add multiprocessing support for Cross Encoder

[omkar-334]

Resolves #3350

Implemented 4 functions to support multiprocessing, exactly as done in SentenceTransformer.py

1. start_multi_process_pool - same as before
2. stop_multi_process_pool - same as before
3. _predict_multi_process - similar to _encode_multi_process
4. _predict_multi_process_worker - similar to _encode_multi_process_worker

So far, multiprocessing support has been added to both predict and rank methods of CrossEncoder.py.

I've included code for raising Error if any of the worker processes result in an error. Can remove this after testing.
I've tested this on macOS, but need to test on Colab GPU and confirm.

@tomaarsen some functions like _encode_multi_process_worker and _encode_multi_process do not have docstrings and params. Should I add them in this PR itself?

[tomaarsen]

Well done! This is looking great in my early tests, with some speedups for e.g. multi-processing on CPUs. I'll have a deeper look at the code itself later, but I'd like to include this in the next release 🤗

• Tom Aarsen

[omkar-334]

hey, thank you! I shall include my test results here shortly.
Other than that, are there any issues or features at the top of your head that I can work upon? I've scoured through the open issues and most look resolved..
thanks!