private static Layer parse_route(KeyValuePair[] options, SizeParams parameters, Network net)
{
string l = OptionList.option_find(options, "layers");
if (string.IsNullOrEmpty(l))
{
Utils.Error("Route Layer must specify input layers");
}
var lines = l.Split(',');
int n = lines.Length - 1;
int[] layers = new int[n];
int[] sizes = new int[n];
for (var i = 0; i < lines.Length; ++i)
{
int index = int.Parse(lines[i]);
if (index < 0)
{
index = parameters.Index + index;
}
layers[i] = index;
sizes[i] = net.Layers[index].Outputs;
}
int batch = parameters.Batch;
Layer layer = Layer.make_route_layer(batch, n, layers, sizes);
var first = net.Layers[layers[0]];
layer.OutW = first.OutW;
layer.OutH = first.OutH;
layer.OutC = first.OutC;
for (var i = 1; i < n; ++i)
{
int index = layers[i];
var next = net.Layers[index];
if (next.OutW == first.OutW && next.OutH == first.OutH)
{
layer.OutC += next.OutC;
}
else
{
layer.OutH = layer.OutW = layer.OutC = 0;
}
}
return(layer);
}
private static Layer parse_shortcut(KeyValuePair[] options, SizeParams parameters, Network net)
{
string l = OptionList.option_find(options, "from");
int index = int.Parse(l);
if (index < 0)
{
index = parameters.Index + index;
}
int batch = parameters.Batch;
Layer from = net.Layers[index];
Layer s = Layer.make_shortcut_layer(batch, index, parameters.W, parameters.H, parameters.C, from.OutW, from.OutH, from.OutC);
string activationS = OptionList.option_find_str(options, "activation", "linear");
Activation activation = ActivationsHelper.Get_activation(activationS);
s.Activation = activation;
return(s);
}
private static void parse_net_options(KeyValuePair[] options, Network net)
{
net.Batch = OptionList.option_find_int(options, "batch", 1);
net.LearningRate = OptionList.option_find_float(options, "learning_rate", .001f);
net.Momentum = OptionList.option_find_float(options, "momentum", .9f);
net.Decay = OptionList.option_find_float(options, "decay", .0001f);
int subdivs = OptionList.option_find_int(options, "subdivisions", 1);
net.TimeSteps = OptionList.option_find_int_quiet(options, "time_steps", 1);
net.Batch /= subdivs;
net.Batch *= net.TimeSteps;
net.Subdivisions = subdivs;
net.Adam = OptionList.option_find_int_quiet(options, "adam", 0) != 0;
if (net.Adam)
{
net.B1 = OptionList.option_find_float(options, "B1", .9f);
net.B2 = OptionList.option_find_float(options, "B2", .999f);
net.Eps = OptionList.option_find_float(options, "eps", .000001f);
}
net.H = OptionList.option_find_int_quiet(options, "height", 0);
net.W = OptionList.option_find_int_quiet(options, "width", 0);
net.C = OptionList.option_find_int_quiet(options, "channels", 0);
net.Inputs = OptionList.option_find_int_quiet(options, "inputs", net.H * net.W * net.C);
net.MaxCrop = OptionList.option_find_int_quiet(options, "max_crop", net.W * 2);
net.MinCrop = OptionList.option_find_int_quiet(options, "min_crop", net.W);
net.Angle = OptionList.option_find_float_quiet(options, "angle", 0);
net.Aspect = OptionList.option_find_float_quiet(options, "aspect", 1);
net.Saturation = OptionList.option_find_float_quiet(options, "saturation", 1);
net.Exposure = OptionList.option_find_float_quiet(options, "exposure", 1);
net.Hue = OptionList.option_find_float_quiet(options, "hue", 0);
if (net.Inputs == 0 && !(net.H != 0 && net.W != 0 && net.C != 0))
{
Utils.Error("No input parameters supplied");
}
string policyS = OptionList.option_find_str(options, "policy", "constant");
net.Policy = get_policy(policyS);
net.BurnIn = OptionList.option_find_int_quiet(options, "burn_in", 0);
if (net.Policy == LearningRatePolicy.Step)
{
net.Step = OptionList.option_find_int(options, "step", 1);
net.Scale = OptionList.option_find_float(options, "scale", 1);
}
else if (net.Policy == LearningRatePolicy.Steps)
{
string l = OptionList.option_find(options, "steps");
string p = OptionList.option_find(options, "scales");
if (string.IsNullOrEmpty(l) || string.IsNullOrEmpty(p))
{
Utils.Error("STEPS policy must have steps and scales in cfg file");
}
var lines = l.Split(',');
int[] steps = new int[lines.Length];
float[] scales = new float[lines.Length];
for (var i = 0; i < lines.Length; ++i)
{
steps[i] = int.Parse(lines[i]);
scales[i] = float.Parse(lines[i]);
}
net.Scales = scales;
net.Steps = steps;
net.NumSteps = lines.Length;
}
else if (net.Policy == LearningRatePolicy.Exp)
{
net.Gamma = OptionList.option_find_float(options, "gamma", 1);
}
else if (net.Policy == LearningRatePolicy.Sig)
{
net.Gamma = OptionList.option_find_float(options, "gamma", 1);
net.Step = OptionList.option_find_int(options, "step", 1);
}
else if (net.Policy == LearningRatePolicy.Poly || net.Policy == LearningRatePolicy.Random)
{
net.Power = OptionList.option_find_float(options, "power", 1);
}
net.MaxBatches = OptionList.option_find_int(options, "max_batches", 0);
}
