local variable 'mean_cv_score' referenced before assignment

[tjc0726]

---

UnboundLocalError Traceback (most recent call last)
in
----> 1 model.fit( traindata=df_after, ts_column='Timestamp',target='Weighted_Price')

/usr/local/lib/python3.8/dist-packages/auto_ts/init.py in fit(self, traindata, ts_column, target, sep, cv)
750 print(f"Total time taken: {elapsed:.0f} seconds.")
751 print("-"*50 + "\n\n")
--> 752 print("Leaderboard with best model on top of list:\n",self.get_leaderboard())
753 return self
754

/usr/local/lib/python3.8/dist-packages/auto_ts/init.py in get_leaderboard(self, ascending)
904 # else: # Assuming List
905 # mean_cv_score = sum(cv_scores)/len(cv_scores)
--> 906 mean_cv_scores.append(mean_cv_score)
907
908 results = pd.DataFrame({"name": names, self.score_type: mean_cv_scores})

UnboundLocalError: local variable 'mean_cv_score' referenced before assignment

---

So I think the problem is around line 898 in init.py
897 elif isinstance(cv_scores, list): 898 if len(cv_scores) == 0: 899 mean_cv_score = np.inf 900 else: 901 mean_cv_score = self.__get_mean_cv_score(cv_scores) 902 # if isinstance(cv_scores, float): 903 # mean_cv_score = cv_scores 904 # else: # Assuming List 905 # mean_cv_score = sum(cv_scores)/len(cv_scores)
because it doesn't assign the value of mean_cv_score if len(cv_scores) is not equal to 0,I'm not an expert to this frame, but I saw a comment in line 905 says 'assuming list',maybe should put it below 899 like
897 elif isinstance(cv_scores, list): 898 if len(cv_scores) == 0: 899 mean_cv_score = np.inf 900 else: 901 mean_cv_score = sum(cv_scores)/len(cv_scores)

Just my guess

[AutoViML]

I have fixed this error in the ;latest version. Please pip install upgrade like this:

$ pip install auto-ts --upgrade --user

This should fix it - if not, please reopen it.
Thx
Ram

[ssth81456]

fe02913

---

UnboundLocalError Traceback (most recent call last)
in
4 target=target,
5 cv=3,
----> 6 sep=sep)

~\Anaconda3\envs\test\lib\site-packages\auto_ts_init_.py in fit(self, traindata, ts_column, target, sep, cv)
750 print(f"Total time taken: {elapsed:.0f} seconds.")
751 print("-"*50 + "\n\n")
--> 752 print("Leaderboard with best model on top of list:\n",self.get_leaderboard())
753 return self
754

~\Anaconda3\envs\test\lib\site-packages\auto_ts_init_.py in get_leaderboard(self, ascending)
904 # else: # Assuming List
905 # mean_cv_score = sum(cv_scores)/len(cv_scores)
--> 906 mean_cv_scores.append(mean_cv_score)
907
908 results = pd.DataFrame({"name": names, self.score_type: mean_cv_scores})

UnboundLocalError: local variable 'mean_cv_score' referenced before assignment

[AutoViML]

Hello:I found the error and fixed it. Please upgrade via: $ pip install auto-ts --upgrade If you see the version number 0.0.36, it should work.Thanks for your patienceRam On Friday, March 12, 2021, 1:22:52 AM EST, ssth81456 ***@***.***> wrote: fe02913 UnboundLocalError Traceback (most recent call last) in 4 target=target, 5 cv=3, ----> 6 sep=sep) ~\Anaconda3\envs\test\lib\site-packages\auto_ts_init_.py in fit(self, traindata, ts_column, target, sep, cv) 750 print(f"Total time taken: {elapsed:.0f} seconds.") 751 print("-"*50 + "\n\n") --> 752 print("Leaderboard with best model on top of list:\n",self.get_leaderboard()) 753 return self 754 ~\Anaconda3\envs\test\lib\site-packages\auto_ts_init_.py in get_leaderboard(self, ascending) 904 # else: # Assuming List 905 # mean_cv_score = sum(cv_scores)/len(cv_scores) --> 906 mean_cv_scores.append(mean_cv_score) 907 908 results = pd.DataFrame({"name": names, self.score_type: mean_cv_scores}) UnboundLocalError: local variable 'mean_cv_score' referenced before assignment — You are receiving this because you modified the open/close state. Reply to this email directly, view it on GitHub, or unsubscribe.

[ssth81456]

Thanks, updated to 0.0.36 and the issue is solved now.