TypeError: only integer scalar arrays can be converted to a scalar index

[DieHumbleX]

I am trying to run this tutorial ( https://colab.research.google.com/github/fepegar/torchio-notebooks/blob/main/notebooks/TorchIO_tutorial.ipynb#scrollTo=zzVqpgRf5eFN )

i get following error:

TypeError                                 Traceback (most recent call last)
<ipython-input-25-5b4812ec9e10> in <module>
----> 1 one_batch = next(iter(training_loader))

/opt/conda/lib/python3.6/site-packages/torch/utils/data/dataloader.py in __next__(self)
    433         if self._sampler_iter is None:
    434             self._reset()
--> 435         data = self._next_data()
    436         self._num_yielded += 1
    437         if self._dataset_kind == _DatasetKind.Iterable and \

/opt/conda/lib/python3.6/site-packages/torch/utils/data/dataloader.py in _next_data(self)
    473     def _next_data(self):
    474         index = self._next_index()  # may raise StopIteration
--> 475         data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
    476         if self._pin_memory:
    477             data = _utils.pin_memory.pin_memory(data)

/opt/conda/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]

/opt/conda/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]

/opt/conda/lib/python3.6/site-packages/torchio/data/dataset.py in __getitem__(self, index)
     83         # Apply transform (this is usually the bottleneck)
     84         if self._transform is not None:
---> 85             subject = self._transform(subject)
     86         return subject
     87 

/opt/conda/lib/python3.6/site-packages/torchio/transforms/transform.py in __call__(self, data)
    119             subject = copy.copy(subject)
    120         with np.errstate(all='raise'):
--> 121             transformed = self.apply_transform(subject)
    122         if self.keep is not None:
    123             for name, image in images_to_keep.items():

/opt/conda/lib/python3.6/site-packages/torchio/transforms/augmentation/composition.py in apply_transform(self, subject)
     45     def apply_transform(self, subject: Subject) -> Subject:
     46         for transform in self.transforms:
---> 47             subject = transform(subject)
     48         return subject
     49 

/opt/conda/lib/python3.6/site-packages/torchio/transforms/transform.py in __call__(self, data)
    119             subject = copy.copy(subject)
    120         with np.errstate(all='raise'):
--> 121             transformed = self.apply_transform(subject)
    122         if self.keep is not None:
    123             for name, image in images_to_keep.items():

/opt/conda/lib/python3.6/site-packages/torchio/transforms/augmentation/spatial/random_flip.py in apply_transform(self, subject)
     57         }
     58         transform = Flip(**self.add_include_exclude(arguments))
---> 59         transformed = transform(subject)
     60         return transformed
     61 

/opt/conda/lib/python3.6/site-packages/torchio/transforms/transform.py in __call__(self, data)
    119             subject = copy.copy(subject)
    120         with np.errstate(all='raise'):
--> 121             transformed = self.apply_transform(subject)
    122         if self.keep is not None:
    123             for name, image in images_to_keep.items():

/opt/conda/lib/python3.6/site-packages/torchio/transforms/augmentation/spatial/random_flip.py in apply_transform(self, subject)
     88         axes = _ensure_axes_indices(subject, self.axes)
     89         for image in self.get_images(subject):
---> 90             _flip_image(image, axes)
     91         return subject
     92 

/opt/conda/lib/python3.6/site-packages/torchio/transforms/augmentation/spatial/random_flip.py in _flip_image(image, axes)
    125     spatial_axes = np.array(axes) + 1
    126     data = image.numpy()
--> 127     data = np.flip(data, axis=spatial_axes)
    128     data = data.copy()  # remove negative strides
    129     data = torch.as_tensor(data)

/opt/conda/lib/python3.6/site-packages/numpy/lib/function_base.py in flip(m, axis)
    204     indexer = [slice(None)] * m.ndim
    205     try:
--> 206         indexer[axis] = slice(None, None, -1)
    207     except IndexError:
    208         raise ValueError("axis=%i is invalid for the %i-dimensional input array"

TypeError: only integer scalar arrays can be converted to a scalar index

[DieHumbleX]

Code works on commenting tio.RandomFlip()

[fepegar]

What version of NumPy are you using? For bugs, next time you can open an issue using the "bug report" template.

[DieHumbleX]

1.14.5 Sure i will do that. Thanks again for your prompt response.

[fepegar]

Thanks. That version is almost 3 years old. Could you please upgrade NumPy and try again?

[fepegar]

(For reference, this change should prevent this issue in the future: 503fb85)

[DieHumbleX]

Thanks!!