Exemple #1
0
options join(options const & opts1, options const & opts2) {
    sexpr r = opts2.m_value;
    for_each(opts1.m_value, [&](sexpr const & p) {
            if (!opts2.contains(to_name(car(p))))
                r = cons(p, r);
        });
    return options(r);
}
Exemple #2
0
inline edges::edges( nodes * in,
                     nodes * out,
                     options const & opts,
                     vec3i const & stride,
                     vec3i const & in_size,
                     task_manager & tm,
                     filter_tag )
    : options_(opts)
    , size_(in_size)
    , tm_(tm)
{
    size_t n = in->num_out_nodes();
    size_t m = out->num_in_nodes();

    ZI_ASSERT((n>0)&&m>0);

    edges_.resize(n*m);
    filters_.resize(n*m);
    waiter_.set(n*m);

    real eta  = opts.optional_as<real>("eta", 0.1);
    real mom  = opts.optional_as<real>("momentum", 0.0);
    real wd   = opts.optional_as<real>("weight_decay", 0.0);
    auto   sz   = opts.require_as<ovec3i>("size");

    size_ = sz;

    for ( size_t k = 0; k < n*m; ++k )
    {
        filters_[k] = std::make_unique<filter>(sz, eta, mom, wd);
    }

    std::string filter_values;


    if ( opts.contains("filters") )
    {
        filter_values = opts.require_as<std::string>("filters");
    }
    else
    {
        size_t n_values = n*m*size_[0]*size_[1]*size_[2];
        real * filters_raw = new real[n_values];

        auto initf = get_initializator(opts);


        initf->initialize( filters_raw, n*m*size_[0]*size_[1]*size_[2] );

        filter_values = std::string( reinterpret_cast<char*>(filters_raw),
                                     sizeof(real) * n_values );
        delete [] filters_raw;
    }

    load_filters(filters_, size_, filter_values);

    int does_fft = options_.optional_as<int>("fft", "1");
    auto repeat  = options_.optional_as<ovec3i>("repeat", "1,1,1");

    if ( size_ == vec3i::one ) does_fft = 0;

    for ( size_t i = 0, k = 0; i < n; ++i )
    {
        for ( size_t j = 0; j < m; ++j, ++k )
        {
            if ( repeat == ovec3i::one )
            {
                if ( does_fft )
                {
                    edges_[k]
                        = std::make_unique<fft_filter_edge>
                        (in, i, out, j, tm_, stride, *filters_[k]);
                }
                else
                {
                    edges_[k]
                        = std::make_unique<filter_edge>
                        (in, i, out, j, tm_, stride, *filters_[k]);
                }
            }
            else
            {
                if ( does_fft )
                {
                    edges_[k]
                        = std::make_unique<fft_filter_ds_edge>
                        (in, i, out, j, tm_, stride, repeat, *filters_[k]);
                }
                else
                {
                    edges_[k]
                        = std::make_unique<filter_ds_edge>
                        (in, i, out, j, tm_, stride, repeat, *filters_[k]);
                }
            }
        }
    }



}
    transfer_nodes( size_t s,
                    vec3i const & fsize,
                    options const & op,
                    task_manager & tm,
                    size_t fwd_p,
                    size_t bwd_p,
                    bool is_out )
        : nodes(s,fsize,op,tm,fwd_p,bwd_p,false,is_out)
        , biases_(s)
        , func_()
        , fwd_dispatch_(s)
        , bwd_dispatch_(s)
        , fwd_accumulators_(s)
        , bwd_accumulators_(s)
        , fs_(s)
        , fwd_done_(s)
        , waiter_(s)
    {

        for ( size_t i = 0; i < nodes::size(); ++i )
        {
            fwd_accumulators_[i]
                = std::make_unique<forward_accumulator>(fsize);
            bwd_accumulators_[i]
                = std::make_unique<backward_accumulator>(fsize);
        }


        auto type = op.require_as<std::string>("type");

        if ( type == "transfer" )
        {

            func_ = get_transfer_function(op);

            // initialize biases

            real eta = op.optional_as<real>("eta", 0.0001);
            real mom = op.optional_as<real>("momentum", 0.0);
            real wd  = op.optional_as<real>("weight_decay", 0.0);

            for ( auto& b: biases_ )
            {
                b = std::make_unique<bias>(eta, mom, wd);
            }

            std::string bias_values;

            if ( op.contains("biases") )
            {
                bias_values = op.require_as<std::string>("biases");
            }
            else
            {
                real biases_raw[nodes::size()];
                if ( op.contains("init") )
                {
                    auto initf = get_initializator(op);
                    initf->initialize( biases_raw, nodes::size() );
                }
                else
                {
                    std::fill_n(biases_raw, nodes::size(), 0);
                }

                bias_values = std::string( reinterpret_cast<char*>(biases_raw),
                                           sizeof(real) * nodes::size() );
            }

            load_biases(biases_, bias_values);
        }
        else
        {
            ZI_ASSERT(type=="sum");
        }
    }