public override void Optimize()
{
GradientClipper.Clip(this);
foreach (var data in Data)
{
if (data.Variable.Type == VariableType.Parameter)
{
if (data.Variable.DataType == typeof(float))
{
var a = _weights[data.Variable].Cast <float>();
var p = data.Tensor.Cast <float>();
var g = data.Gradient.Cast <float>();
Context.Assign(a, Rho.AsScalar <float>() * a + (1.0.AsScalar <float>() - Rho.AsScalar <float>()) * g * g);
Context.Assign(p, p - LearningRate.AsScalar <float>() * g / (Sqrt(a) + Epsilon.AsScalar <float>()));
}
else if (data.Variable.DataType == typeof(double))
{
var a = _weights[data.Variable].Cast <double>();
var p = data.Tensor.Cast <double>();
var g = data.Gradient.Cast <double>();
Context.Assign(a, Rho.AsScalar <double>() * a + (1.0.AsScalar <double>() - Rho.AsScalar <double>()) * g * g);
Context.Assign(p, p - LearningRate.AsScalar <double>() * g / (Sqrt(a) + Epsilon.AsScalar <double>()));
}
else
{
throw new InvalidOperationException();
}
}
}
}