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"""
Take in a YAML, and output all "other" splits with this YAML
"""
import argparse
import logging
import os
import yaml
from tqdm import tqdm
eval_logger = logging.getLogger("lm-eval")
SUBJECTS = {
"abstract_algebra": "stem",
"anatomy": "stem",
"astronomy": "stem",
"business_ethics": "other",
"clinical_knowledge": "other",
"college_biology": "stem",
"college_chemistry": "stem",
"college_computer_science": "stem",
"college_mathematics": "stem",
"college_medicine": "other",
"college_physics": "stem",
"computer_security": "stem",
"conceptual_physics": "stem",
"econometrics": "social_sciences",
"electrical_engineering": "stem",
"elementary_mathematics": "stem",
"formal_logic": "humanities",
"global_facts": "other",
"high_school_biology": "stem",
"high_school_chemistry": "stem",
"high_school_computer_science": "stem",
"high_school_european_history": "humanities",
"high_school_geography": "social_sciences",
"high_school_government_and_politics": "social_sciences",
"high_school_macroeconomics": "social_sciences",
"high_school_mathematics": "stem",
"high_school_microeconomics": "social_sciences",
"high_school_physics": "stem",
"high_school_psychology": "social_sciences",
"high_school_statistics": "stem",
"high_school_us_history": "humanities",
"high_school_world_history": "humanities",
"human_aging": "other",
"human_sexuality": "social_sciences",
"international_law": "humanities",
"jurisprudence": "humanities",
"logical_fallacies": "humanities",
"machine_learning": "stem",
"management": "other",
"marketing": "other",
"medical_genetics": "other",
"miscellaneous": "other",
"moral_disputes": "humanities",
"moral_scenarios": "humanities",
"nutrition": "other",
"philosophy": "humanities",
"prehistory": "humanities",
"professional_accounting": "other",
"professional_law": "humanities",
"professional_medicine": "other",
"professional_psychology": "social_sciences",
"public_relations": "social_sciences",
"security_studies": "social_sciences",
"sociology": "social_sciences",
"us_foreign_policy": "social_sciences",
"virology": "other",
"world_religions": "humanities",
}
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--base_yaml_path", required=True)
parser.add_argument("--save_prefix_path", default="mmlu")
parser.add_argument("--cot_prompt_path", default=None)
parser.add_argument("--task_prefix", default="")
parser.add_argument("--group_prefix", default="")
return parser.parse_args()
if __name__ == "__main__":
args = parse_args()
# get filename of base_yaml so we can `"include": ` it in our "other" YAMLs.
base_yaml_name = os.path.split(args.base_yaml_path)[-1]
with open(args.base_yaml_path, encoding="utf-8") as f:
base_yaml = yaml.full_load(f)
if args.cot_prompt_path is not None:
import json
with open(args.cot_prompt_path, encoding="utf-8") as f:
cot_file = json.load(f)
ALL_CATEGORIES = []
for subject, category in tqdm(SUBJECTS.items()):
if category not in ALL_CATEGORIES:
ALL_CATEGORIES.append(category)
if args.cot_prompt_path is not None:
description = cot_file[subject]
else:
description = f"The following are multiple choice questions (with answers) about {' '.join(subject.split('_'))}.\n\n"
yaml_dict = {
"include": base_yaml_name,
"group": f"mmlu_{args.task_prefix}_{category}"
if args.task_prefix != ""
else f"mmlu_{category}",
"group_alias": category.replace("_", " "),
"task": f"mmlu_{args.task_prefix}_{subject}"
if args.task_prefix != ""
else f"mmlu_{subject}",
"task_alias": subject.replace("_", " "),
"dataset_name": subject,
"description": description,
}
file_save_path = args.save_prefix_path + f"_{subject}.yaml"
eval_logger.info(f"Saving yaml for subset {subject} to {file_save_path}")
with open(file_save_path, "w", encoding="utf-8") as yaml_file:
yaml.dump(
yaml_dict,
yaml_file,
allow_unicode=True,
default_style='"',
)
if args.task_prefix != "":
mmlu_subcategories = [
f"mmlu_{args.task_prefix}_{category}" for category in ALL_CATEGORIES
]
else:
mmlu_subcategories = [f"mmlu_{category}" for category in ALL_CATEGORIES]
if args.group_prefix != "":
file_save_path = args.group_prefix + ".yaml"
else:
file_save_path = args.save_prefix_path + ".yaml"
eval_logger.info(f"Saving benchmark config to {file_save_path}")
with open(file_save_path, "w", encoding="utf-8") as yaml_file:
yaml.dump(
{
"group": f"mmlu_{args.task_prefix}"
if args.task_prefix != ""
else "mmlu",
"task": mmlu_subcategories,
},
yaml_file,
indent=4,
default_flow_style=False,
)
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