Fix datamodules ImportError and add tests

[akihironitta]

What does this PR do?

Fixes #379.

Bacause raising ModuleNotFoundError in pl_bolts/datamodules/sklearn_datamodule.py makes from pl_bolts.datamodules import SklearnDataModule raise ImportError as reported in the issue, this PR fixes the problem by replacing it with warn_missing_pkg.

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[codecov]

Codecov Report

Merging #380 (37cd8d3) into master (70833f0) will decrease coverage by 0.93%.
The diff coverage is 93.75%.

@@            Coverage Diff             @@
##           master     #380      +/-   ##
==========================================
- Coverage   82.03%   81.10%   -0.94%     
==========================================
  Files         100      100              
  Lines        5639     5725      +86     
==========================================
+ Hits         4626     4643      +17     
- Misses       1013     1082      +69     

Flag	Coverage Δ
cpu	25.22% <81.25%> (+0.67%)	⬆️
pytest	25.22% <81.25%> (+0.67%)	⬆️
unittests	80.47% <81.25%> (-0.82%)	⬇️

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

Impacted Files	Coverage Δ
pl_bolts/datasets/kitti_dataset.py	35.29% <83.33%> (+4.85%)	⬆️
pl_bolts/datamodules/experience_source.py	95.86% <100.00%> (+0.14%)	⬆️
pl_bolts/datasets/imagenet_dataset.py	19.41% <100.00%> (+0.95%)	⬆️
..._bolts/models/self_supervised/simclr/transforms.py	80.88% <0.00%> (-19.12%)	⬇️
pl_bolts/datamodules/__init__.py	77.35% <0.00%> (-11.33%)	⬇️
...lts/models/self_supervised/simclr/simclr_module.py	71.49% <0.00%> (-11.32%)	⬇️
pl_bolts/losses/self_supervised_learning.py	71.33% <0.00%> (-6.37%)	⬇️
pl_bolts/datasets/base_dataset.py	95.45% <0.00%> (-4.55%)	⬇️
...l_bolts/models/self_supervised/byol/byol_module.py	83.90% <0.00%> (-1.04%)	⬇️
pl_bolts/models/self_supervised/resnets.py	92.04% <0.00%> (-0.74%)	⬇️
... and 2 more

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[Borda]

shall we add some tests that we do not break these imports in the future?

[akihironitta]

@Borda Yes, let's.

[Borda]

@Borda Yes, let's.

may we add it as part of this PR?
probably for this test, we would need to mock some packages aka they are not installed...
there shall be a way wrap such test and inside call these testing imports

[akihironitta]

@Borda Just added the import tests when optional packages are unavailable. How does it look?
https://github.com/PyTorchLightning/pytorch-lightning-bolts/blob/ff8cd589328a32557c9f1f68356f94a296f07ab4/tests/datamodules/test_imports.py

[akihironitta]

We still have similar problems in importing datamodules when dependencies are not met... e.g. from pl_bolts.datamodules import DiscountedExperienceSource still fails without gym installed, so let me extend this PR to fix the problem for all datamodules.

[Borda]

@Borda Just added the import tests when optional packages are unavailable. How does it look?
https://github.com/PyTorchLightning/pytorch-lightning-bolts/blob/ff8cd589328a32557c9f1f68356f94a296f07ab4/tests/datamodules/test_imports.py

I may be thinking about some automatic way lets say parse the __init__ but that would require more work of finding dependency in the follow-up file... co this is fine :]
cc: @oke-aditya

[oke-aditya]

I too will give a thought. Solution doesn't seem very straightforward to me 😅

[akihironitta]

I'm aware that there is inconsistency in how we check if optional packages are available (i.e. try: ... except ModuleNotFoundError: ... and importlib.util.find_spec("some_package")). I'm trying to refactor datamodules in #338. Also, in #346, I'm suggesting to implement a context manager class which will reduce repetitive import checks all over the codebase, so for this PR, let's only make datamodules importing work.

[akihironitta]

@Borda mind having a look again?