sbss.common.callbacks.CyclicAnnealerCallback¶
- class sbss.common.callbacks.CyclicAnnealerCallback(name: str, cycle: int, max_value: float, ini_period: int = 0, ini_max_value: float = 1.0)[source]¶
Lightning callback that cyclically varies a module attribute during training.
This callback modifies a specified attribute (e.g., a learning rate or coefficient) in the Lightning module according to a cyclic schedule. The value increases linearly within each cycle and resets afterward. An optional initial period can use a different maximum value before switching to the main cycle.
- Parameters:
name (str) – Name of the attribute in the Lightning module to modify.
cycle (int) – Number of training epochs or fraction of total steps that define one cycle.
max_value (float) – Maximum value reached during the cycle.
ini_period (int, optional) – Initial period before cyclic behavior starts. Defaults to 0.
ini_max_value (float, optional) – Maximum value used during the initial period. Defaults to 1.0.
- Returns:
None
- __init__(name: str, cycle: int, max_value: float, ini_period: int = 0, ini_max_value: float = 1.0)[source]¶
Methods
__init__(name, cycle, max_value[, ...])load_state_dict(state_dict)Called when loading a checkpoint, implement to reload callback state given callback's
state_dict.on_after_backward(trainer, pl_module)Called after
loss.backward()and before optimizers are stepped.on_before_backward(trainer, pl_module, loss)Called before
loss.backward().on_before_optimizer_step(trainer, pl_module, ...)Called before
optimizer.step().on_before_zero_grad(trainer, pl_module, ...)Called before
optimizer.zero_grad().on_exception(trainer, pl_module, exception)Called when any trainer execution is interrupted by an exception.
on_fit_end(trainer, pl_module)Called when fit ends.
on_fit_start(trainer, pl_module)Called when fit begins.
on_load_checkpoint(trainer, pl_module, ...)Called when loading a model checkpoint, use to reload state.
on_predict_batch_end(trainer, pl_module, ...)Called when the predict batch ends.
on_predict_batch_start(trainer, pl_module, ...)Called when the predict batch begins.
on_predict_end(trainer, pl_module)Called when predict ends.
on_predict_epoch_end(trainer, pl_module)Called when the predict epoch ends.
on_predict_epoch_start(trainer, pl_module)Called when the predict epoch begins.
on_predict_start(trainer, pl_module)Called when the predict begins.
on_sanity_check_end(trainer, pl_module)Called when the validation sanity check ends.
on_sanity_check_start(trainer, pl_module)Called when the validation sanity check starts.
on_save_checkpoint(trainer, pl_module, ...)Called when saving a checkpoint to give you a chance to store anything else you might want to save.
on_test_batch_end(trainer, pl_module, ...[, ...])Called when the test batch ends.
on_test_batch_start(trainer, pl_module, ...)Called when the test batch begins.
on_test_end(trainer, pl_module)Called when the test ends.
on_test_epoch_end(trainer, pl_module)Called when the test epoch ends.
on_test_epoch_start(trainer, pl_module)Called when the test epoch begins.
on_test_start(trainer, pl_module)Called when the test begins.
on_train_batch_end(trainer, pl_module, ...)Called when the train batch ends.
on_train_batch_start(trainer, pl_module, ...)Called when the train batch begins.
on_train_end(trainer, pl_module)Called when the train ends.
on_train_epoch_end(trainer, pl_module)Called when the train epoch ends.
on_train_epoch_start(trainer, pl_module)Called when the train epoch begins.
on_train_start(trainer, pl_module)Called when the train begins.
on_validation_batch_end(trainer, pl_module, ...)Called when the validation batch ends.
on_validation_batch_start(trainer, ...[, ...])Called when the validation batch begins.
on_validation_end(trainer, pl_module)Called when the validation loop ends.
on_validation_epoch_end(trainer, pl_module)Called when the val epoch ends.
on_validation_epoch_start(trainer, pl_module)Called when the val epoch begins.
on_validation_start(trainer, pl_module)Called when the validation loop begins.
setup(trainer, pl_module, stage)Called when fit, validate, test, predict, or tune begins.
state_dict()Called when saving a checkpoint, implement to generate callback's
state_dict.teardown(trainer, pl_module, stage)Called when fit, validate, test, predict, or tune ends.
Attributes
state_keyIdentifier for the state of the callback.