def get_lr_scheduler(optimizer, mode='max', factor=0.5, patience=10, threshold=1e-4, threshold_mode='rel'):
def reduce_lr(self, epoch):
ReduceLROnPlateau._reduce_lr(self, epoch)
lr_scheduler = ReduceLROnPlateau(optimizer, mode, factor, patience, False, threshold, threshold_mode)
lr_scheduler._reduce_lr = partial(reduce_lr, lr_scheduler)
return lr_scheduler
def get_lr_scheduler(logger, optimizer, mode='max', factor=0.5, patience=10, threshold=1e-4, threshold_mode='rel'):
def reduce_lr(self, epoch):
ReduceLROnPlateau._reduce_lr(self, epoch)
logger.info(f"learning rate is reduced by factor {factor}!")
lr_scheduler = ReduceLROnPlateau(optimizer, mode, factor, patience, False, threshold, threshold_mode)
lr_scheduler._reduce_lr = partial(reduce_lr, lr_scheduler)
return lr_scheduler
def get_lr_scheduler(logger, optimizer):
def reduce_lr(self, epoch):
ReduceLROnPlateau._reduce_lr(self, epoch)
logger.info("learning rate is reduced by factor 0.2!")
lr_scheduler = ReduceLROnPlateau(optimizer, mode="max", factor=0.2, patience=10, threshold=0.005,
threshold_mode="rel")
lr_scheduler._reduce_lr = partial(reduce_lr, lr_scheduler)
return lr_scheduler
def reduce_lr(self, epoch):
ReduceLROnPlateau._reduce_lr(self, epoch)
def reduce_lr(self, epoch):
ReduceLROnPlateau._reduce_lr(self, epoch)
logger.info(f"learning rate is reduced by factor {factor}!")
