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import os.path
import numpy as np
import pandas as pd
import argparse
from sklearn.metrics import roc_auc_score
parser = argparse.ArgumentParser()
parser.add_argument('--path', type=str, required=True)
parser.add_argument('--name', type=str, required=True)
parser.add_argument('--answer_file', type=str, required=True)
parser.add_argument('--predict_file', type=str, required=True)
parser.add_argument('--value', type=str, default="generated")
args = parser.parse_args()
actual = pd.read_csv( args.answer_file)
submission = pd.read_csv(args.predict_file)
# 移除id列，剩下的是矩阵的值
submission_values = submission.drop(columns=['id']).values
actual_values = actual.drop(columns=['id']).values
# 计算平均绝对误差
performance = np.mean(np.abs(submission_values - actual_values))
with open(os.path.join(args.path, args.name, "result.txt"), "w") as f:
f.write(str(performance))
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