Bug in caching: Boolean value of tensor comparison is ambiguous

I think this is an edge case. when we do if sample.obj not in unique_objects in fetch_unique_objects of data loader classes, it may return a tensor of Trues and Falses if the individual elements in the tensor (sample.obj) are equal in certain indexes and not equal in others. When we want to use that returned tensor in a conditional expression, it tries to reduce it to a single boolean value, but the combination of multiple Trues and Falses is ambiguous, so it throws a runtime error:

...
  File "C:\Users\Yusuf\coding\quaterion\quaterion\dataset\cache_data_loader.py", line 68, in cache_collate_fn
    unique_objects = self.unique_objects_extractor(batch)
  File "C:\Users\Yusuf\coding\quaterion\quaterion\dataset\similarity_data_loader.py", line 42, in fetch_unique_objects
    if sample.obj_b not in unique_objects:
RuntimeError: Boolean value of Tensor with more than one value is ambiguous
Predicting:   0%|          | 0/387 [00:00<?, ?it/s]

Possible solution

1. Create another container for unique hashes in addition to unique_objects, e.g.: unique_hashes.
2. If hash(obj) not in the new container, add the hash there and add the object to unique_objects.
3. Return unique_objects as usual. We can even return list of hashes to further use them later, maybe.

[joein]

We discussed and here are to possible solutions we figured out:

• torch.Tensors, np.ndarray and everything built upon them doomed to be broken (e.g. pandas objects), the first ones will raise RuntimeError, the second - ValueError. We can suppress this exceptions in method like obj_in_list and wait for feedback if they are not sufficient.
• replace fetch_unique_objects with emit_objects like discussed earlier in this thread

@generall

[monatis]

Fixed in #34