mlr_callback_set.lr_scheduler: Learning Rate Scheduling Callback

In mlr3torch: Deep Learning with 'mlr3'

Learning Rate Scheduling Callback

Description

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() (where the default values for epochs and steps_per_epoch are the number of training epochs and the number of batches per epoch)

• 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

• CallbackSetLRScheduler$new()

• CallbackSetLRScheduler$on_begin()

• CallbackSetLRScheduler$clone()

Inherited methods

• mlr3torch::CallbackSet$load_state_dict()
• mlr3torch::CallbackSet$print()
• mlr3torch::CallbackSet$state_dict()

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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 initialization arguments.

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Method on_begin()

Creates the scheduler using the optimizer from the context

Usage

CallbackSetLRScheduler$on_begin()

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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.

mlr3torch documentation built on Aug. 26, 2025, 5:09 p.m.