Optimize Error Handling and Regex Caching in Tensor Loading

[Madhav-MKNC]

This PR introduces two key enhancements to the tensor loading process: (Fixes #220)

• Improved error handling within ThreadPoolExecutor to provide detailed logs for failures during parallel tensor loading.
• Implementation of caching for regex operations in get_load_path_str to reduce computational overhead and improve loading efficiency.

These changes aim to enhance the robustness and performance of tensor loading, particularly in distributed computing environments.

[Aareon]

Hey! I'm happy to see a limit set for the memory usage in LRU Cache. Would it be possible for you to roll a test for this change? I think a pytest test would suffice.

[Aareon]

Perhaps path_tuple_to_string can also utilize the LRU cache, as well. Just a thought.

[Aareon]

Is this docstring supposed to be here, or inside the path_tuple_to_string method?

[Aareon]

After delving a bit. I now think 32MB in LRU cache may be too much overkill. I don't think more than 250kb at most should be necessary.

[RaphaelFakhri]

"delving" hahahaha (for reference: https://x.com/JeremyNguyenPhD/status/1774021645709295840)

[Aareon]

"delving" hahahaha (for reference: https://x.com/JeremyNguyenPhD/status/1774021645709295840)

Hadn't seen this, and the stat doesn't really correspond with anything related to ChatGPT. I most certainly didn't need to use ChatGPT to come to that conclusion.

I recommend trying both ways and running benchmarks to see which provides the best performance improvement.