refactor/fix default_uncollate

[Borda]

What does this PR do?

I found there is a problem if the meta-data included size as a tuple which is an argument for upscaling predictions as images after image segmentation so start playing around and do not claim that this is the right solution... :)

>>> import torch
>>> from pprint import pprint
>>> batch = {"input": torch.zeros([5, 3, 224, 224]), "target": torch.zeros([5, 3, 224, 224]),
...          "metadata": {
...             'size': [torch.tensor([266, 266, 266, 266, 266]), torch.tensor([266, 266, 266, 266, 266])],
...             'height': torch.tensor([266, 266, 266, 266, 266]),
...             'width': torch.tensor([266, 266, 266, 266, 266])
... }}
>>> bbatch = default_uncollate(batch)
>>> len(bbatch)
5
>>> print(bbatch[0].keys())
dict_keys(['input', 'target', 'metadata'])
>>> print(bbatch[0]["input"].size(), bbatch[0]["target"].size())
torch.Size([3, 224, 224]) torch.Size([3, 224, 224])
>>> pprint(bbatch[0]["metadata"])
{'height': tensor(266),
 'size': (tensor(266), tensor(266)),
 'width': tensor(266)}

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[codecov[bot]]

Codecov Report

Merging #1347 (96a8cf0) into master (e7adb6a) will not change coverage. The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master    #1347   +/-   ##
=======================================
  Coverage   92.28%   92.28%           
=======================================
  Files         287      287           
  Lines       13050    13050           
=======================================
  Hits        12043    12043           
  Misses       1007     1007           

Flag	Coverage Δ
pytest	12.12% <33.33%> (ø)
tpu	12.12% <33.33%> (ø)
unittests	92.83% <100.00%> (ø)

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
flash/core/data/batch.py	96.55% <100.00%> (ø)

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[krshrimali]

The recent commits should fix the tests (if not, I'll fix them further), also I improved the error message to print the type of the input type with the ValueError:

>>> default_uncollate({"preds"})

# Error below:

     71 if isinstance(batch, (list, tuple, Tensor)):
     72     return list(batch)
---> 73 raise ValueError(
     74     "The batch of outputs to be uncollated is expected to be a `dict` or list-like "
     75     f"(e.g. `torch.Tensor`, `list`, `tuple`, etc.), but got input of type: {type(batch)}"
     76 )

ValueError: The batch of outputs to be uncollated is expected to be a `dict` or list-like (e.g. `torch.Tensor`, `list`, `tuple`, etc.), but got input of type: <class 'set'>