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#!/usr/bin/env python3 | |
# coding=utf-8 | |
from utility.schedule.linear_lr import LinearLr | |
def multi_scheduler_wrapper(optimizer, args, steps_per_epoch): | |
n_layers = (len(optimizer.param_groups) - 2) // 2 | |
return MultiScheduler( | |
[ | |
LinearLr(optimizer.param_groups[i], args.encoder_learning_rate * (args.layerwise_lr_decay ** i), args.epochs * steps_per_epoch, False, args.lr_decay_multiplier) | |
for i in range(n_layers) | |
] | |
+ | |
[ | |
LinearLr(optimizer.param_groups[n_layers + i], args.encoder_learning_rate * (args.layerwise_lr_decay ** i), args.epochs * steps_per_epoch, False, args.lr_decay_multiplier) | |
for i in range(n_layers) | |
] | |
+ | |
[ | |
LinearLr(optimizer.param_groups[-2], args.decoder_learning_rate, args.epochs * steps_per_epoch, False, args.lr_decay_multiplier), | |
LinearLr(optimizer.param_groups[-1], args.decoder_learning_rate, args.epochs * steps_per_epoch, False, args.lr_decay_multiplier) | |
] | |
) | |
class MultiScheduler: | |
def __init__(self, schedulers): | |
self.schedulers = schedulers | |
def __call__(self, epoch): | |
for scheduler in self.schedulers: | |
scheduler(epoch) | |
def lr(self) -> float: | |
return [scheduler.lr() for scheduler in self.schedulers] | |