, 127]
 */
void esp_nn_avg_pool_s8_ansi(const int8_t *input,
                             const uint16_t input_wd,
                             const uint16_t input_ht,
                             int8_t *output,
                             const uint16_t output_wd,
                             const uint16_t output_ht,
                             const uint16_t stride_wd,
                             const uint16_t stride_ht,
                             const uint16_t filter_wd,
                             const uint16_t filter_ht,
                             const uint16_t pad_wd,
                             const uint16_t pad_ht,
                             const int32_t activation_min,
                             const int32_t activation_max,
                             const uint16_t channels);


/************************** Fully connected functions ***********************/

/**
 * @brief       fully connected
 *
 * @note        inputs type: int8_t, output: int8_t
 *              input offsets: although int32_t, they are contained in 8 bits [-128, 127]
 */
void esp_nn_fully_connected_s8_ansi(const int8_t *input_data,
                                    const int32_t input_offset,
                                    const uint16_t row_len,
                                    const int8_t *filter_data,
                                    const int32_t filter_offset,
                                    const int32_t *bias,
                                    int8_t *out_data,
                                    const uint16_t out_channels,
                                    const int32_t out_offset,
                                    const int32_t out_shift,
                                    const int32_t out_mult,
                                    const int32_t activation_min,
                                    const int32_t activation_max);

/**
 * @brief   Get scratch buffer size needed by softmax function
 *
 * @param   width
 * @param   height
 * @return  size in bytes
 *
 * @note    buffer must be 4 byte aligned
 */
int32_t esp_nn_get_softmax_scratch_size_ansi(const int32_t width, const int32_t height);

/* ANSI C function to be hooked up when optimised version needed */
int32_t esp_nn_get_softmax_scratch_size_opt(const int32_t width, const int32_t height);

/**
 * @brief   Set scratch buffer to be used by softmax function
 *
 * @param   buffer  this can be NULL if one needs to unset it
 *                  must be aligned to 4 bytes
 */
void esp_nn_set_softmax_scratch_buf_ansi(void *buffer);

/**
 * @brief       reference softmax function
 *
 * @note        inputs type: int8_t, output: int8_t
 */
void esp_nn_softmax_s8_ansi(const int8_t *input_data,
                            const int32_t height,
                            const int32_t width,
                            const int32_t mult,
                            const int32_t shift,
                            const int32_t diff_min,
                            int8_t *output_data);


//////////////////////////// Generic optimisations /////////////////////////////

/************************** Convolution functions *****************************/

/**
 * @brief       2d-convolution channelwise optimized version
 *
 * @note        operation: result += (input + offset) * filter
 *
 *              inputs type: int8_t, output: int8_t
 *              input offsets: although int32_t, they are contained in 8 bits [-128, 127]
 */
void esp_nn_conv_s8_opt(const data_dims_t *input_dims,
                        const int8_t *input_data,
                        const data_dims_t *filter_dims,
                        const int8_t *filter_data,
                        const int32_t *bias,
                        const data_dims_t *output_dims,
                        int8_t *out_data,
                        const conv_params_t *conv_params,
                        const quant_data_t *quant_data);

/**
 * @brief       depthwise convolution per channel optimized version
 *
 * @note        inputs type: int8_t, output: int8_t
 *              Version used in tflite is per channel.
 *              This version follows the same footsprints.
 *              Meaning, it has per out_channel shift and multiplier for
 *              requantization
 *
 *              optimization notes: Though input_offset is int32 type,
 *              offset values are contained in 8 bits [-128, 127]
 */
void esp_nn_depthwise_conv_s8_opt(const data_dims_t *input_dims,
                                  const int8_t *input_data,
                                  const data_dims_t *filter_dims,
                                  const int8_t *filter_data,
                                  const int32_t *bias,
                                  const data_dims_t *output_dims,
                                  int8_t *out_data,
                                  const dw_conv_params_t *conv_params,
                                  const quant_data_t *quant_data);

int esp_nn_get_conv_scratch_size_opt(const data_dims_t *input_dims,
                                     const data_dims_t *filter_dims,
                                     const data_dims_t *output_dims,
                                     const conv_params_t *conv_params);
void esp_nn_set_conv_scratch_buf_opt(const void *buf);

int esp_nn_get_depthwise_conv_scratch_size_opt(const data_dims_t *input_dims,
                                               const data_dims_t *filter_dims,
                                               const data_dims_t *output_dims,
                                               const dw_conv_params_t *conv_params);
void esp_nn_set_depthwise_conv_scratch_buf_opt(const void *buf);

/* ANSI C function to be hooked up when optimised version needed */
void esp_nn_set_softmax_scratch_buf_opt(void *buffer);

/**
 * @brief       optimised version of softmax function
 *
 * @note        the function uses extra buffer (4 * width bytes)
 *              hence, scratch buffers must be set before calling this.
 */
void esp_nn_softmax_s8_opt(const int8_t *input_data,
                           const int32_t height,
                           const int32_t width,
                           const int32_t mult,
                           const int32_t shift,
                           const int32_t diff_min,
                           int8_t *output_data);