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Polynomial Learning Rate Decay Scheduler for PyTorch

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cmpark0126/pytorch-polynomial-lr-decay

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Polynomial Learning Rate Decay Scheduler for PyTorch

This scheduler is frequently used in many DL paper. But there is no official implementation in PyTorch. So I propose this code.

Install

$ pip install git+https://github.com/cmpark0126/pytorch-polynomial-lr-decay.git

Usage

fromtorch_poly_lr_decayimportPolynomialLRDecayscheduler_poly_lr_decay=PolynomialLRDecay(optim,max_decay_steps=100,end_learning_rate=0.0001,power=2.0)forepochinrange(train_epoch):scheduler_poly_lr_decay.step()# you can handle step as epoch number    ...

or

fromtorch_poly_lr_decayimportPolynomialLRDecayscheduler_poly_lr_decay=PolynomialLRDecay(optim,max_decay_steps=100,end_learning_rate=0.0001,power=2.0)...forbatch_idx, (inputs,targets)inenumerate(trainloader):scheduler_poly_lr_decay.step()# also, you can handle step as each iter number

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