def __init__(self, tensor, inner_scheduler_cfg, last_epoch=-1):
mock_optimizer = torch.optim.SGD([torch.zeros(1)], lr=tensor.item())
self.tensor = tensor
scheduler_cls = get_scheduler_cls(inner_scheduler_cfg.pop("type"))
self.inner_scheduler = scheduler_cls(mock_optimizer,
**inner_scheduler_cfg)
super(TensorScheduler, self).__init__(mock_optimizer, last_epoch)
def init_scheduler(optimizer, cfg):
if cfg and optimizer is not None:
cfg = {k:v for k, v in six.iteritems(cfg)}
sch_cls = get_scheduler_cls(cfg.pop("type"))
return sch_cls(optimizer, **cfg)
return None
