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");
}
}
