Add batched mode for faster inference on pre-recorded conversations

[juanmc2005]

Problem

Running the online diarization pipeline on an entire dataset can be difficult and slow because the current implementation simulates an online scenario and processes one chunk at a time.
This is the way to go in a real-time scenario but it would be very useful to have a faster implementation for evaluation, for example to see the performance impact of swapping a component (issue #34 is a good example).

Idea

Pre-calculate segmentation and embeddings for all chunks in a file and only run clustering and output reconstruction online, this would considerably speed up the process. It could be hosted in a new BatchedOnlineSpeakerDiarization class implementing the same interface as OnlineSpeakerDiarization

[juanmc2005]

Changes added as part of PR #46.
Implemented as OnlineSpeakerDiarization.from_file()