Spaces:
Running
on
Zero
Running
on
Zero
File size: 2,145 Bytes
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#!/usr/bin/python
# -*- encoding: utf-8 -*-
import torch
import logging
logger = logging.getLogger()
class Optimizer(object):
def __init__(self,
model,
lr0,
momentum,
wd,
warmup_steps,
warmup_start_lr,
max_iter,
power,
*args, **kwargs):
self.warmup_steps = warmup_steps
self.warmup_start_lr = warmup_start_lr
self.lr0 = lr0
self.lr = self.lr0
self.max_iter = float(max_iter)
self.power = power
self.it = 0
wd_params, nowd_params, lr_mul_wd_params, lr_mul_nowd_params = model.get_params()
param_list = [
{'params': wd_params},
{'params': nowd_params, 'weight_decay': 0},
{'params': lr_mul_wd_params, 'lr_mul': True},
{'params': lr_mul_nowd_params, 'weight_decay': 0, 'lr_mul': True}]
self.optim = torch.optim.SGD(
param_list,
lr = lr0,
momentum = momentum,
weight_decay = wd)
self.warmup_factor = (self.lr0/self.warmup_start_lr)**(1./self.warmup_steps)
def get_lr(self):
if self.it <= self.warmup_steps:
lr = self.warmup_start_lr*(self.warmup_factor**self.it)
else:
factor = (1-(self.it-self.warmup_steps)/(self.max_iter-self.warmup_steps))**self.power
lr = self.lr0 * factor
return lr
def step(self):
self.lr = self.get_lr()
for pg in self.optim.param_groups:
if pg.get('lr_mul', False):
pg['lr'] = self.lr * 10
else:
pg['lr'] = self.lr
if self.optim.defaults.get('lr_mul', False):
self.optim.defaults['lr'] = self.lr * 10
else:
self.optim.defaults['lr'] = self.lr
self.it += 1
self.optim.step()
if self.it == self.warmup_steps+2:
logger.info('==> warmup done, start to implement poly lr strategy')
def zero_grad(self):
self.optim.zero_grad()
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