Tag htype

[FayazRahman]

🚀 🚀 Pull Request

Impact

• Bug fix (non-breaking change which fixes expected existing functionality)
• Enhancement/New feature (adds functionality without impacting existing logic)
• Breaking change (fix or feature that would cause existing functionality to change)

Description

• We need a special htype for tagging samples (small strings) that are used for search and not for training.
• We don't want to use class_label because there's no need to encode the tags as numbers and the htype's name is not intuitive.
• We don't want to use text or json because these htypes need to support large amounts of information in comparison to tags, and visualizer needs to display both of these differently.

Things to be aware of

Things to worry about

Additional Context

[codecov]

Codecov Report

Attention: 7 lines in your changes are missing coverage. Please review.

Comparison is base (7b84efb) 84.37% compared to head (6fa0be3) 83.81%.

Files	Patch %	Lines
deeplake/integrations/pytorch/common.py	40.00%	6 Missing ⚠️
deeplake/util/htype.py	50.00%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #2676      +/-   ##
==========================================
- Coverage   84.37%   83.81%   -0.56%     
==========================================
  Files         231      231              
  Lines       25902    25914      +12     
==========================================
- Hits        21854    21720     -134     
- Misses       4048     4194     +146     

Flag	Coverage Δ
unittests	83.81% <75.00%> (-0.56%)	⬇️

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[adolkhan]

I do get all of the changes, but I don't get bigger picture, why do we need tag htype? From what I am seeing it is the same text htype but with a different name. If there is a specific reason on why we need it, maybe then it would be a better idea to create a base class for the htypes that are string?

[sonarcloud]

Kudos, SonarCloud Quality Gate passed!   

0 Bugs
0 Vulnerabilities
0 Security Hotspots
1 Code Smell

77.4% Coverage
0.0% Duplication