/// <summary>
/// Constructor
/// </summary>
/// <param name="optimizer">Wrapped optimizer.</param>
/// <param name="gamma">Multiplicative factor of learning rate decay. Default: 0.1.</param>
/// <param name="last_epoch">The index of last epoch. Default: -1.</param>
/// <param name="verbose"> If true, prints a message to stdout for each update. Default: false.</param>
/// <returns>A scheduler</returns>
public ExponentialLR(ILearningRateController optimizer, double gamma = 0.1, int last_epoch = -1, bool verbose = false)
{
if (optimizer == null)
{
throw new ArgumentNullException("optimizer");
}
_optimizer = optimizer;
_initial = optimizer.LearningRate;
_gamma = gamma;
_last = last_epoch;
_verbose = verbose;
}
/// <summary>
/// Decays the learning rate of each parameter group by gamma every step_size epochs.
/// Notice that such decay can happen simultaneously with other changes to the learning rate from outside this scheduler.
/// When last_epoch=-1, sets initial lr as lr.
/// </summary>
/// <param name="optimizer">Wrapped optimizer.</param>
/// <param name="step_size">Period of learning rate decay.</param>
/// <param name="gamma">Multiplicative factor of learning rate decay. Default: 0.1.</param>
/// <param name="last_epoch">The index of last epoch. Default: -1.</param>
/// <param name="verbose"> If true, prints a message to stdout for each update. Default: false.</param>
/// <returns>A scheduler instance</returns>
public static LRScheduler StepLR(ILearningRateController optimizer, uint step_size, double gamma = 0.1, int last_epoch = -1, bool verbose = false)
{
return(new StepLR(optimizer, step_size, gamma, last_epoch, verbose));
}
/// <summary>
/// Decays the learning rate of each parameter group by gamma every epoch.
/// Notice that such decay can happen simultaneously with other changes to the learning rate from outside this scheduler.
/// When last_epoch=-1, sets initial lr as lr.
/// </summary>
/// <param name="optimizer">Wrapped optimizer.</param>
/// <param name="gamma">Multiplicative factor of learning rate decay. Default: 0.1.</param>
/// <param name="last_epoch">The index of last epoch. Default: -1.</param>
/// <param name="verbose"> If true, prints a message to stdout for each update. Default: false.</param>
/// <returns>A scheduler</returns>
public static LRScheduler ExponentialLR(ILearningRateController optimizer, double gamma = 0.1, int last_epoch = -1, bool verbose = false)
{
return(new impl.ExponentialLR(optimizer, gamma, last_epoch, verbose));
}
