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Gustav Louw 2018-04-10 18:53:29 -07:00
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@ -2,51 +2,53 @@
Tinn (Tiny Neural Network) is a 200 line dependency free neural network library written in C99.
#include "Tinn.h"
#include <stdio.h>
```c
#include "Tinn.h"
#include <stdio.h>
#define SETS 4
#define NIPS 2
#define NHID 8
#define NOPS 1
#define ITER 2000
#define RATE 1.0f
#define SETS 4
#define NIPS 2
#define NHID 8
#define NOPS 1
#define ITER 2000
#define RATE 1.0f
int main()
int main()
{
// This example learns XOR.
float in[SETS][NIPS] = {
{ 0, 0 },
{ 0, 1 },
{ 1, 0 },
{ 1, 1 },
};
float tg[SETS][NOPS] = {
{ 0 },
{ 1 },
{ 1 },
{ 0 },
};
// Build.
const Tinn tinn = xtbuild(NIPS, NHID, NOPS);
// Train.
for(int i = 0; i < ITER; i++)
{
// This example learns XOR.
float in[SETS][NIPS] = {
{ 0, 0 },
{ 0, 1 },
{ 1, 0 },
{ 1, 1 },
};
float tg[SETS][NOPS] = {
{ 0 },
{ 1 },
{ 1 },
{ 0 },
};
// Build.
const Tinn tinn = xtbuild(NIPS, NHID, NOPS);
// Train.
for(int i = 0; i < ITER; i++)
{
float error = 0.0f;
for(int j = 0; j < SETS; j++)
error += xttrain(tinn, in[j], tg[j], RATE);
printf("%.12f\n", error / SETS);
}
// Predict.
for(int i = 0; i < SETS; i++)
{
const float* pd = xtpredict(tinn, in[i]);
printf("%f :: %f\n", tg[i][0], (double) pd[0]);
}
// Cleanup.
xtfree(tinn);
return 0;
float error = 0.0f;
for(int j = 0; j < SETS; j++)
error += xttrain(tinn, in[j], tg[j], RATE);
printf("%.12f\n", error / SETS);
}
// Predict.
for(int i = 0; i < SETS; i++)
{
const float* pd = xtpredict(tinn, in[i]);
printf("%f :: %f\n", tg[i][0], (double) pd[0]);
}
// Cleanup.
xtfree(tinn);
return 0;
}
```
For a more complicated demo on how to learn hand written digits, get some training data: