[QDP] Simplify Python API with unified encode() method

[guan404ming]

Purpose of PR

Why

• API had 6 different encoding methods (encode, encode_batch, encode_tensor, encode_from_parquet, encode_from_arrow_ipc, encode_from_numpy)
• Users needed to know which method to call for each input type

How

• Unified encode() method - auto-detects lists, NumPy arrays, PyTorch tensors, and file paths
• Default encoding method - encoding_method="amplitude" is now the default

Changes Made

• Bug fix
• New feature
• Refactoring
• Documentation
• Test
• CI/CD pipeline
• Other

Breaking Changes

• Yes
• No

Checklist

• Added or updated unit tests for all changes
• Added or updated documentation for all changes
• Successfully built and ran all unit tests or manual tests locally
• PR title follows "MAHOUT-XXX: Brief Description" format (if related to an issue)
• Code follows ASF guidelines

[guan404ming]

cc @ryankert01 @400Ping

[rich7420]

@guan404ming thanks for the patch!
I think we need to change encode() functions in all benchmark files as well. (the rest qdp/qdp-python/benchmark/benchmark_numpy_io.py and qdp/qdp-python/benchmark/benchmark_latency.py)
And it would be better to check the tensor's shape. like, if it's 1D, use the single-sample encode path and then if it's 2D, use the batch encoding path and for anything else, throw a clear error explaining what shapes are supported.
On the other hand , maybe we could support for pathlib.Path objects by using os.fspath() to convert them to strings before processing.

[guan404ming]

I've updated with three additions. Please take another look, thanks!

1. Updated benchmark files to use unified encode() API:
2. Added tensor shape validation with clear error messages (lib.rs):
3. Added pathlib.Path support

[rich7420]

Thanks for the update!
I think some comments been removed unnecessarily.
maybe shape validation in pytorch hasn't done yet. but it could be follow-up.

[ryankert01]

Thanks!
Overall lg, I agree with @rich7420 that it definitely needs refactor and can be a follow up!

[400Ping]

Overall LGTM

[guan404ming]

Thanks, I'll send a follow up for it.