CyclicalScheduler

class ignite.handlers.param_scheduler.CyclicalScheduler(optimizer, param_name, start_value, end_value, cycle_size, cycle_mult=1.0, start_value_mult=1.0, end_value_mult=1.0, warmup_duration=0, save_history=False, param_group_index=None)

An abstract class for updating an optimizer’s parameter value over a cycle of some size.

Parameters

• optimizer (Optimizer) – torch optimizer or any object with attribute param_groups as a sequence.

• param_name (str) – name of optimizer’s parameter to update.

• start_value (float) – value at start of cycle.

• end_value (float) – value at the middle of the cycle.

• cycle_size (int) – length of cycle, value should be larger than 1.

• cycle_mult (float) – ratio by which to change the cycle_size. at the end of each cycle (default=1.0).

• start_value_mult (float) – ratio by which to change the start value at the end of each cycle (default=1.0).

• end_value_mult (float) – ratio by which to change the end value at the end of each cycle (default=1.0).

• warmup_duration (int) – duration of warm-up to be applied before each cycle. Through this warm-up, the parameter starts from the last cycle’s end value and linearly goes to next cycle’s start value. Default is no cyclic warm-up.

• save_history (bool) – whether to log the parameter values to engine.state.param_history, (default=False).

• param_group_index (Optional[int]) – optimizer’s parameters group to use.

Note

If the scheduler is bound to an ‘ITERATION_*’ event, ‘cycle_size’ should usually be the number of batches in an epoch.

New in version 0.4.5.

Changed in version 0.4.13: Added cyclic warm-up to the scheduler using warmup_duration.

Methods