Add PyTorch Finetuning Capability, Examples

[mwalmsley]

Key change is adding pytorch.training.finetune() method. Works on either classification (e.g. 0, 1) data or count (e.g. 12 said yes, 4 said no) data.

Includes three working examples:

• Binary classification, with tiny rings subset
• Counts for single question, with full internal rings data
• Counts for all questions, with GZ Cosmic Dawn schema

Also updates various imports for the galaxy-datasets refactor, fixes prediction method to work on unlabelled data, minor QoL improvements.

Finally, changes PyTorch dense layer initialisation to custom high-uncertainty initialisation - see efficientnet_custom.py

cc @camallen

[mwalmsley]

PyTorch benchmarks train successfully - punching merge