URL
https://opencores.org/ocsvn/artificial_neural_network/artificial_neural_network/trunk
Subversion Repositories artificial_neural_network
Compare Revisions
- This comparison shows the changes necessary to convert path
/
- from Rev 4 to Rev 3
- ↔ Reverse comparison
Rev 4 → Rev 3
/artificial_neural_network/trunk/API_header_files/ann.h
0,0 → 1,108
/* |
* ann.h |
* |
* Description: This header file helps programmers to access correctly to ANN IP core weight and bias memories. |
* User must edit ANN_BASEADDRESS, NLAYER, and definitions of layer inputs and neurons. |
* MAX_MUL macro can be calculated manually, or relay on automated calculation if NLAYER<=4. |
* A Wyb(x) macro must be declared on the code per layer of the ANN IP core. |
* Those macro declare the 2D weight arrays and 1D bias arrays needed to access ANN IP core memories. |
* |
* Created on: 17/05/2016 |
* Author: David A |
*/ |
|
#ifndef ANN_H |
#define ANN_H |
|
/* Base address of weight and bias memories of the ANN IP core */ |
// Example for Xilinx's SDK using the example wrapper for Vivado. Correct user base address must be defined here: |
#define ANN_BASEADDRESS XPAR_ANN_0_WYB_S_AXI_BASEADDR |
|
/* Number of layers */ |
#define NLAYER 4 |
|
/* Number of inputs and neurons of each layer */ |
// Add or remove as many layers as needed: |
#define NumIn0 16 |
#define NumN0 13 |
#define NumIn1 NumN0 |
#define NumN1 6 |
#define NumIn2 NumN1 |
#define NumN2 13 |
#define NumIn3 NumN2 |
#define NumN3 16 |
|
/* (optional) Redefine number of neurons in the last layer as number of outputs */ |
#define NumOut NumN3 |
|
/* Next-power-of-two of inputs and neurons of each layer */ |
// Define a next-power-of-two macro per parameter in the number of inputs and neurons of each layer list: |
// NOTE: next_2power(x) macro function calculates the next-power-of-two of x for x<=256. If x>256 it still returns 256. |
#define NumN0_b2 next_2power(NumN0) |
#define NumIn0_b2 next_2power(NumIn0) |
#define NumN1_b2 next_2power(NumN1) |
#define NumIn1_b2 next_2power(NumIn1) |
#define NumN2_b2 next_2power(NumN2) |
#define NumIn2_b2 next_2power(NumIn2) |
#define NumN3_b2 next_2power(NumN3) |
#define NumIn3_b2 next_2power(NumIn3) |
|
/* Maximum multiplication of the next-power-of-two of inputs by the next-power-of-two of neurons */ |
// MAX_MUL macro can be defined manually, or automatically if NLAYER<=4. |
// To define it manually user must determine which layer has the maximum of these products, and edit MAX_MUL definition: |
// In the example is layer 0 (or layer 3 with same MAX_MUL), 256 > 128 |
// NumIn0 = 16 ==> NumIn0_b2 = 16 |
// NumN0 = 13 ==> NumN0_b2 = 16 |
// NumN0_b2*NumIn0_b2=16*16=256 |
// NumIn1 = 13 ==> NumIn1_b2 = 16 |
// NumN1 = 6 ==> NumN1_b2 = 8 |
// NumN1_b2*NumIn1_b2=16*8=128 |
// NumIn2 = 6 ==> NumIn2_b2 = 8 |
// NumN2 = 13 ==> NumN2_b2 = 16 |
// NumN2_b2*NumIn2_b2=8*16=128 |
// NumIn3 = 13 ==> NumIn3_b2 = 16 |
// NumN3 = 16 ==> NumN3_b2 = 16 |
// NumN3_b2*NumIn3_b2=16*16=256 |
|
//#define MAX_MUL (NumN0_b2*NumIn0_b2) //Uncomment and edit this manual definition of MAX_MUL for manual definition of MAX_MUL |
|
// Automated calculation of MAX_MUL for NLAYER<=4: |
#ifndef MAX_MUL |
#if NLAYER > 4 |
#error MAX_MUL cannot be automatically calculated if NLAYER>4. Define MAX_MUL manually or complete the automaed calculation of MAX_MUL preprocessor code. |
#endif |
#define max2(x,y) ( ((x) < (y)) ? y : x ) |
#define MAX_0 (NumN0_b2*NumIn0_b2) |
#if NLAYER > 1 |
#define MAX_1 max2((NumN1_b2*NumIn1_b2),MAX_0) |
#if NLAYER > 2 |
#define MAX_2 max2((NumN2_b2*NumIn2_b2),MAX_1) |
#if NLAYER == 4 |
#define MAX_MUL max2((NumN3_b2*NumIn3_b2),MAX_2) |
#elif NLAYER == 3 |
#define MAX_MUL MAX_2 |
#endif //NLAYER == 4 |
#elif NLAYER == 2 |
#define MAX_MUL MAX_1 |
#endif //NLAYER > 2 |
#else //NLAYER == 1 |
#define MAX_MUL MAX_0 |
#endif //NLAYER > 1 |
#endif |
|
/* Definition of the macro function next_2power(x) */ |
// It calculates the next-power-of-two of x for x<=256. If x>256 it still returns 256. |
#define next_2power(x) ( ((x) > 128) ? 256 : ((x) > 64) ? 128 : ((x) > 32) ? 64 : ((x) > 16) ? 32 : ((x) > 8) ? 16 : ((x) > 4) ? 8 : ((x) > 2) ? 4 : ((x) > 1) ? 2 : 1 ) |
|
/* When this macro is expanded for a particular layer x, it declares pointers to the weight 2D array, bias 1D array, and unused spaces; and initializes them with a proper address */ |
// Declare a Wvb(x) macro per layer on the user's ANN, each time with a different layer number x, from 0 to NLAYER-1. |
// Example: For a two layer ANN (NLAYER 2) |
// Wvb(0) // declares and initializes int (*W0)[NumN0][NumIn0_b2], (*b0)[NumN0]; |
// Wyb(1) // declares and initializes int (*W1)[NumN1][NumIn1_b2], (*b1)[NumN1]; |
// The unused spaces (*NOT_EXISTx0) and (*NOT_EXISTx1) are declared in order to prevent the use of these space address for other proposes. Although it does not assure it will not be used. |
#define Wyb(x) volatile int (*W##x)[NumN##x][NumIn##x##_b2] = (void *) ANN_BASEADDRESS + MAX_MUL*2*x*sizeof(int), \ |
(*NOT_EXIST##x##0)[MAX_MUL-NumN##x*NumIn##x##_b2] = (void *) ANN_BASEADDRESS + (NumN##x*NumIn##x##_b2 + MAX_MUL*2*x)*sizeof(int), \ |
(*b##x)[NumN##x] = (void *) ANN_BASEADDRESS + MAX_MUL*(2*x+1)*sizeof(int), \ |
(*NOT_EXIST##x##1)[MAX_MUL-NumN##x] = (void *) ANN_BASEADDRESS + (NumN##x + MAX_MUL*(2*x+1))*sizeof(int); |
|
#endif // ANN_H |