Exemplo n.º 1
0
/**********************************************************************
*   MSE Class
***********************************************************************/
double MSE::cost(cube pred, cube y){
    dbg_assert(y.n_cols == 1 && y.n_slices == 1);
    pred.reshape(pred.n_elem,1,1);
    y.reshape(y.n_elem,1,1);
    
    double retn = 0.0f;
    for(int i=0; i < y.n_elem; i++) {
        retn += pow(pred(i,0,0) - y(i,0,0),2);
    }
    retn /= y.n_elem;
    retn *= 0.5f;
    //return(retn);
    return(0.5 * mean(mean(square(pred.slice(0) - y.slice(0)))));        
}
Exemplo n.º 2
0
cube ConvLayer::backward(cube delta) {
   
    // NOTE: delta may come from a linear layer
    delta.reshape(_a.n_rows, _a.n_cols, _a.n_slices);
    
    if(!_prev) {
        dbg_print("null pointer to _prev in ConvLayer::backward");
        return zeros<cube>(0,0,0);
    }

    // Compute Weight Updates
    cube input = addPadding(_prev->getActivationCube(), _ksize);
    for(int i = 0; i < _units; i++){
        // dz_dw
        for(int j=0; j < input.n_slices; j++) {
            _dw(i).slice(j) = conv2d(input.slice(j), delta.slice(i));
        }
        // dz_db
        _db(0,0,i) = accu(delta.slice(i));
    }
    

    // Compute next delta
    int nr = _prev->getActivationCube().n_rows;
    int nc = _prev->getActivationCube().n_cols;
    int ns = _prev->getActivationCube().n_slices;
    
    delta = addPadding(delta, _ksize);
    cube next_delta = zeros<cube>(nr,nc,ns);
    for(int i=0; i < ns; i++){
        for(int j=0; j < _units; j++) {
          next_delta.slice(i) += conv2d(
                                    delta.slice(j), 
                                    fliplr(flipud(_w(j).slice(i)))
                                    );
        }
    }

    if(_prev) {
        return(_prev->backward(next_delta));
    }

    return(next_delta);

}