/// <summary>
/// Gets the underlaying tensor instance.
/// </summary>
/// <returns></returns>
public Tensor GetTensor()
{
if (UnderlayingTensor == null)
{
UnderlayingTensor = K.CreateVariable(UnderlayingVariable.Data <float>(), Shape);
}
return(UnderlayingTensor);
}
/// <summary>
/// Generates output predictions for the input samples.
/// </summary>
/// <param name="x">The input data frame to run prediction.</param>
/// <returns></returns>
public Tensor Predict(DataFrame x)
{
List <float> predictions = new List <float>();
Tensor output = x.GetTensor();
foreach (var layer in Layers)
{
if (layer.SkipPred)
{
continue;
}
layer.Forward(output);
output = layer.Output;
}
predictions.AddRange(output.ToArray().Cast <float>());
return(K.CreateVariable(predictions.ToArray(), output.Shape));
}
