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import yaml
from yaml import Loader
import subprocess
import argparse
parser = argparse.ArgumentParser(description="Experiment Settings")
parser.add_argument("--slurm", default="nlprun -g 1 -d a6000 -r 80G -a model-tracing", type=str)
parser.add_argument("--python", default="python experiment.py", type=str)
parser.add_argument("--models", default="config/llama_flat.yaml", type=str)
parser.add_argument("--save", default="/juice4/scr4/nlp/model-tracing", type=str)
parser.add_argument("--flat", default="all", type=str)
args = parser.parse_args()
model_paths = yaml.load(open(args.models, "r"), Loader=Loader)
subprocess.run(f"mkdir -p {args.save}/logs", shell=True)
subprocess.run(f"mkdir -p {args.save}/results", shell=True)
if args.flat == "all":
for i in range(len(model_paths)):
for j in range(i + 1, len(model_paths)):
model_a = model_paths[i]
model_b = model_paths[j]
job_id = model_a.replace("/", "-") + "_AND_" + model_b.replace("/", "-")
if "miqu" not in job_id:
continue
if job_id[0] == "-":
job_id = job_id[1:]
log_path = args.save + "/logs/" + job_id + ".out"
results_path = args.save + "/results/" + job_id + ".p"
job = (
args.slurm + f" -o {log_path} -n {job_id}"
f" '{args.python}"
+ f" --base_model_id {model_a} --ft_model_id {model_b} --save {results_path}'"
)
subprocess.run(job, shell=True)
elif args.flat == "split":
base_models = model_paths["base_models"]
ft_models = model_paths["ft_models"]
for base_model in base_models:
for ft_model in ft_models:
job_id = base_model.replace("/", "-") + "_AND_" + ft_model.replace("/", "-")
log_path = args.save + "/logs/" + job_id + ".out"
results_path = args.save + "/results/" + job_id + ".p"
job = (
args.slurm + f" -o {log_path} -n {job_id}"
f" '{args.python}"
+ f" --base_model_id {base_model} --ft_model_id {ft_model} --save {results_path}'"
)
subprocess.run(job, shell=True)
elif args.flat == "specified":
models_1 = model_paths["models_1"]
models_2 = model_paths["models_2"]
names_1 = model_paths["names_1"]
names_2 = model_paths["names_2"]
for i in range(len(models_1)):
model_a = models_1[i]
model_b = models_2[i]
name_a = names_1[i]
name_b = names_2[i]
job_id = name_a.replace("/", "-") + "_AND_" + name_b.replace("/", "-")
log_path = args.save + "/logs/" + job_id + ".out"
results_path = args.save + "/results/" + job_id + ".p"
job = (
args.slurm + f" -o {log_path} -n {job_id}"
f" '{args.python}"
+ f" --base_model_id {model_a} --ft_model_id {model_b} --save {results_path}'"
)
subprocess.run(job, shell=True)
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