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Currently, lr_scheduler is stored differently as optimizer, model and data_loader, with keys to be "lr_scheduler_0", "lr_scheduler_1", ... stored in the state
This PR aims to flatten lr_shceduler so that all the schedulers would be stored as a list under self.state['lr_scheduler'], which is consistent with optimizer, model and data_loader
The PR is tested by 2 parts:
before and after this PR, lr_shceduler values are the same
Memory trace:
Before the flatten, rerun llama3_8b.toml from step 5 to step 10:
After the flatten, rerun llama3_8b.toml from step 5 to step 10: