alfa-group / robust-adv-malware-detection Goto Github PK

(nn_mal) sivakumars-MBP:ab kiranrishika$ python generate_vectors.py
Starting data loading
Malware Files: 19000
Benign Files: 19000
Preparing training datasets
Preparing validation datasets
Preparing testing datasets
hi
15200
15200
malicious
<class 'str'>
<torch.utils.data.dataloader.DataLoader object at 0x129777ef0>
Traceback (most recent call last):
File "generate_vectors.py", line 30, in
for index, data in enumerate(dataloader):
File "/Users/kiranrishika/anaconda3/envs/nn_mal/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 637, in next
return self._process_next_batch(batch)
File "/Users/kiranrishika/anaconda3/envs/nn_mal/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 658, in _process_next_batch
raise batch.exc_type(batch.exc_msg)
TypeError: Traceback (most recent call last):
File "/Users/kiranrishika/anaconda3/envs/nn_mal/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 138, in _worker_loop
samples = collate_fn([dataset[i] for i in batch_indices])
File "/Users/kiranrishika/anaconda3/envs/nn_mal/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 232, in default_collate
return [default_collate(samples) for samples in transposed]
File "/Users/kiranrishika/anaconda3/envs/nn_mal/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 232, in
return [default_collate(samples) for samples in transposed]
File "/Users/kiranrishika/anaconda3/envs/nn_mal/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 234, in default_collate
raise TypeError((error_msg.format(type(batch[0]))))
TypeError: batch must contain tensors, numbers, dicts or lists; found <class 'NoneType'>

Hey, @ash-aldujaili @hembergerik @alhuang10 I have submitted the google docs form three times, but I still haven't received the dataset. I was wondering if there is something else I should do in order to qualify.

Also regarding the dataset, are the contents of the datasets actual binaries for the malwares? If so, do I then run the generate_vectors.py script to extract the features?