Obtaining optimizer state_dict when resuming training

[amazingproducer]

When using the --resume feature of train_ssd.py, it appears as though the learning rate and other optimizations from the previous session are not retained. For example, if the learning rate scheduler has set learning rate to 0.00001 by the final epoch of a session, resuming from that particular epoch will begin training at the default learning rate.

By what means would one effectively use the --resume feature of train_ssd.py and resume training according to the previous session's learning rate scheduler?