[AL-1443] Tiling + Slicing + Updating

[farizrahman4u]

🚀 🚀 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

https://activeloop.atlassian.net/browse/AL-1443
Lazy download of tiled sample slices + updating

[CLAassistant]

All committers have signed the CLA.

[codecov]

Codecov Report

Merging #1374 (38c2207) into main (f6b62ca) will increase coverage by 0.60%.
The diff coverage is 98.75%.

@@            Coverage Diff             @@
##             main    #1374      +/-   ##
==========================================
+ Coverage   92.40%   93.01%   +0.60%     
==========================================
  Files         175      174       -1     
  Lines       13043    13369     +326     
==========================================
+ Hits        12053    12435     +382     
+ Misses        990      934      -56     

Flag	Coverage Δ
unittests	93.01% <98.75%> (+0.60%)	⬆️

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

Impacted Files	Coverage Δ
hub/core/meta/encode/base_encoder.py	98.34% <ø> (+0.01%)	⬆️
hub/core/tiling/deserialize.py	93.65% <92.68%> (-2.78%)	⬇️
hub/core/chunk_engine.py	97.96% <99.27%> (+0.44%)	⬆️
hub/api/tests/test_api.py	100.00% <100.00%> (+2.54%)	⬆️
hub/api/tests/test_api_tiling.py	100.00% <100.00%> (ø)
hub/core/chunk/base_chunk.py	98.12% <100.00%> (+0.11%)	⬆️
hub/core/chunk/chunk_compressed_chunk.py	98.78% <100.00%> (+0.03%)	⬆️
hub/core/chunk/sample_compressed_chunk.py	100.00% <100.00%> (+1.81%)	⬆️
hub/core/chunk/uncompressed_chunk.py	100.00% <100.00%> (ø)
hub/core/dataset/dataset.py	94.11% <100.00%> (+0.07%)	⬆️
... and 66 more

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[aliubimov]

Please also add missing coverage

[AbhinavTuli]

why aren't we using this function anymore?

[farizrahman4u]

The function cannot handle the indexing logic for tiled samples, as the whole sample might not be available. Behavior stays same for non-tile samples, the logic is moved to numpy().