The following code for a neural network, for some infuriating reason, outputs 50 if I use any number above two. Is this just my computer, or my code?

Code: [Select]#pragma region "Stuff behind the scenes that I don't feel like looking at"
inline double sigmoid(double input)
{
double tmp = 0;
double in = -1 * (input - 5);
double e = 2.718281828459045;
tmp = pow(e, in);
tmp++;
tmp = 1 / tmp;
return tmp;
}
class neuron
{
public:
double current_value;
};

class layer
{
public:
neuron *NEURONS;
int neurons_length;
~layer()
{
delete neurons;
}
};

class CONNECTION
{
public:
neuron *previous, *next;
double weight;
~connection()
{
delete previous;
delete next;
}
};

connection *ReDimPreserve(connection *ptr, int size, int newsize)
{
connection *temptr = new connection[newsize];
for (int i = 0; i < size; i++)
{
*(temptr + i) = *(ptr + i);
}
return temptr;
}

class neural_network
{
public:
int inputs_length, outputs_length, layers_length, connections_length;
layer *layers;
connection *connections;
neuron *inputs;
neuron *outputs;
neural_network() {}
neural_network(int inputs_size, int outputs_size, int layers_size, layer *lyrs, neuron *inpts, neuron *outpts, double initial_connection)
{
this->inputs_length = inputs_size;
this->outputs = outpts;
this->outputs_length = outputs_size;
for (int i = 0; i < outputs_length; i++)
{
outputs[i].current_value = 0;
}
this->layers_length = layers_size;
this->layers = lyrs;
for (int i = 0; i < layers_length; i++)
{
for (int B = 0; b < layers[i].neurons_length; b++)
{
layers[i].neurons[b].current_value = 0;
}
}
this->inputs = inpts;
this->connections_length = 0;
int counter = 0;
//connections
for (int i = 0; i < layers_length + 1; i++)
{
if (i == 0)
{
if (layers_length != 0)
{
int tmp = inputs_length * layers->neurons_length;
connections = new connection[tmp];
for (int b = 0; b < tmp + connections_length; b++)
{
(this->connections + b)->previous = inputs + (b % inputs_length);
(this->connections + b)->next = layers[i].neurons + (b % layers[i].neurons_length);
(this->connections + b)->weight = initial_connection;
}
this->connections_length = tmp;
}
}
else if(i == layers_length)
{
int tmp = (layers + layers_length - 1)->neurons_length * outputs_length;
connections = ReDimPreserve(connections, this->connections_length, tmp + this->connections_length);
for (int b = connections_length; b < tmp + connections_length; b++)
{
(this->connections + b)->previous = layers[i - 1].neurons + (b % layers[i - 1].neurons_length);
(this->connections + b)->next = outputs + (b % outputs_length);
(this->connections + b)->weight = initial_connection;
}
this->connections_length += tmp;
}
else
{
int tmp = layers[i - 1].neurons_length * layers[i].neurons_length;
connections = ReDimPreserve(connections, this->connections_length, tmp + this->connections_length);
for (int b = connections_length; b < tmp + connections_length; b++)
{
(this->connections + b)->previous = layers[i - 1].neurons + (b % layers[i - 1].neurons_length);
(this->connections + b)->next = layers[i].neurons + (b % layers[i].neurons_length);
(this->connections + b)->weight = initial_connection;
}
this->connections_length += tmp;
}
}
}
inline double sigmoid(double input)
{
double tmp = 0;
double in = -1 * (input - 5);
double e = 2.718281828459045;
tmp = pow(e, in);
tmp++;
tmp = 1 / tmp;
return tmp;
}
void run()
{
double previous_one = 0;
for (int i = 0; i < this->connections_length; i++)
{
double tmp = 0;
tmp = sigmoid(connections[i].previous->current_value) * connections[i].weight;
connections[i].next->current_value += tmp;
}
}
private:
~neural_network()
{
delete inputs;
delete outputs;
delete connections;
delete layers;
}
};
#pragma endregion

int main()
{
layer *layers = new layer[2];
neuron *l1neurons = new neuron[50];
neuron *l2neurons = new neuron[50];
neuron *in = new neuron[60];
neuron *out = new neuron[3];
layers->neurons = l1neurons;
(layers + 1)->neurons = l2neurons;
layers->neurons_length = 50;
(layers + 1)->neurons_length = 50;
for (int i = 0; i < 60; i++)
{
(in + i)->current_value = 10000000;
}
neural_network *stockpicker = new neural_network(60, 3, 2, layers, in, out, 1);
stockpicker->run();
cout << out->current_value << ", " << (out + 1)->current_value << ", " << (out + 2)->current_value;
cin.ignore();

return 0;
}Its the code! .... but I haven't found where the typo is yet. You have a few locations where variable is sent to = 50. So this is a good place to start and work backwards from.

Quote

layers->neurons_length = 50;
(layers + 1)->neurons_length = 50;