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[Sarveshsatheesh]

I've implemented the same logic which was mentioned in this documentation, while performing recocilation
p_rec = rec_model.reconcile(Y_hat_df=p_1, Y_df=train, S=S_train, tags=tags) i got the below error

KeyError Traceback (most recent call last)
File c:\Users\Sarvesh\anaconda3\envs\WAGGLE_AI\Lib\site-packages\pandas\core\indexes\base.py:3805, in Index.get_loc(self, key)
3804 try:
-> 3805 return self._engine.get_loc(casted_key)
3806 except KeyError as err:

File index.pyx:167, in pandas._libs.index.IndexEngine.get_loc()

File index.pyx:196, in pandas._libs.index.IndexEngine.get_loc()

File pandas\_libs\hashtable_class_helper.pxi:7081, in pandas._libs.hashtable.PyObjectHashTable.get_item()

File pandas\_libs\hashtable_class_helper.pxi:7089, in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'AutoARIMA'

The above exception was the direct cause of the following exception:

KeyError Traceback (most recent call last)
Cell In[60], line 1
----> 1 p_rec = rec_model.reconcile(Y_hat_df=p_1, Y_df=train, S=S_train, tags=tags)

File c:\Users\Sarvesh\anaconda3\envs\WAGGLE_AI\Lib\site-packages\hierarchicalforecast\core.py:280, in HierarchicalReconciliation.reconcile(self, Y_hat_df, S, tags, Y_df, level, intervals_method, num_samples, seed, sort_df, is_balanced)
278 y_hat_insample = Y_df[model_name].values.reshape(len(S_df), -1).astype(np.float32)
...
3815 # InvalidIndexError. Otherwise we fall through and re-raise
3816 # the TypeError.
3817 self._check_indexing_error(key)

KeyError: 'AutoARIMA'