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# neural-forecast
s
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j
Hey. The features must be a list, and the tune choice expects a sequence, so what's happening is that you're providing
'hist_exog_list': 'x_7'
and it should be
'hist_exog_list': ['x_7']
so the config for tune should be something like:
hist_exog_list: tune.choice([['x_7']])
About the 700 exogenous the problem is memory, so it's really up to the hardware, but i'd say it's probably going to run out of memory.
u
Thanks for the quick replying! After I changing to the 'list' as you shown above, the new Exception occurs:
Copy code
(_train_tune pid=2432)   File "/usr/local/lib/python3.10/dist-packages/neuralforecast/common/_base_windows.py", line 336, in _get_temporal_data_cols
(_train_tune pid=2432)     set(temporal_cols.tolist()) & set(self.hist_exog_list + self.futr_exog_list)
(_train_tune pid=2432) TypeError: can only concatenate tuple (not "list") to tuple
The value I used is pure integer value.
The way I fixed this is by setting the *futr_exog_list: tune.ch*oice([[]])) in the config dictionary... Could you please explain why is this happening (it must require hist and futr setting?), and the way I do this would affect the model training or not. Thanks!
j
Did you provide it like I suggested? Seems like the hist_exog_list is a tuple instead of a list
l
@王梦石, would you not want to do feature selection first before you feed into the nfc models since you have 700 exogenous features?
u
Hi Jose, I did exactly as your suggestion. If I do not specify the 'futr_exog_list' as an empty list, the error still exist there. It's kinda weird
@José Morales, Hi Jose, I did exactly as your suggestion. If I do not specify the 'futr_exog_list' as an empty list, the error still exist there. It's kinda weird. I have also checked the ray codes, it convert all the lists into tuples for the hyperparameter options to tune.
j
I think this is what it does internally, so if you specify it as a list it should return it as a list