AL-[1616] Tensorflow API Design

[levongh]

🚀 🚀 Pull Request

Checklist:

• My code follows the style guidelines of this project and the Contributing document
• I have commented my code, particularly in hard-to-understand areas
• I have kept the coverage-rate up
• I have performed a self-review of my own code and resolved any problems
• I have checked to ensure there aren't any other open Pull Requests for the same change
• I have described and made corresponding changes to the relevant documentation
• New and existing unit tests pass locally with my changes

Changes

[codecov]

Codecov Report

Merging #1530 (93e21fe) into main (b7b83b8) will decrease coverage by 0.09%.
The diff coverage is 75.21%.

@@            Coverage Diff             @@
##             main    #1530      +/-   ##
==========================================
- Coverage   92.23%   92.13%   -0.10%     
==========================================
  Files         191      193       +2     
  Lines       16902    17029     +127     
==========================================
+ Hits        15589    15690     +101     
- Misses       1313     1339      +26     

Flag	Coverage Δ
unittests	92.13% <75.21%> (-0.10%)	⬇️

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

Impacted Files	Coverage Δ
hub/integrations/tf/hubtensorflowdataset.py	74.10% <74.10%> (ø)
hub/integrations/__init__.py	100.00% <100.00%> (ø)
hub/integrations/tf/__init__.py	100.00% <100.00%> (ø)
hub/integrations/tf/datasettotensorflow.py	59.37% <100.00%> (ø)
hub/core/ipc.py	0.00% <0.00%> (ø)
hub/integrations/pytorch/dataset.py	91.37% <0.00%> (+0.03%)	⬆️
hub/core/query/filter.py	87.79% <0.00%> (+0.04%)	⬆️
hub/core/lock.py	89.47% <0.00%> (+0.06%)	⬆️
hub/core/compression.py	87.75% <0.00%> (+0.11%)	⬆️
hub/__init__.py	93.87% <0.00%> (+0.12%)	⬆️
... and 4 more

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[AbhinavTuli]

why is super used in some methods and tf.data.Dataset? let's use super everywhere?