def main(args):
cfg = setup(args)
# disable strict kwargs checking: allow one to specify path handle
# hints through kwargs, like timeout in DP evaluation
PathManager.set_strict_kwargs_checking(False)
if args.eval_only:
model = Trainer.build_model(cfg)
print(parameter_count_table(model, max_depth=2))
DensePoseCheckpointer(model, save_dir=cfg.OUTPUT_DIR).resume_or_load(
cfg.MODEL.WEIGHTS, resume=args.resume
)
res = Trainer.test(cfg, model)
if cfg.TEST.AUG.ENABLED:
res.update(Trainer.test_with_TTA(cfg, model))
if comm.is_main_process():
verify_results(cfg, res)
return res
model = Trainer.build_model(cfg)
print(parameter_count_table(model, max_depth=2))
del model
trainer = Trainer(cfg)
trainer.resume_or_load(resume=args.resume)
if cfg.TEST.AUG.ENABLED:
trainer.register_hooks(
[hooks.EvalHook(0, lambda: trainer.test_with_TTA(cfg, trainer.model))]
)
return trainer.train()
def do_parameter(cfg):
if isinstance(cfg, CfgNode):
model = build_model(cfg)
else:
model = instantiate(cfg.model)
logger.info("Parameter Count:\n" +
parameter_count_table(model, max_depth=5))
def do_parameter(cfg):
model = build_model(cfg)
logger.info("Parameter Count:\n" + parameter_count_table(model, max_depth=5))