private void backward_convolute_on_depth(UnitLayer to, int stride, int depth, int length)
{
int to_depth = depth + length;
if (to_depth >= Depth)
{
to_depth = Depth;
}
for (int d = depth; d < to_depth; d++)
{
WeightLayer weights = WeightLayerPool.find(to.Id, Id, d);
int width_of_weights = weights.Width, height_of_weights = weights.Height;
for (int y = 0; y < Height; y++)
{
int top = y * stride;
int bottom = top + height_of_weights;
for (int x = 0; x < Width; x++)
{
int left = x * stride;
to.diff_convolute_product(left, top, left + width_of_weights, bottom, Units[x, y, d].gradient_at_inport, weights);
}
}
weights.diff_weights();
}
}
private void backward_fully_connect_on_depth(UnitLayer to, int depth, int length)
{
int to_depth = depth + length;
if (to_depth >= Depth)
{
to_depth = Depth;
}
for (int d = depth; d < to_depth; d++)
{
for (int y = 0; y < Height; y++)
{
for (int x = 0; x < Width; x++)
{
WeightLayer weights = WeightLayerPool.find(to.Id, Id, x, y, d);
to.diff_fully_product(Units[x, y, d].gradient_at_inport, weights);
weights.diff_weights();
}
}
}
}