C++ (Cpp) fann_train_epoch_batch примеры использования

Пример #1

Файл: fann_train_data.cpp Проект: akoshterek/MultiGammonCpp

/*
 * Train for one epoch with the selected training algorithm
 */
FANN_EXTERNAL float FANN_API fann_train_epoch(struct fann *ann, struct fann_train_data *data)
{
    switch (ann->training_algorithm)
    {
    case FANN_TRAIN_QUICKPROP:
        return fann_train_epoch_quickprop(ann, data);
    case FANN_TRAIN_RPROP:
        return fann_train_epoch_irpropm(ann, data);
    case FANN_TRAIN_BATCH:
        return fann_train_epoch_batch(ann, data);
    case FANN_TRAIN_INCREMENTAL:
        return fann_train_epoch_incremental(ann, data);
    }
    return 0;
}

Пример #2

Файл: fann_train_data.c Проект: Envek/fann

/*
 * Train for one epoch with the selected training algorithm 
 */
FANN_EXTERNAL float FANN_API fann_train_epoch(struct fann *ann, struct fann_train_data *data)
{
	if(fann_check_input_output_sizes(ann, data) == -1)
		return 0;
	
	switch (ann->training_algorithm)
	{
	case FANN_TRAIN_QUICKPROP:
		return fann_train_epoch_quickprop(ann, data);
	case FANN_TRAIN_RPROP:
		return fann_train_epoch_irpropm(ann, data);
	case FANN_TRAIN_SARPROP:
		return fann_train_epoch_sarprop(ann, data);
	case FANN_TRAIN_BATCH:
		return fann_train_epoch_batch(ann, data);
	case FANN_TRAIN_INCREMENTAL:
		return fann_train_epoch_incremental(ann, data);
	}
	return 0;
}

Пример #3

Файл: fann_train_data.c Проект: dror-g/nn-colletion

/*
 * Train for one epoch with the selected training algorithm 
 */
FANN_EXTERNAL float FANN_API fann_train_epoch(struct fann *ann, struct fann_train_data *data, struct fpts_cl *fptscl)
{
	if(fann_check_input_output_sizes(ann, data) == -1)
		return 0;
	//sclWrite(fptscl->hardware, ann->total_connections*sizeof(fann_type), fptscl->weightscl, ann->weights);
	//printf("wok. Enter train. fptscl->software_mulsum = %s, %d\n", fptscl->software_mulsum.kernelName, fptscl->hardware.deviceType);
	switch (ann->training_algorithm)
	{
	case FANN_TRAIN_QUICKPROP:
		return fann_train_epoch_quickprop(ann, data);
	case FANN_TRAIN_RPROP:
		return fann_train_epoch_irpropm(ann, data, fptscl);
	case FANN_TRAIN_SARPROP:
		return fann_train_epoch_sarprop(ann, data);
	case FANN_TRAIN_BATCH:
		return fann_train_epoch_batch(ann, data);
	case FANN_TRAIN_INCREMENTAL:
		return fann_train_epoch_incremental(ann, data);
	}
	return 0;
}