Bug in Pascal5i dataloader

I am using Pascal5i dataloader through the following code but I am unable to iterate it.

from torchmeta.datasets import Pascal5i
from torchmeta.utils.data import BatchMetaDataLoader
import config

def load_trainloader():
     trainset = Pascal5i("data", num_classes_per_task=config.n, meta_train=True, download=True)
     trainloader = BatchMetDataLoader(trainset, batch_size=config.batch_size, shuffle=True, num_workers=0)

    return trainset, trainloader

_, trainloader = load_trainloader()
batch = next(iter(trainloader))

Error:

TypeError                                Traceback (most recent call last)
<ipython-input-8-e4dc503de88f> in <module>
----> 1 batch = next(iter(trainloader))

~/venv/torch-py3/lib/python3.6/site-packages/torch/utils/data/dataloader.py in __next__(self)
343 
344     def __next__(self):
--> 345         data = self._next_data()
346         self._num_yielded += 1
347         if self._dataset_kind == _DatasetKind.Iterable and \

~/venv/torch-py3/lib/python3.6/site-packages/torch/utils/data/dataloader.py in _next_data(self)
383     def _next_data(self):
384         index = self._next_index()  # may raise StopIteration
--> 385         data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
386         if self._pin_memory:
387             data = _utils.pin_memory.pin_memory(data)

~/venv/torch-py3/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py in fetch(self, possibly_batched_index)
 42     def fetch(self, possibly_batched_index):
 43         if self.auto_collation:
---> 44             data = [self.dataset[idx] for idx in possibly_batched_index]
 45         else:
 46             data = self.dataset[possibly_batched_index]

~/venv/torch-py3/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py in <listcomp>(.0)
 42     def fetch(self, possibly_batched_index):
 43         if self.auto_collation:
---> 44             data = [self.dataset[idx] for idx in possibly_batched_index]
 45         else:
 46             data = self.dataset[possibly_batched_index]

~/venv/torch-py3/lib/python3.6/site-packages/torchmeta/utils/data/dataset.py in __getitem__(self, index)
274                 self.num_classes_per_task - 1, index))
275         assert len(index) == self.num_classes_per_task
--> 276         datasets = [self.dataset[i] for i in index]
277         # Use deepcopy on `Categorical` target transforms, to avoid any side
278         # effect across tasks.

~/venv/torch-py3/lib/python3.6/site-packages/torchmeta/utils/data/dataset.py in <listcomp>(.0)
274                 self.num_classes_per_task - 1, index))
275         assert len(index) == self.num_classes_per_task
--> 276         datasets = [self.dataset[i] for i in index]
277         # Use deepcopy on `Categorical` target transforms, to avoid any side
278         # effect across tasks.

~/venv/torch-py3/lib/python3.6/site-packages/torchmeta/datasets/pascal5i.py in __getitem__(self, index)
146 
147         return PascalDataset((data, masks), class_id, transform=transform,
--> 148             target_transform=target_transform)
149 
150     @property

~/venv/torch-py3/lib/python3.6/site-packages/torchmeta/datasets/pascal5i.py in __init__(self, data, class_id, transform, target_transform)
245     def __init__(self, data, class_id, transform=None, target_transform=None):
246         super(PascalDataset, self).__init__(transform=transform,
--> 247             target_transform=target_transform)
248         self.data, self.masks = data
249         self.class_id = class_id

TypeError: __init__() missing 1 required positional argument: 'index'

I posted the same problem on Pytorch discussion forum and came to realize that the 'index' argument is not made optional which is causing this problem. Can you please look into it?

tristandeleu / pytorch-meta

Bug in Pascal5i dataloader #57

Error: