118 lines
3.1 KiB
C
118 lines
3.1 KiB
C
#include "riscv_math.h"
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#include <stdint.h>
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#include <stdlib.h>
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#include "../common.h"
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#include "../HelperFunctions/math_helper.c"
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#include "../HelperFunctions/ref_helper.c"
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#include <stdio.h>
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#define DELTAF32 (0.05f)
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#define DELTAQ31 (63)
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#define DELTAQ15 (1)
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#define DELTAQ7 (1)
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int test_flag_error = 0;
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/*
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The sigmoid SVM instance containing all parameters.
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Those parameters can be generated with the python library scikit-learn.
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*/
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riscv_svm_sigmoid_instance_f32 params;
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/*
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Parameters generated by a training of the SVM classifier
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using scikit-learn and some random input data.
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*/
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#define NB_SUPPORT_VECTORS 2
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/*
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Dimension of the vector space. A vector is your feature.
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It could, for instance, be the pixels of a picture or the FFT of a signal.
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*/
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#define VECTOR_DIMENSION 2
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const float32_t dualCoefficients[NB_SUPPORT_VECTORS]={-0.5006101f,0.5006101f}; /* Dual coefficients */
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const float32_t supportVectors[NB_SUPPORT_VECTORS*VECTOR_DIMENSION]={-1.33358633f,3.46798561f,-0.56781298f,-2.79117593f}; /* Support vectors */
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/*
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Class A is identified with value 0.
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Class B is identified with value 1.
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This array is used by the SVM functions to do a conversion and ease the comparison
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with the Python code where different values could be used.
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*/
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const int32_t classes[2]={0,1};
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int main()
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{
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int i;
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BENCH_INIT;
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/* Array of input data */
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float32_t in[VECTOR_DIMENSION];
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/* Result of the classifier */
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int32_t result;
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/*
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Initialization of the SVM instance parameters.
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Additional parameters (intercept, degree, coef0 and gamma) are also coming from Python.
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*/
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riscv_svm_sigmoid_init_f32(¶ms,
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NB_SUPPORT_VECTORS,
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VECTOR_DIMENSION,
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0.000017f, /* Intercept */
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dualCoefficients,
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supportVectors,
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classes,
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1.100000f, /* Coef0 */
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0.500000f /* Gamma */
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);
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/*
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Input data.
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It is corresponding to a point inside the first class.
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*/
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in[0] = 0.4f;
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in[1] = 0.1f;
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BENCH_START(riscv_svm_sigmoid_predict_f32);
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riscv_svm_sigmoid_predict_f32(¶ms, in, &result);
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BENCH_END(riscv_svm_sigmoid_predict_f32);
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/* Result should be 0 : First class */
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if (result != 0) {
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BENCH_ERROR(riscv_svm_sigmoid_predict_f32);
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printf("expect: %d, actual: %d\n", 0, result);
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test_flag_error = 1;
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}
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BENCH_STATUS(riscv_svm_sigmoid_predict_f32);
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/*
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This input vector is corresponding to a point inside the second class.
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*/
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in[0] = 3.0f;
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in[1] = 0.0f;
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riscv_svm_sigmoid_predict_f32(¶ms, in, &result);
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/* Result should be 0 : First class */
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if (result != 1) {
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BENCH_ERROR(riscv_svm_sigmoid_predict_f32);
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printf("expect: %d, actual: %d\n", 1, result);
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test_flag_error = 1;
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}
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BENCH_STATUS(riscv_svm_sigmoid_predict_f32);
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BENCH_FINISH;
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if (test_flag_error) {
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printf("test error apprears, please recheck.\n");
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return 1;
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} else {
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printf("all test are passed. Well done!\n");
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}
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return 0;
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};
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