openmv/lib/stai/libstai/include/lite_conv2d_is16.h
iabdalkader e95a19c963 lib: Add STAI library and ML backend.
Signed-off-by: iabdalkader <i.abdalkader@gmail.com>
2025-06-10 11:53:31 +02:00

214 lines
9.6 KiB
C

/**
******************************************************************************
* @file lite_dense_is16.h
* @author Giacomo Turati
* @brief header file of AI platform lite conv2d kernel (with signed int16 input)
******************************************************************************
* @attention
*
* Copyright (c) 2024 STMicroelectronics.
* All rights reserved.
*
* This software is licensed under terms that can be found in the LICENSE file
* in the root directory of this software component.
* If no LICENSE file comes with this software, it is provided AS-IS.
*
******************************************************************************
*/
#ifndef LITE_CONV2D_IS16_H
#define LITE_CONV2D_IS16_H
#include "stai.h"
#include "ai_lite_interface.h"
/*!
* @brief Conv2d layer with fixed-point int16_t weights (e.g., Qkeras "auto_po2").
* Support signed integer 16 input and signed integer 16 output activations.
* Both weights and bias (if any) must be quantized with 16 bits.
* Manage different fixed-point scales between weights and bias (if any).
* @param output Pointer to the output buffer
* @param input Pointer to the input buffer
* @param weights Pointer to the weights array
* @param n_channel_in Number of input channels
* @param n_channel_out Number of output channels, i.e.,the number of conv2d hidden filters
* @param width_in Input width
* @param height_in Input height
* @param width_out Output width
* @param height_out Output height
* @param filt_width Filters width
* @param filt_height Filters height
* @param filt_pad_x Filters pad width
* @param filt_pad_y Filters pad height
* @param stride_x Stride width
* @param stride_y Stride height
* @param shifts Array of fixed-point binary scales for the weights
* @param bias_shifts Array of fixed-point binary scales for the bias
* @param signed_input Signed input flag
* @param signed_output Signed output flag
*/
LITE_API_ENTRY
void forward_lite_conv2d_is16os16ws16_fxp(
int16_t* output,
const int16_t* input,
const int16_t* weights,
const int16_t* bias,
const ai_size n_channel_in,
const ai_size n_channel_out,
const ai_size width_in,
const ai_size height_in,
const ai_size width_out,
const ai_size height_out,
const ai_size filt_width,
const ai_size filt_height,
const ai_size filt_pad_x,
const ai_size filt_pad_y,
const uint16_t stride_x,
const uint16_t stride_y,
const uint8_t* shifts,
const uint8_t* bias_shifts
);
/*!
* @brief Conv2d layer with fixed-point int16_t weights (e.g., Qkeras "auto_po2").
* Support signed integer 16 input and unsigned integer 16 output activations.
* Both weights and bias (if any) must be quantized with 16 bits.
* Manage different fixed-point scales between weights and bias (if any).
* @param output Pointer to the output buffer
* @param input Pointer to the input buffer
* @param weights Pointer to the weights array
* @param n_channel_in Number of input channels
* @param n_channel_out Number of output channels, i.e.,the number of conv2d hidden filters
* @param width_in Input width
* @param height_in Input height
* @param width_out Output width
* @param height_out Output height
* @param filt_width Filters width
* @param filt_height Filters height
* @param filt_pad_x Filters pad width
* @param filt_pad_y Filters pad height
* @param stride_x Stride width
* @param stride_y Stride height
* @param shifts Array of fixed-point binary scales for the weights
* @param bias_shifts Array of fixed-point binary scales for the bias
* @param signed_input Signed input flag
* @param signed_output Signed output flag
*/
LITE_API_ENTRY
void forward_lite_conv2d_is16ou16ws16_fxp(
uint16_t* output,
const int16_t* input,
const int16_t* weights,
const int16_t* bias,
const ai_size n_channel_in,
const ai_size n_channel_out,
const ai_size width_in,
const ai_size height_in,
const ai_size width_out,
const ai_size height_out,
const ai_size filt_width,
const ai_size filt_height,
const ai_size filt_pad_x,
const ai_size filt_pad_y,
const uint16_t stride_x,
const uint16_t stride_y,
const uint8_t* shifts,
const uint8_t* bias_shifts
);
/*!
* @brief Conv2d layer with fixed-point int16_t weights (e.g., Qkeras "auto_po2").
* Support unsigned integer 16 input and signed integer 16 output activations.
* Both weights and bias (if any) must be quantized with 16 bits.
* Manage different fixed-point scales between weights and bias (if any).
* @param output Pointer to the output buffer
* @param input Pointer to the input buffer
* @param weights Pointer to the weights array
* @param n_channel_in Number of input channels
* @param n_channel_out Number of output channels, i.e.,the number of conv2d hidden filters
* @param width_in Input width
* @param height_in Input height
* @param width_out Output width
* @param height_out Output height
* @param filt_width Filters width
* @param filt_height Filters height
* @param filt_pad_x Filters pad width
* @param filt_pad_y Filters pad height
* @param stride_x Stride width
* @param stride_y Stride height
* @param shifts Array of fixed-point binary scales for the weights
* @param bias_shifts Array of fixed-point binary scales for the bias
* @param signed_input Signed input flag
* @param signed_output Signed output flag
*/
LITE_API_ENTRY
void forward_lite_conv2d_iu16os16ws16_fxp(
int16_t* output,
const uint16_t* input,
const int16_t* weights,
const int16_t* bias,
const ai_size n_channel_in,
const ai_size n_channel_out,
const ai_size width_in,
const ai_size height_in,
const ai_size width_out,
const ai_size height_out,
const ai_size filt_width,
const ai_size filt_height,
const ai_size filt_pad_x,
const ai_size filt_pad_y,
const uint16_t stride_x,
const uint16_t stride_y,
const uint8_t* shifts,
const uint8_t* bias_shifts
);
/*!
* @brief Conv2d layer with fixed-point int16_t weights (e.g., Qkeras "auto_po2").
* Support unsigned integer 16 input and unsigned integer 16 output activations.
* Both weights and bias (if any) must be quantized with 16 bits.
* Manage different fixed-point scales between weights and bias (if any).
* @param output Pointer to the output buffer
* @param input Pointer to the input buffer
* @param weights Pointer to the weights array
* @param n_channel_in Number of input channels
* @param n_channel_out Number of output channels, i.e.,the number of conv2d hidden filters
* @param width_in Input width
* @param height_in Input height
* @param width_out Output width
* @param height_out Output height
* @param filt_width Filters width
* @param filt_height Filters height
* @param filt_pad_x Filters pad width
* @param filt_pad_y Filters pad height
* @param stride_x Stride width
* @param stride_y Stride height
* @param shifts Array of fixed-point binary scales for the weights
* @param bias_shifts Array of fixed-point binary scales for the bias
* @param signed_input Signed input flag
* @param signed_output Signed output flag
*/
LITE_API_ENTRY
void forward_lite_conv2d_iu16ou16ws16_fxp(
uint16_t* output,
const uint16_t* input,
const int16_t* weights,
const int16_t* bias,
const ai_size n_channel_in,
const ai_size n_channel_out,
const ai_size width_in,
const ai_size height_in,
const ai_size width_out,
const ai_size height_out,
const ai_size filt_width,
const ai_size filt_height,
const ai_size filt_pad_x,
const ai_size filt_pad_y,
const uint16_t stride_x,
const uint16_t stride_y,
const uint8_t* shifts,
const uint8_t* bias_shifts
);
#endif /* LITE_CONV2D_IS16_H */