"""
Modified from https://github.com/microsoft/Swin-Transformer/blob/main/lr_scheduler.py
"""
import logging
import math
import numpy as np
import oneflow as flow
from .scheduler import Scheduler
[docs]class LinearLRScheduler(Scheduler):
"""
Linear warmup and linear decay scheduler
Inspiration from
https://github.com/microsoft/Swin-Transformer/blob/main/lr_scheduler.py
Args:
optimizer: The optimizer will be used for the training process
t_initial: The initial number of epochs. Example, 50, 100 etc.
t_mul: updates the SGDR schedule annealing.
lr_min_rate: The minimum learning rate factor to use during the scheduling.
The learning rate does not ever go below to ``lr * lr_min_rate``.
warmup_t: Defines the number of warmup epochs.
warmup_lr_init: The initial learning rate during warmup.
"""
def __init__(
self,
optimizer: flow.optim.Optimizer,
t_initial: int,
lr_min_rate: float,
warmup_t=0,
warmup_lr_init=0.0,
t_in_epochs=True,
noise_range_t=None,
noise_pct=0.67,
noise_std=1.0,
noise_seed=42,
initialize=True,
) -> None:
super().__init__(
optimizer,
param_group_field="lr",
noise_range_t=noise_range_t,
noise_pct=noise_pct,
noise_std=noise_std,
noise_seed=noise_seed,
initialize=initialize,
)
self.t_initial = t_initial
self.lr_min_rate = lr_min_rate
self.warmup_t = warmup_t
self.warmup_lr_init = warmup_lr_init
self.t_in_epochs = t_in_epochs
if self.warmup_t:
self.warmup_steps = [
(v - warmup_lr_init) / self.warmup_t for v in self.base_values
]
super().update_groups(self.warmup_lr_init)
else:
self.warmup_steps = [1 for _ in self.base_values]
def _get_lr(self, t):
if t < self.warmup_t:
lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps]
else:
t = t - self.warmup_t
total_t = self.t_initial - self.warmup_t
lrs = [
v - ((v - v * self.lr_min_rate) * (t / total_t))
for v in self.base_values
]
return lrs
def get_epoch_values(self, epoch: int):
if self.t_in_epochs:
return self._get_lr(epoch)
else:
return None
def get_update_values(self, num_updates: int):
if not self.t_in_epochs:
return self._get_lr(num_updates)
else:
return None