public static Network parse_network_cfg(string filename)
{
Section[] sections = read_cfg(filename);
if (sections.Length < 1)
{
Utils.Error("Config file has no Sections");
}
var n = sections[0];
Network net = new Network(sections.Length - 1);
SizeParams parameters = new SizeParams();
var s = new Section(n);
var options = s.Options;
if (is_network(s))
{
Utils.Error("First Section must be [net] or [Network]");
}
parse_net_options(options, net);
parameters.H = net.H;
parameters.W = net.W;
parameters.C = net.C;
parameters.Inputs = net.Inputs;
parameters.Batch = net.Batch;
parameters.TimeSteps = net.TimeSteps;
parameters.Net = net;
ulong workspaceSize = 0;
var index = 1;
int count = 0;
Console.Error.Write("Layer filters size input output\n");
while (index < sections.Length)
{
n = sections[index];
index++;
parameters.Index = count;
Console.Error.Write($"{count:5} ");
s = new Section(n);
options = s.Options;
Layer l = new Layer();
LayerType lt = string_to_layer_type(s.Type);
if (lt == LayerType.Convolutional)
{
l = parse_convolutional(options, parameters);
}
else if (lt == LayerType.Local)
{
l = parse_local(options, parameters);
}
else if (lt == LayerType.Avgpool)
{
l = parse_activation(options, parameters);
}
else if (lt == LayerType.Rnn)
{
l = parse_rnn(options, parameters);
}
else if (lt == LayerType.Gru)
{
l = parse_gru(options, parameters);
}
else if (lt == LayerType.Crnn)
{
l = parse_crnn(options, parameters);
}
else if (lt == LayerType.Connected)
{
l = parse_connected(options, parameters);
}
else if (lt == LayerType.Crop)
{
l = parse_crop(options, parameters);
}
else if (lt == LayerType.Cost)
{
l = parse_cost(options, parameters);
}
else if (lt == LayerType.Region)
{
l = parse_region(options, parameters);
}
else if (lt == LayerType.Detection)
{
l = parse_detection(options, parameters);
}
else if (lt == LayerType.Softmax)
{
l = parse_softmax(options, parameters);
net.Hierarchy = l.SoftmaxTree;
}
else if (lt == LayerType.Normalization)
{
l = parse_normalization(options, parameters);
}
else if (lt == LayerType.Batchnorm)
{
l = parse_batchnorm(options, parameters);
}
else if (lt == LayerType.Maxpool)
{
l = parse_maxpool(options, parameters);
}
else if (lt == LayerType.Reorg)
{
l = parse_reorg(options, parameters);
}
else if (lt == LayerType.Avgpool)
{
l = parse_avgpool(options, parameters);
}
else if (lt == LayerType.Route)
{
l = parse_route(options, parameters, net);
}
else if (lt == LayerType.Shortcut)
{
l = parse_shortcut(options, parameters, net);
}
else if (lt == LayerType.Dropout)
{
l = parse_dropout(options, parameters);
l.Output = net.Layers[count - 1].Output;
l.Delta = net.Layers[count - 1].Delta;
l.OutputGpu = net.Layers[count - 1].OutputGpu;
l.DeltaGpu = net.Layers[count - 1].DeltaGpu;
}
else
{
Console.Error.Write($"LayerType not recognized: {s.Type}\n");
}
l.Dontload = OptionList.option_find_int_quiet(options, "dontload", 0) != 0;
l.Dontloadscales = OptionList.option_find_int_quiet(options, "dontloadscales", 0) != 0;
OptionList.option_unused(options);
net.Layers[count] = l;
if (l.WorkspaceSize > workspaceSize)
{
workspaceSize = l.WorkspaceSize;
}
++count;
if (index + 1 < sections.Length)
{
parameters.H = l.OutH;
parameters.W = l.OutW;
parameters.C = l.OutC;
parameters.Inputs = l.Outputs;
}
}
net.Outputs = Network.get_network_output_size(net);
net.Output = Network.get_network_output(net);
if (workspaceSize != 0)
{
if (CudaUtils.UseGpu)
{
net.Workspace = new float[(workspaceSize - 1) / sizeof(float) + 1];
}
else
{
net.Workspace = new float[1];
}
}
return(net);
}
