A mlr3misc::Dictionary of torch callbacks.
Use t_clbk() to conveniently retrieve callbacks.
Can be converted to a data.table using
as.data.table.
See also
Other Callback:
TorchCallback,
as_torch_callback(),
as_torch_callbacks(),
callback_set(),
mlr_callback_set,
mlr_callback_set.checkpoint,
mlr_callback_set.progress,
mlr_callback_set.tb,
mlr_callback_set.unfreeze,
mlr_context_torch,
t_clbk(),
torch_callback()
Other Dictionary:
mlr3torch_losses,
mlr3torch_optimizers,
t_opt()
Examples
mlr3torch_callbacks$get("checkpoint")
#> <TorchCallback:checkpoint> Checkpoint
#> * Generator: CallbackSetCheckpoint
#> * Parameters: list()
#> * Packages: mlr3torch,torch
# is the same as
t_clbk("checkpoint")
#> <TorchCallback:checkpoint> Checkpoint
#> * Generator: CallbackSetCheckpoint
#> * Parameters: list()
#> * Packages: mlr3torch,torch
# convert to a data.table
as.data.table(mlr3torch_callbacks)
#> Key: <key>
#> key label
#> <char> <char>
#> 1: checkpoint Checkpoint
#> 2: history History
#> 3: lr_cosine_annealing Cosine Annealing LR Scheduler
#> 4: lr_lambda Multiplication by Function LR Scheduler
#> 5: lr_multiplicative Multiplication by Factor LR Scheduler
#> 6: lr_one_cycle 1cyle LR Scheduler
#> 7: lr_reduce_on_plateau Reduce on Plateau LR Scheduler
#> 8: lr_step Step Decay LR Scheduler
#> 9: progress Progress
#> 10: tb TensorBoard
#> 11: unfreeze Unfreeze
#> packages
#> <list>
#> 1: mlr3torch,torch
#> 2: mlr3torch,torch
#> 3: mlr3torch,torch
#> 4: mlr3torch,torch
#> 5: mlr3torch,torch
#> 6: mlr3torch,torch
#> 7: mlr3torch,torch
#> 8: mlr3torch,torch
#> 9: progress,mlr3torch,torch
#> 10: tfevents,mlr3torch,torch
#> 11: mlr3torch,torch