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add: GIM (https://github.com/xuelunshen/gim)
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import argparse
from pathlib import Path
from pprint import pprint
from typing import Optional
import pkg_resources
from omegaconf import OmegaConf
from ..models import get_model
from ..settings import TRAINING_PATH
from ..utils.experiments import load_experiment
def parse_config_path(name_or_path: Optional[str], defaults: str) -> Path:
default_configs = {}
for c in pkg_resources.resource_listdir("gluefactory", str(defaults)):
if c.endswith(".yaml"):
default_configs[Path(c).stem] = Path(
pkg_resources.resource_filename("gluefactory", defaults + c)
)
if name_or_path is None:
return None
if name_or_path in default_configs:
return default_configs[name_or_path]
path = Path(name_or_path)
if not path.exists():
raise FileNotFoundError(
f"Cannot find the config file: {name_or_path}. "
f"Not in the default configs {list(default_configs.keys())} "
"and not an existing path."
)
return Path(path)
def extract_benchmark_conf(conf, benchmark):
mconf = OmegaConf.create(
{
"model": conf.get("model", {}),
}
)
if "benchmarks" in conf.keys():
return OmegaConf.merge(mconf, conf.benchmarks.get(benchmark, {}))
else:
return mconf
def parse_eval_args(benchmark, args, configs_path, default=None):
conf = {"data": {}, "model": {}, "eval": {}}
if args.conf:
conf_path = parse_config_path(args.conf, configs_path)
custom_conf = OmegaConf.load(conf_path)
conf = extract_benchmark_conf(OmegaConf.merge(conf, custom_conf), benchmark)
args.tag = (
args.tag if args.tag is not None else conf_path.name.replace(".yaml", "")
)
cli_conf = OmegaConf.from_cli(args.dotlist)
conf = OmegaConf.merge(conf, cli_conf)
conf.checkpoint = args.checkpoint if args.checkpoint else conf.get("checkpoint")
if conf.checkpoint and not conf.checkpoint.endswith(".tar"):
checkpoint_conf = OmegaConf.load(
TRAINING_PATH / conf.checkpoint / "config.yaml"
)
conf = OmegaConf.merge(extract_benchmark_conf(checkpoint_conf, benchmark), conf)
if default:
conf = OmegaConf.merge(default, conf)
if args.tag is not None:
name = args.tag
elif args.conf and conf.checkpoint:
name = f"{args.conf}_{conf.checkpoint}"
elif args.conf:
name = args.conf
elif conf.checkpoint:
name = conf.checkpoint
if len(args.dotlist) > 0 and not args.tag:
name = name + "_" + ":".join(args.dotlist)
print("Running benchmark:", benchmark)
print("Experiment tag:", name)
print("Config:")
pprint(OmegaConf.to_container(conf))
return name, conf
def load_model(model_conf, checkpoint):
if checkpoint:
model = load_experiment(checkpoint, conf=model_conf).eval()
else:
model = get_model("two_view_pipeline")(model_conf).eval()
if not model.is_initialized():
raise ValueError(
"The provided model has non-initialized parameters. "
+ "Try to load a checkpoint instead."
)
return model
def get_eval_parser():
parser = argparse.ArgumentParser()
parser.add_argument("--tag", type=str, default=None)
parser.add_argument("--checkpoint", type=str, default=None)
parser.add_argument("--conf", type=str, default=None)
parser.add_argument("--overwrite", action="store_true")
parser.add_argument("--overwrite_eval", action="store_true")
parser.add_argument("--plot", action="store_true")
parser.add_argument("dotlist", nargs="*")
return parser