public SampledSoftmaxLayer(SampledSoftmaxLayerConfig config) : base(config)
{
this.config = config;
if (negativeSampleSize > LayerSize)
{
throw new ArgumentException(
$"The size of negative sampling('{negativeSampleSize}') cannot be greater than the hidden layer size('{LayerSize}').");
}
}
private void SetOutputLayers()
{
//Settings for output layer
var outputLayer = config.GetValueRequired(OUTPUT_LAYER);
var items = outputLayer.Split(':');
var sLayerType = items[0];
var outputLayerType = LayerType.None;
foreach (
var type in
Enum.GetValues(typeof(LayerType))
.Cast <LayerType>()
.Where(type => sLayerType.Equals(type.ToString(), StringComparison.InvariantCultureIgnoreCase)))
{
outputLayerType = type;
break;
}
if (IsCRFTraining == true && outputLayerType != LayerType.Simple)
{
throw new ArgumentException($"For RNN-CRF model, its output layer type must be simple layer.");
}
switch (outputLayerType)
{
case LayerType.Softmax:
OutputLayerConfig = new SoftmaxLayerConfig();
Logger.WriteLine("Initialize configuration for softmax layer.");
break;
case LayerType.SampledSoftmax:
var sampledSoftmaxLayerConfig = new SampledSoftmaxLayerConfig {
NegativeSampleSize = int.Parse(items[1])
};
OutputLayerConfig = sampledSoftmaxLayerConfig;
Logger.WriteLine(
$"Initialize configuration for sampled Softmax layer. Negative sample size = '{sampledSoftmaxLayerConfig.NegativeSampleSize}'");
break;
case LayerType.Simple:
OutputLayerConfig = new SimpleLayerConfig();
Logger.WriteLine("Initialize configuration for simple layer.");
break;
default:
Logger.WriteLine($"Invalidated output layer type {sLayerType}");
throw new ArgumentException($"Invalidated output layer type {sLayerType}");
}
}