AA.composed.ImgOptical requires a dataset to sample from for AA.image_domain.optical.CroppedTemplateOverlap. This indexes the dataset to pull a random galaxy. Prefetched Tensorflow datasets cannot be indexed so requesting a random image fails.
I would suggest having the dataset an optional requirement in AA.composed.ImgOptical and either skipping the call to AA.image_domain.optical.CroppedTemplateOverlap or calling it with a template if dataset == None
<ipython-input-7-cf2b44823a21> in <module>
30 train_iter = iter(train)
31
---> 32 img = next(train_iter)['image']
33 print(img.shape)
~/.local/lib/python3.6/site-packages/tensorflow/python/data/ops/iterator_ops.py in __next__(self)
759 def __next__(self):
760 try:
--> 761 return self._next_internal()
762 except errors.OutOfRangeError:
763 raise StopIteration
~/.local/lib/python3.6/site-packages/tensorflow/python/data/ops/iterator_ops.py in _next_internal(self)
745 self._iterator_resource,
746 output_types=self._flat_output_types,
--> 747 output_shapes=self._flat_output_shapes)
748
749 try:
~/.local/lib/python3.6/site-packages/tensorflow/python/ops/gen_dataset_ops.py in iterator_get_next(iterator, output_types, output_shapes, name)
2726 return _result
2727 except _core._NotOkStatusException as e:
-> 2728 _ops.raise_from_not_ok_status(e, name)
2729 except _core._FallbackException:
2730 pass
~/.local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in raise_from_not_ok_status(e, name)
6939 message = e.message + (" name: " + name if name is not None else "")
6940 # pylint: disable=protected-access
-> 6941 six.raise_from(core._status_to_exception(e.code, message), None)
6942 # pylint: enable=protected-access
6943
~/.local/lib/python3.6/site-packages/six.py in raise_from(value, from_value)
InvalidArgumentError: TypeError: 'PrefetchDataset' object does not support indexing
Traceback (most recent call last):
File "/home/pearsonw/.local/lib/python3.6/site-packages/tensorflow/python/ops/script_ops.py", line 249, in __call__
ret = func(*args)
File "/home/pearsonw/.local/lib/python3.6/site-packages/tensorflow/python/autograph/impl/api.py", line 645, in wrapper
return func(*args, **kwargs)
File "<ipython-input-7-cf2b44823a21>", line 13, in aug_fn
aug_data = transform(**data)
File "/home/pearsonw/.local/lib/python3.6/site-packages/albumentations/core/composition.py", line 205, in __call__
data = t(force_apply=force_apply, **data)
File "/home/pearsonw/.local/lib/python3.6/site-packages/albumentations/core/transforms_interface.py", line 95, in __call__
return self.apply_with_params(params, **kwargs)
File "/home/pearsonw/.local/lib/python3.6/site-packages/albumentations/core/transforms_interface.py", line 110, in apply_with_params
res[key] = target_function(arg, **dict(params, **target_dependencies))
File "/home/pearsonw/.local/lib/python3.6/site-packages/albumentations/augmentations/transforms.py", line 2219, in apply
return fn(img, **params)
File "/home/pearsonw/.local/lib/python3.6/site-packages/astroaugmentations/composed.py", line 183, in __call__
return self.augmentation(image=image)['image']
File "/home/pearsonw/.local/lib/python3.6/site-packages/albumentations/core/composition.py", line 205, in __call__
data = t(force_apply=force_apply, **data)
File "/home/pearsonw/.local/lib/python3.6/site-packages/albumentations/core/transforms_interface.py", line 95, in __call__
return self.apply_with_params(params, **kwargs)
File "/home/pearsonw/.local/lib/python3.6/site-packages/albumentations/core/transforms_interface.py", line 110, in apply_with_params
res[key] = target_function(arg, **dict(params, **target_dependencies))
File "/home/pearsonw/.local/lib/python3.6/site-packages/albumentations/augmentations/transforms.py", line 2219, in apply
return fn(img, **params)
File "/home/pearsonw/.local/lib/python3.6/site-packages/astroaugmentations/image_domain/optical.py", line 310, in __call__
datasample, _ = self.dataset[self.rng.integers(0, len(self.dataset))]
TypeError: 'PrefetchDataset' object does not support indexing
[[{{node augment}}]] [Op:IteratorGetNext]
AA.composed.ImgOptical requires a dataset to sample from for AA.image_domain.optical.CroppedTemplateOverlap. This indexes the dataset to pull a random galaxy. Prefetched Tensorflow datasets cannot be indexed so requesting a random image fails.
I would suggest having the dataset an optional requirement in AA.composed.ImgOptical and either skipping the call to AA.image_domain.optical.CroppedTemplateOverlap or calling it with a template if
dataset == NoneFull traceback:
(I did promise you I would break it)