benchmarks/feedback/scripts/eval.py

import sys
import sys
import os
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "../env"))
from importlib import reload
import train
reload(train)
import pandas as pd
from train import compute_metrics_for_regression, DIMENSIONS
import numpy as np

def get_score(submission_folder = "../env"):
    submission_path = os.path.join(submission_folder, "submission.csv")
    solution = pd.read_csv(os.path.join(os.path.dirname(__file__), "answer.csv"))[DIMENSIONS].to_numpy()
    submission = pd.read_csv(submission_path)[DIMENSIONS].to_numpy()

    metrics = compute_metrics_for_regression(solution, submission)
    return np.mean(list(metrics.values()))

if __name__ == "__main__":
    print(get_score())