Comments (3)
I use another LR scheduler it is OK, maybe there are some problem with ReduceLROnPlateau'???
from pytorch-gradual-warmup-lr.
I think the code is not strong. For ReduceLROnPlateau, you need to remove return self.after_scheduler.get_lr(), or you can add some conditional judgement to distinguish ReduceLROnPlateau and other lr scheduler.
from pytorch-gradual-warmup-lr.
I don't think get_lr
is designed to be an accessible interface for all schedulers. See this issue.
from pytorch-gradual-warmup-lr.
Related Issues (18)
- when i use your readme code ,it has a bug???? HOT 1
- LR not work when pytorch version under 1.2.0
- StepLR and Cos has no funcion like ".get_last_lr()" HOT 1
- What is the meaning of base_lrs? HOT 1
- Math is wrong for multiplier=1 HOT 1
- `warmup_lr` is computed incorrectly in `step_ReduceLROnPlateau` HOT 8
- When to call scheduler.step? HOT 1
- Set Starting learning rate HOT 1
- multiplier works weird HOT 2
- Target optimizer not set properly when loading from state dict
- WARNING: Did not find branch or tag '08f7d5e', assuming revision or ref
- Question of run.py
- Usage mandatory metric HOT 5
- why multiplier must be greater than 1.0? HOT 1
- It seems you got one learning rate per epoch. HOT 2
- the initial lr value is higher than target lr value HOT 2
- optimizer.step() and lr_scheduler.step() HOT 3
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from pytorch-gradual-warmup-lr.