RuntimeError: Standard deviation is 0 for masked values in image "default_image_name" (None)

[paul-reiners]

Does anyone know what might be causing this error:

python-BaseException
Traceback (most recent call last):
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastai/data/load.py", line 172, in one_batch
    with self.fake_l.no_multiproc(): res = first(self)
                                           ^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastcore/basics.py", line 681, in first
    return next(x, None)
           ^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastai/data/load.py", line 127, in __iter__
    for b in _loaders[self.fake_l.num_workers==0](self.fake_l):
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/torch/utils/data/dataloader.py", line 633, in __next__
    data = self._next_data()
           ^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/torch/utils/data/dataloader.py", line 677, in _next_data
    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/torch/utils/data/_utils/fetch.py", line 41, in fetch
    data = next(self.dataset_iter)
           ^^^^^^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastai/data/load.py", line 138, in create_batches
    yield from map(self.do_batch, self.chunkify(res))
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastcore/basics.py", line 234, in chunked
    res = list(itertools.islice(it, chunk_sz))
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastai/data/load.py", line 153, in do_item
    try: return self.after_item(self.create_item(s))
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastcore/transform.py", line 208, in __call__
    def __call__(self, o): return compose_tfms(o, tfms=self.fs, split_idx=self.split_idx)
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastcore/transform.py", line 158, in compose_tfms
    x = f(x, **kwargs)
        ^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastcore/transform.py", line 81, in __call__
    def __call__(self, x, **kwargs): return self._call('encodes', x, **kwargs)
                                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastcore/transform.py", line 91, in _call
    return self._do_call(getattr(self, fn), x, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastcore/transform.py", line 98, in _do_call
    res = tuple(self._do_call(f, x_, **kwargs) for x_ in x)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastcore/transform.py", line 98, in <genexpr>
    res = tuple(self._do_call(f, x_, **kwargs) for x_ in x)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastcore/transform.py", line 97, in _do_call
    return retain_type(f(x, **kwargs), x, ret)
                       ^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastcore/dispatch.py", line 120, in __call__
    return f(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastMONAI/vision_augmentation.py", line 88, in encodes
    o = torch.stack([self.z_normalization(c[None])[0] for c in o])
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/fastMONAI/vision_augmentation.py", line 88, in <listcomp>
    o = torch.stack([self.z_normalization(c[None])[0] for c in o])
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/torchio/transforms/transform.py", line 163, in __call__
    transformed = self.apply_transform(subject)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/torchio/transforms/preprocessing/intensity/normalization_transform.py", line 50, in apply_transform
    self.apply_normalization(subject, image_name, mask)
  File "/panfs/jay/groups/4/miran045/reine097/projects/loes-scoring-2/.venv/lib64/python3.11/site-packages/torchio/transforms/preprocessing/intensity/z_normalization.py", line 40, in apply_normalization
    raise RuntimeError(message)
RuntimeError: Standard deviation is 0 for masked values in image "default_image_name" (None)