Generate np chunks for caching

[gitttt-1234]

This PR adds an option to cache samples to disk as .npz files, apart from the in-memory caching available with torch Dataset pipeline in sleap-nn. These .npz files stores dictionaries with preprocessed images and keypoints extracted from the .slp file. In the Dataset.__getitem__() method, we apply augmentation, and generate confidence maps (and part affinity fields for bottom-up model) to ensure randomness. The .npz dir is then deleted at the end of training.

Example:

from sleap_nn.training.model_trainer import ModelTrainer

trainer = ModelTrainer(config, data_pipeline_fw="torch_dataset_np_chunks", np_chunks_path="./")

trainer.train()

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[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 97.35%. Comparing base (fe64019) to head (261689d).

Additional details and impacted files

@@                       Coverage Diff                       @@
##           divya/remove-randomcrop-aug     #125      +/-   ##
===============================================================
- Coverage                        97.51%   97.35%   -0.16%     
===============================================================
  Files                               39       39              
  Lines                             3986     4049      +63     
===============================================================
+ Hits                              3887     3942      +55     
- Misses                              99      107       +8     

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