def run(FLAGS, cfg):
# init parallel environment if nranks > 1
init_parallel_env()
if FLAGS.enable_ce:
set_random_seed(0)
# build trainer
trainer = Trainer(cfg, mode='train')
# load weights
trainer.load_weights(cfg.pretrain_weights, FLAGS.weight_type)
# training
trainer.train()
def run(FLAGS, cfg):
# init fleet environment
if cfg.fleet:
init_fleet_env()
else:
# init parallel environment if nranks > 1
init_parallel_env()
if FLAGS.enable_ce:
set_random_seed(0)
# build trainer
trainer = Trainer(cfg, mode='train')
# load weights
if not FLAGS.slim_config:
trainer.load_weights(cfg.pretrain_weights, FLAGS.weight_type)
# training
trainer.train(FLAGS.eval)
def run(FLAGS, cfg):
# init fleet environment
if cfg.fleet:
init_fleet_env()
else:
# init parallel environment if nranks > 1
init_parallel_env()
if FLAGS.enable_ce:
set_random_seed(0)
# build trainer
trainer = Trainer(cfg, mode='train')
# load weights
if FLAGS.resume is not None:
trainer.resume_weights(FLAGS.resume)
elif 'pretrain_weights' in cfg and cfg.pretrain_weights:
trainer.load_weights(cfg.pretrain_weights)
# training
trainer.train(FLAGS.eval)