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from utils.hparams import hparams | |
class NoneSchedule(object): | |
def __init__(self, optimizer): | |
super().__init__() | |
self.optimizer = optimizer | |
self.constant_lr = hparams['lr'] | |
self.step(0) | |
def step(self, num_updates): | |
self.lr = self.constant_lr | |
for param_group in self.optimizer.param_groups: | |
param_group['lr'] = self.lr | |
return self.lr | |
def get_lr(self): | |
return self.optimizer.param_groups[0]['lr'] | |
def get_last_lr(self): | |
return self.get_lr() | |
class RSQRTSchedule(object): | |
def __init__(self, optimizer): | |
super().__init__() | |
self.optimizer = optimizer | |
self.constant_lr = hparams['lr'] | |
self.warmup_updates = hparams['warmup_updates'] | |
self.hidden_size = hparams['hidden_size'] | |
self.lr = hparams['lr'] | |
for param_group in optimizer.param_groups: | |
param_group['lr'] = self.lr | |
self.step(0) | |
def step(self, num_updates): | |
constant_lr = self.constant_lr | |
warmup = min(num_updates / self.warmup_updates, 1.0) | |
rsqrt_decay = max(self.warmup_updates, num_updates) ** -0.5 | |
rsqrt_hidden = self.hidden_size ** -0.5 | |
self.lr = max(constant_lr * warmup * rsqrt_decay * rsqrt_hidden, 1e-7) | |
for param_group in self.optimizer.param_groups: | |
param_group['lr'] = self.lr | |
return self.lr | |
def get_lr(self): | |
return self.optimizer.param_groups[0]['lr'] | |
def get_last_lr(self): | |
return self.get_lr() | |