AttributeError: 'dict' object has no attribute 'check_consistent_spatial_shape' - torchio version 0.18.21

🐛Bug

When attempting to build a PyTorch dataloader for sampling patches, using the example from the torchio.data.Queue class documentation, I get an AttributeError when attempting to sample a single batch of patches.

This seems to exist in version 0.18.21. When I downgrade to 0.18.20, the code works as expected. I am using PyTorch version 1.7.1.

To reproduce

This is directly from the documentation.

import torch
import torchio as tio
from torch.utils.data import DataLoader
patch_size = 96
queue_length = 300
samples_per_volume = 10
sampler = tio.data.UniformSampler(patch_size)
subject = tio.datasets.Colin27()
subjects_dataset = tio.SubjectsDataset(10 * [subject])
patches_queue = tio.Queue(
    subjects_dataset,
    queue_length,
    samples_per_volume,
    sampler,
    num_workers=4,
)
patches_loader = DataLoader(patches_queue, batch_size=16)
batch = next(iter(patches_loader))

Under 0.18.21 I get:

AttributeError                            Traceback (most recent call last)
<ipython-input-28-bf125a1bde76> in <module>
----> 1 batch = next(iter(patches_loader))

~/miniconda3/envs/master/lib/python3.7/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 \

~/miniconda3/envs/master/lib/python3.7/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)

~/miniconda3/envs/master/lib/python3.7/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]

~/miniconda3/envs/master/lib/python3.7/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]

~/miniconda3/envs/master/lib/python3.7/site-packages/torchio/data/queue.py in __getitem__(self, _)
    166         if not self.patches_list:
    167             self._print('Patches list is empty.')
--> 168             self.fill()
    169         sample_patch = self.patches_list.pop()
    170         self.num_sampled_patches += 1

~/miniconda3/envs/master/lib/python3.7/site-packages/torchio/data/queue.py in fill(self)
    232             subject = self.get_next_subject()
    233             iterable = self.sampler(subject)
--> 234             patches = list(islice(iterable, self.samples_per_volume))
    235             self.patches_list.extend(patches)
    236         if self.shuffle_patches:

~/miniconda3/envs/master/lib/python3.7/site-packages/torchio/data/sampler/uniform.py in __call__(self, subject, num_patches)
     24             num_patches: int = None,
     25             ) -> Generator[Subject, None, None]:
---> 26         subject.check_consistent_spatial_shape()
     27
     28         if np.any(self.patch_size > subject.spatial_shape):

AttributeError: 'dict' object has no attribute 'check_consistent_spatial_shape'

Expected behavior

I should be able to retrieve the patches from the Colin27 subject .

Actual behavior

Throws an error

TorchIO version 0.18.21

[fepegar]

I’ve disabled memory pinning in the queue, i.e., reverted some of the changes in #423. If there’s interest in memory pinning, we’ll work on that.

This error shouldn’t happen in v0.18.22. Thanks for reporting, @rayryeng!

[rayryeng]

My pleasure! Thanks for making such an awesome set of tools for training medical models!