VAPO_data_demo / compute_model_output_len.py
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from utils_display import model_info
from data_utils import load_infer_results
from tqdm import tqdm
import json
length_info = {}
for model_name in tqdm(list(model_info.keys())):
result = load_infer_results(model_name)
lens = []
for item in result:
o = item["output"]
if type(o) == list:
L = len(o[0].strip())
else:
L = len(o.strip())
if L > 0:
lens.append(L)
avg_len = sum(lens) / len(lens)
print(f"{model_name}: {avg_len}")
length_info[model_name] = avg_len
with open("model_len_info.json", "w") as f:
json.dump(length_info, f, indent=2)