elch10/dfs

Implementation of Deep Feature Selection algorithm

dfs's Issues

A "MisconfigurationException:" error occurred when I executed the code

I downloaded the notebooks and dataset from the project. I executed the codes using jupyter notebook, and the codes were
running successfully until this one:

from pytorch_lightning import Trainer
from test_tube import Experiment
import os

model = CoolSystem(loss_attrs=loss_attrs, class_weights=class_weights)

# PyTorch summarywriter with a few bells and whistles    
exp = Experiment(save_dir=os.getcwd())

# train on cpu using only 10% of the data (for demo purposes)
# pass in experiment for automatic tensorboard logging.    
trainer = Trainer(experiment=exp, max_nb_epochs=20, gpus=[0])

  
trainer.fit(model)

and I got the error below:

---------------------------------------------------------------------------
MisconfigurationException                 Traceback (most recent call last)
<ipython-input-28-de23d35f9938> in <module>()
     13 
     14 
---> 15 trainer.fit(model)

4 frames
/usr/local/lib/python3.6/dist-packages/pytorch_lightning/trainer/data_loading.py in reset_train_dataloader(self, model)
    128                 must be an int. An int k specifies checking validation every k training batches.
    129                 '''
--> 130                 raise MisconfigurationException(m)
    131 
    132             self._percent_range_check('val_check_interval')

MisconfigurationException: 
                When using an infinite DataLoader (e.g. with an IterableDataset or when DataLoader
                does not implement `__len__`) for `train_dataloader`, `Trainer(val_check_interval)`
                must be an int. An int k specifies checking validation every k training batches.
                

After searching some help from Google and Stackoverflow, I still don't get the solution. Is there any way to solve this? Thanks