mlr_callback_set.lr_scheduler function

Learning Rate Scheduling Callback

Changes the learning rate based on the schedule specified by a torch::lr_scheduler.

As of this writing, the following are available:

• torch::lr_cosine_annealing()
• torch::lr_lambda()
• torch::lr_multiplicative()
• torch::lr_one_cycle()
• torch::lr_reduce_on_plateau()
• torch::lr_step()
• Custom schedulers defined with torch::lr_scheduler().

Super class

mlr3torch::CallbackSet -> CallbackSetLRScheduler

Public fields

• scheduler_fn: (lr_scheduler_generator)

   The `torch` function that creates a learning rate scheduler
  

• scheduler: (LRScheduler)

   The learning rate scheduler wrapped by this callback
  

Methods

Public methods

• list("CallbackSetLRScheduler$new()")

• list("CallbackSetLRScheduler$on_begin()")

• list("CallbackSetLRScheduler$clone()")

Method new()

Creates a new instance of this R6 class.

Usage

CallbackSetLRScheduler$new(.scheduler, step_on_epoch, ...)

Arguments

• .scheduler: (lr_scheduler_generator)

   The `torch` scheduler generator (e.g. `torch::lr_step`).
  

• step_on_epoch: (logical(1))

   Whether the scheduler steps after every epoch (otherwise every batch).
  

• ...: (any)

   The scheduler-specific arguments
  

Method on_begin()

Creates the scheduler using the optimizer from the context

Usage

CallbackSetLRScheduler$on_begin()

Method clone()

The objects of this class are cloneable with this method.

Usage

CallbackSetLRScheduler$clone(deep = FALSE)

Arguments

• deep: Whether to make a deep clone.