class MultipleLRSchedulers(*args: LRScheduler)[source]#

A wrapper for multiple learning rate schedulers.

Every time step() is called, it calls the step() method of each of the schedulers that it contains. Example usage:

scheduler1 = ConstantLR(opt1, factor=0.1, total_iters=2)
scheduler2 = ExponentialLR(opt2, gamma=0.9)
scheduler = MultipleLRSchedulers(scheduler1, scheduler2)
policy = PPOPolicy(..., lr_scheduler=scheduler)
load_state_dict(state_dict: list[dict]) None[source]#

Load states from state_dict.


state_dict – A list of learning rate scheduler state_dict, in the same order as the schedulers.

state_dict() list[dict][source]#

Get state_dict for each of the learning rate schedulers.


A list of state_dict of learning rate schedulers.

step() None[source]#

Take a step in each of the learning rate schedulers.