"""Evaluation tasks - modified from https://github.com/EleutherAI/lm-evaluation-harness"""
import os
import sys
sys.path.append(
os.path.abspath(os.path.join(os.path.dirname(__file__), os.path.pardir))
)
from megatron.training import forward_step
from megatron.utils import setup_for_inference_or_eval, init_wandb
from megatron.logging import tb_wandb_log
from eval_tasks import run_eval_harness
from pprint import pprint
from datetime import datetime
import json
def main():
model, neox_args = setup_for_inference_or_eval(use_cache=False)
results = run_eval_harness(
model,
forward_step,
neox_args,
eval_tasks=neox_args.eval_tasks,
bootstrap_iters=10000,
)
if neox_args.rank == 0:
init_wandb(neox_args=neox_args)
for k, v in results["results"].items():
if isinstance(v, dict):
for k2, v2 in v.items():
k3 = "_".join([k, k2])
tb_wandb_log(
f"eval/{k3}",
v2,
neox_args.iteration,
use_wandb=neox_args.use_wandb,
)
else:
tb_wandb_log(
f"eval/{k}",
v,
neox_args.iteration,
use_wandb=neox_args.use_wandb,
)
pprint(results)
results_path = (
f'eval_results_{datetime.now().strftime("%m-%d-%Y-%H-%M-%S")}.json'
)
if neox_args.eval_results_prefix:
results_path = f"{neox_args.eval_results_prefix}_{results_path}"
with open(results_path, "w") as f:
json.dump(results, f, indent=4)
if __name__ == "__main__":
main()