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eval.py
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eval.py
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import argparse
import os
import pathlib
import yaml
from pytorch_lightning import Trainer
from pytorch_lightning.loggers.csv_logs import CSVLogger
from dataset import DataModule
from lightning_module import (
PretrainLightningModule,
SSLStepLightningModule,
SSLDualLightningModule,
)
def get_arg():
parser = argparse.ArgumentParser()
parser.add_argument("--config_path", required=True, type=pathlib.Path)
parser.add_argument("--ckpt_path", required=True, type=pathlib.Path)
parser.add_argument(
"--stage", required=True, type=str, choices=["pretrain", "ssl-step", "ssl-dual"]
)
parser.add_argument("--run_name", required=True, type=str)
return parser.parse_args()
def eval(args, config, output_path):
csvlogger = CSVLogger(save_dir=output_path, name="test_log")
trainer = Trainer(
gpus=-1,
deterministic=False,
auto_select_gpus=True,
benchmark=True,
logger=[csvlogger],
default_root_dir=os.getcwd(),
)
if config["general"]["stage"] == "pretrain":
model = PretrainLightningModule(config).load_from_checkpoint(
checkpoint_path=args.ckpt_path, config=config
)
elif config["general"]["stage"] == "ssl-step":
model = SSLStepLightningModule(config).load_from_checkpoint(
checkpoint_path=args.ckpt_path, config=config
)
elif config["general"]["stage"] == "ssl-dual":
model = SSLDualLightningModule(config).load_from_checkpoint(
checkpoint_path=args.ckpt_path, config=config
)
else:
raise NotImplementedError()
datamodule = DataModule(config)
trainer.test(model=model, verbose=True, datamodule=datamodule)
if __name__ == "__main__":
args = get_arg()
config = yaml.load(open(args.config_path, "r"), Loader=yaml.FullLoader)
output_path = str(pathlib.Path(config["general"]["output_path"]) / args.run_name)
config["general"]["stage"] = str(getattr(args, "stage"))
eval(args, config, output_path)