103 lines
3.4 KiB
C
103 lines
3.4 KiB
C
#include "riscv_math.h"
|
|
#include <stdint.h>
|
|
#include <stdlib.h>
|
|
#include "../common.h"
|
|
|
|
#include "../HelperFunctions/math_helper.c"
|
|
#include "../HelperFunctions/ref_helper.c"
|
|
|
|
#include <stdio.h>
|
|
#define DELTAF32 (0.05f)
|
|
#define DELTAQ31 (63)
|
|
#define DELTAQ15 (1)
|
|
#define DELTAQ7 (1)
|
|
|
|
int test_flag_error = 0;
|
|
|
|
/*
|
|
Those parameters can be generated with the python library scikit-learn.
|
|
*/
|
|
riscv_gaussian_naive_bayes_instance_f32 S;
|
|
|
|
#define NB_OF_CLASSES 3
|
|
#define VECTOR_DIMENSION 2
|
|
|
|
const float32_t theta[NB_OF_CLASSES*VECTOR_DIMENSION] = {1.525400412246743, 1.1286029390034396, -1.5547934054920127, 0.9976789084710983, -0.14944114212609047, -3.0461975645866857}; /**< Mean values for the Gaussians */
|
|
|
|
const float32_t sigma[NB_OF_CLASSES*VECTOR_DIMENSION] = {0.8790413342380022, 1.0687689375338891, 0.9512598687040021, 0.9514543522981638, 1.0755900156857314, 0.9088718773623725}; /**< Variances for the Gaussians */
|
|
|
|
const float32_t classPriors[NB_OF_CLASSES] = {0.3333333333333333f, 0.3333333333333333f, 0.3333333333333333f}; /**< Class prior probabilities */
|
|
|
|
int32_t main(void)
|
|
{
|
|
BENCH_INIT;
|
|
/* Array of input data */
|
|
float32_t in[2];
|
|
|
|
/* Result of the classifier */
|
|
float32_t result[NB_OF_CLASSES];
|
|
float32_t pBufferB[NB_OF_CLASSES];
|
|
float32_t maxProba;
|
|
uint32_t index;
|
|
|
|
S.vectorDimension = VECTOR_DIMENSION;
|
|
S.numberOfClasses = NB_OF_CLASSES;
|
|
S.theta = theta;
|
|
S.sigma = sigma;
|
|
S.classPriors = classPriors;
|
|
S.epsilon=4.731813637210494e-09f;
|
|
|
|
in[0] = 1.5f;
|
|
in[1] = 1.0f;
|
|
BENCH_START(riscv_gaussian_naive_bayes_predict_f32);
|
|
riscv_gaussian_naive_bayes_predict_f32(&S, in, result, pBufferB);
|
|
BENCH_END(riscv_gaussian_naive_bayes_predict_f32);
|
|
riscv_max_f32(result, NB_OF_CLASSES, &maxProba, &index);
|
|
/* Index should be 0 : First class */
|
|
for(int i=0;i<NB_OF_CLASSES;i++)
|
|
printf("%f,",result[i]);
|
|
if (index != 0) {
|
|
BENCH_ERROR(riscv_gaussian_naive_bayes_predict_f32);
|
|
printf("expect: %d, actual: %d\n", 0, index);
|
|
test_flag_error = 1;
|
|
}
|
|
BENCH_STATUS(riscv_gaussian_naive_bayes_predict_f32);
|
|
|
|
|
|
in[0] = -1.5f;
|
|
in[1] = 1.0f;
|
|
BENCH_START(riscv_gaussian_naive_bayes_predict_f32);
|
|
riscv_gaussian_naive_bayes_predict_f32(&S, in, result, pBufferB);
|
|
BENCH_END(riscv_gaussian_naive_bayes_predict_f32);
|
|
riscv_max_f32(result, NB_OF_CLASSES, &maxProba, &index);
|
|
/* Index should be 1 : First class */
|
|
if (index != 1) {
|
|
BENCH_ERROR(riscv_gaussian_naive_bayes_predict_f32);
|
|
printf("expect: %d, actual: %d\n", 1, index);
|
|
test_flag_error = 1;
|
|
}
|
|
BENCH_STATUS(riscv_gaussian_naive_bayes_predict_f32);
|
|
|
|
in[0] = 0.0f;
|
|
in[1] = -3.0f;
|
|
BENCH_START(riscv_gaussian_naive_bayes_predict_f32);
|
|
riscv_gaussian_naive_bayes_predict_f32(&S, in, result, pBufferB);
|
|
BENCH_END(riscv_gaussian_naive_bayes_predict_f32);
|
|
riscv_max_f32(result, NB_OF_CLASSES, &maxProba, &index);
|
|
/* Index should be 2 : First class */
|
|
if (index != 2) {
|
|
BENCH_ERROR(riscv_gaussian_naive_bayes_predict_f32);
|
|
printf("expect: %d, actual: %d\n", 2, index);
|
|
test_flag_error = 1;
|
|
}
|
|
BENCH_STATUS(riscv_gaussian_naive_bayes_predict_f32);
|
|
|
|
BENCH_FINISH;
|
|
if (test_flag_error) {
|
|
printf("test error apprears, please recheck.\n");
|
|
return 1;
|
|
} else {
|
|
printf("all test are passed. Well done!\n");
|
|
}
|
|
return 0;
|
|
} |