caser_pytorch
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Padding issue, when trying to run the traning on ml1m validation set
I got this error when trying I run the model on /ml1m/validation/{train,test}.txt set (a.k.a validation set) , meanwhile it works just fine for /ml1m/validation/{train,test}.txt set :
Traceback (most recent call last):
File "train_caser.py", line 335, in <module>
model.fit(train, test, verbose=True)
File "train_caser.py", line 181, in fit
precision, recall, mean_aps = evaluate_ranking(self, test, train, k=[1, 5, 10])
File "C:\Users\username\JupyterLab\caser_pytorch-master\evaluation.py", line 53, in evaluate_ranking
test = test.tocsr()
File "C:\Users\username\JupyterLab\caser_pytorch-master\interactions.py", line 92, in tocsr
return self.tocoo().tocsr()
File "C:\Users\username\JupyterLab\caser_pytorch-master\interactions.py", line 84, in tocoo
return sp.coo_matrix((data, (row, col)),
File "C:\Users\username\Anaconda3\envs\PT1_6\lib\site-packages\scipy\sparse\coo.py", line 196, in __init__
self._check()
File "C:\Users\username\Anaconda3\envs\PT1_6\lib\site-packages\scipy\sparse\coo.py", line 285, in _check
raise ValueError('column index exceeds matrix dimensions')
ValueError: column index exceeds matrix dimensions
Is there any explanation ?
ps: it's works fine when I comment the padding code (or putting a boolean variable to False), like fellow :
def to_sequence(self, sequence_length=5, target_length=1, padding=True):
...
# change the item index start from 1 as 0 is used for padding in sequences
if padding:
for k, v in self.item_map.items():
self.item_map[k] = v + 1
self.item_ids = self.item_ids + 1
self.num_items += 1
...
although, I think it's totally wrong not doing the padding !
Hi @MayloIFERR , sorry for the late reply. I ran the code with validation dataset while I cannot reproduce your error. From the error message, the error seems to come from scipy. Could you please use a different version of scipy (as well as pandas and numpy, I used scipy v1.2, pandas v0.24 and numpy v1.16) and see if the error go away?
Feel free to close the issue if you find a solution for it.
I have the same problem. Have you solved it?