Hi,
I am using PyTorch for implementing neural net for my columnar (structural) data with mix of categorical and continuous variables. But I am getting TypeError: zip argument #16 must support iteration error while trying to iterate through my dataloader. I have seen below thread but it didn’t help me (as mine is structural data as opposed to images data)

  
    
    
    Error iterating DataLoader 
  
  
    It gives the same error. I think the problem is with test_loader not being iterable!
  


Below is code for creating dataset. I am trying to return a list of df with categorical vars (to be passed into embedding layer) + df with continuous vars and target var.

Screen Shot 2017-12-20 at 2.09.42 PM.png1538×592 83.6 KB

train_dataset = taxi_dataset_from_df(train_feat, cat_vars, train_target) train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=200, shuffle=True) it = iter(train_loader); next(it)[0]
It throws TypeError: zip argument #16 must support iteration error.
I am sorry if this has been discussed before, but I couldn’t find solution on any thread.
thanks in advance