79 lines
3.7 KiB
C
79 lines
3.7 KiB
C
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/****************************************************************************
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Copyright(c) 2019 by Aerospace C.Power (Chongqing) Microelectronics. ALL RIGHTS RESERVED.
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This Information is proprietary to Aerospace C.Power (Chongqing) Microelectronics and MAY NOT
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be copied by any method or incorporated into another program without
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the express written consent of Aerospace C.Power. This Information or any portion
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thereof remains the property of Aerospace C.Power. The Information contained herein
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is believed to be accurate and Aerospace C.Power assumes no responsibility or
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liability for its use in any way and conveys no license or title under
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any patent or copyright and makes no representation or warranty that this
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Information is free from patent or copyright infringement.
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****************************************************************************/
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#ifndef CNN_K3D_H
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#define CNN_K3D_H
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#include "os_types_api.h"
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#ifdef __cplusplus
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extern "C" {
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#endif
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/** \defgroup cnn k3d API
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* @brief cnn k3d APIs
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* These functions could be used for mid_filter or depth calculation
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* The formular for depth calculation is as below, where x is the input image, Z is the output, f_x_ir, L and d0, whose units are all millimeter, are constant independent from x,
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* Z = f_x_ir * L / (f_x_ir * L / d0 - x)
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* CNN engine will be used in these functions, except for cpu_prelu_ddr, cpu_prelu_before_depth, cpu_prelu_before_point, cpu_prelu_iram.
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* For any features, every column will occupy a size which is a multiple of 32 bytes. Here column means the last dimension of a tensor
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* For example, if a tensor of type int16_t named A is of size 4 * 30 * 300, it will be saved in the memory of this form so that every column occupies 608 bytes:
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* A[0][0][0], A[0][0][1], ..., A[0][0][299], 0, 0, 0, ..., 0, A[0][1][0], A[0][1][1], ..., A[0][1][299], 0, 0, 0, 0, ..., 0, ..., A[0][29][0], ..., A[0][29][299], 0, ..., 0, A[1][0][0], ...
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*
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*
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*
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*/
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/** @addtogroup cnn_k3d_APIs
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* @{
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*/
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enum cnn_k3d_driver_to_do {
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mid_filter_only = 2,
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mid_filter_and_depth = 3,
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depth_only = 4
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};
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struct cnn_k3d_config_bean {
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uint32_t input_addr; // where the input is put
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uint32_t output_addr; // where the output will be put
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uint16_t input_height; // height of input image
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uint16_t input_width; // width of input image
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uint16_t output_height; // height of output image, you don't need to set it, this will be set after calculation
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uint16_t output_width; // width of output image, you don't need to set it, this will be set after calculation
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uint16_t padding_to_same; // 1: use "SAME" mode for padding, 0: use "VALID" mode for padding, ref: tensorflow doc
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enum cnn_k3d_driver_to_do to_do; // 2: middle filter only, 3: middle filter and depth calculation, 4: depth calculation only
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uint8_t feature_signed; // non-zero: input are signed numbers, zero: input are unsigned numbers, only valid when to_do is not 4 cause input need to be signed when to_do is 4
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uint8_t int8_mode; // non-zero: 8bit mode, zero: 16bit mode, only valid when to_do is 2
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int16_t F_L_d0_mu; // the value of f_x_ir * L / d0 in the formular for depth calculation, this number should be in form of S(16, 4), i.e. int16_t, with fraction of 4bits
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uint16_t F_L_mu; // the value of f_x_ir * L in the formular for depth calculation, this number should be in form of US(16, 1), i.e. uint16_t, with fraction of 1bits
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};
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/* @brief cnn_k3d_driver() - do a middle filter or depth calculation in 16bit mode, middle filter's kernel is 3
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* @param config: config info of the pooling process
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* @return 0 -- succeed
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* @return 2 -- input height is 0
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* @return 3 -- input width is 0
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*/
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uint8_t cnn_k3d_driver(struct cnn_k3d_config_bean *config);
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/**
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* @}
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*/
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#ifdef __cplusplus
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}
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#endif
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#endif
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