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#ifndef NNTRAIN_INC_C
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#define NNTRAIN_INC_C
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#include "nnlayer.inc.c"
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typedef struct NeuralTrainer {
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int sizeX, sizeY, count;
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double *x, *y;
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} NeuralTrainer;
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NeuralTrainer* ntNew(int sizeX, int sizeY, int count) {
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assert(sizeX > 0);
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assert(sizeY > 0);
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assert(count > 0);
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NeuralTrainer *nt = calloc(sizeof(NeuralTrainer), 1);
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nt->sizeX = sizeX;
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nt->sizeY = sizeY;
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nt->count = count;
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nt->x = calloc(sizeof(double)*(sizeX + sizeY)*count, 1);
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nt->y = nt->x + sizeX*count;
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return nt;
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}
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void ntFree(NeuralTrainer *nt) {
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free(nt->x);
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free(nt);
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}
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double ntTrain(NeuralTrainer *nt, NeuralLayer *nl, int blocks, int blockSize, int repeats, double qmin, double qminSample) {
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assert(!nl->prev);
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assert(nt->sizeX == nl->size);
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assert(nt->sizeY == nlBack(nl)->size);
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printf("training: %d x %d x %d = %d:\n", blocks, blockSize, repeats, blocks*blockSize*repeats);
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double qmax, qsum;
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int total = 0;
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int samples = 0;
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for(int i = 0; i < blocks; ++i) {
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qmax = qsum = 0;
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int repeatsPerBlock = 0;
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for(int j = 0; j < blockSize; ++j, ++samples) {
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int index = rand() % nt->count;
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double *x = nt->x + nt->sizeX*index;
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double *y = nt->y + nt->sizeY*index;
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double q = 0;
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for(int k = 0; k < repeats; ++k) {
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double qq = nlTrainPass(nl, x, y);
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++total, ++repeatsPerBlock;
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if (!k) q = qq;
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if (qq <= qminSample) break;
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}
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if (qmax < q) qmax = q;
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qsum += q;
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}
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printf(" blocks %d (samples: %d, total: %d (%lf)): %lf, %lf\n", i+1, samples, total, repeatsPerBlock/(double)blockSize - 1, qmax, qsum/blockSize);
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if (qmax <= qminSample) break;
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}
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printf("done\n");
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return qmax;
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}
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NeuralTrainer* ntNewSymbolMap(const char *filename, int sizeX, int sizeY) {
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FILE *f = fopen(filename, "rb");
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if (!f)
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return printf("cannot open file '%s' for read\n", filename), NULL;
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fseek(f, 0, SEEK_END);
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size_t fs = ftell(f);
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fseek(f, 0, SEEK_SET);
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size_t testSize = sizeX + 1;
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int count = fs/testSize;
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if (!count)
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return printf("file '%s' is lesser minimal size\n", filename), fclose(f), NULL;
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unsigned char *data = calloc(testSize, count);
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if (count != fread(data, testSize, count, f))
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return printf("cannot read from file '%s'\n", filename), fclose(f), NULL;
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fclose(f);
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NeuralTrainer *nt = ntNew(sizeX, sizeY, count);
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const unsigned char *d = data;
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double *x = nt->x, *y = nt->y, *ey = y + sizeY*count;
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const double delta = 0;
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for(double *p = y; p < ey; ++p) *p = delta;
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while(y < ey) {
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for(double *e = x + sizeX; x < e; ++x, ++d)
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*x = *d/255.0;
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assert(*d < sizeY);
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y[*d++] = 1 - delta;
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y += sizeY;
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}
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return nt;
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}
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void ntPrintSymbol(NeuralTrainer *nt, int index, int width) {
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assert(index >= 0 && index < nt->count);
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assert(width > 0);
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for(int i = 0; i < nt->sizeX; ++i) {
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if (i && !(i % width)) printf("\n");
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printf("%c", nt->x[nt->sizeX*index + i] > 0 ? '#' : '.');
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}
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printf("\n");
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for(int i = 0; i < nt->sizeY; ++i)
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printf(" %4.1lf", nt->y[nt->sizeY*index + i]);
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printf("\n");
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}
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#endif
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