Ejemplo n.º 1
0
deconvolutional_layer parse_deconvolutional(list *options, size_params params)
{
    int n = option_find_int(options, "filters",1);
    int size = option_find_int(options, "size",1);
    int stride = option_find_int(options, "stride",1);
    char *activation_s = option_find_str(options, "activation", "logistic");
    ACTIVATION activation = get_activation(activation_s);

    int batch,h,w,c;
    h = params.h;
    w = params.w;
    c = params.c;
    batch=params.batch;
    if(!(h && w && c)) error("Layer before deconvolutional layer must output image.");

    deconvolutional_layer layer = make_deconvolutional_layer(batch,h,w,c,n,size,stride,activation);

    char *weights = option_find_str(options, "weights", 0);
    char *biases = option_find_str(options, "biases", 0);
    parse_data(weights, layer.filters, c*n*size*size);
    parse_data(biases, layer.biases, n);
    #ifdef GPU
    if(weights || biases) push_deconvolutional_layer(layer);
    #endif
    return layer;
}
Ejemplo n.º 2
0
layer parse_deconvolutional(list *options, size_params params)
{
    int n = option_find_int(options, "filters",1);
    int size = option_find_int(options, "size",1);
    int stride = option_find_int(options, "stride",1);

    char *activation_s = option_find_str(options, "activation", "logistic");
    ACTIVATION activation = get_activation(activation_s);

    int batch,h,w,c;
    h = params.h;
    w = params.w;
    c = params.c;
    batch=params.batch;
    if(!(h && w && c)) error("Layer before deconvolutional layer must output image.");
    int batch_normalize = option_find_int_quiet(options, "batch_normalize", 0);
    int pad = option_find_int_quiet(options, "pad",0);
    int padding = option_find_int_quiet(options, "padding",0);
    if(pad) padding = size/2;

    layer l = make_deconvolutional_layer(batch,h,w,c,n,size,stride,padding, activation, batch_normalize, params.net->adam);

    return l;
}