Accept iterable as type of input subjects

torchio/data/dataset.py

@@ -1,6 +1,5 @@
 import copy
-import collections
-from typing import Sequence, Optional, Callable
+from typing import Sequence, Optional, Callable, Iterable
 
 from torch.utils.data import Dataset
 
@@ -17,8 +16,7 @@ class SubjectsDataset(Dataset):
     and an optional transform applied to the volumes after loading.
 
     Args:
-        subjects: List of instances of
-            :class:`~torchio.Subject`.
+        subjects: List of instances of :class:`~torchio.Subject`.
         transform: An instance of :class:`~torchio.transforms.Transform`
             that will be applied to each subject.
         load_getitem: Load all subject images before returning it in
@@ -96,7 +94,7 @@ def set_transform(self, transform: Optional[Callable]) -> None:
         self._transform = transform
 
     @staticmethod
-    def _parse_subjects_list(subjects_list: Sequence[Subject]) -> None:
+    def _parse_subjects_list(subjects_list: Iterable[Subject]) -> None:
         # Check that it's an iterable
         try:
             iter(subjects_list)