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); }