def steplr_wrapper(optimizer):
pytorch_support(required_version='1.0.0',
info_str='LRScheduler - StepLR')
return optim.lr_scheduler.StepLR(optimizer,
step_size=args.step_size,
gamma=args.gamma,
last_epoch=args.last_epoch)
def cosineannealinglr_wrapper(optimizer):
pytorch_support(required_version='1.0.0',
info_str='LRScheduler - CosineAnnealingLR')
return optim.lr_scheduler.CosineAnnealingLR(optimizer,
T_max=args.T_max,
eta_min=args.eta_min,
last_epoch=args.last_epoch)
def multisteplr_wrapper(optimizer):
pytorch_support(required_version='1.0.0',
info_str='LRScheduler - MultiStepLR')
return optim.lr_scheduler.MultiStepLR(optimizer,
milestones=args.milestones,
gamma=args.gamma,
last_epoch=args.last_epoch)
def polynomiallr_wrapper(optimizer):
pytorch_support(required_version='1.0.0',
info_str='LRScheduler - PolynomialLR')
return PolynomialLR(optimizer,
epochs=args.epochs,
iters_per_epoch=args.iters_per_epoch,
power=args.power,
last_epoch=args.last_epoch)
def run_script(config, proxy_file, proxy_class):
# PixelSSL requires PyTorch >= 1.0.0
pytorch_support(required_version='1.0.0', info_str='PixelSSL')
# help information
if len(sys.argv) > 1 and sys.argv[1] in ['help', '--help', 'h', '-h']:
config['h'] = True
# create parser and parse args from config
parser = create_parser(config['ssl_algorithm'])
proxy_file.add_parser_arguments(parser)
args = cmd.parse_args(parser, config)
task_proxy = proxy_class(args)
task_proxy.run()
def exponentiallr_wrapper(optimizer):
pytorch_support(required_version='1.0.0',
info_str='LRScheduler - ExponentialLR')
return optim.lr_scheduler.ExponentialLR(optimizer,
gamma=args.gamma,
last_epoch=args.last_epoch)