chore(l2g): log annotated gold standards in w&b

[ireneisdoomed]

✨ Context

This is the entry API to train the L2G model:

LocusToGeneTrainer.train(
                    gold_standard_data=data,
                    l2g_model=l2g_model,
                    model_path=model_path,
                    evaluate=True,
                    wandb_run_name=wandb_run_name,
                    **hyperparameters,
                )

Everything except the input gold_standard_data are just set parameters.
If we wanted to speed up experimenting as I suggest in opentargets/issues#3253, we would just need to store gold_standard_data.

We can use W&B for that. We currently upload to W&B the train set of the annotated gold standards. I want to log the full matrix before splitting into train, test. Since we use a seed to split the data, this still makes sure we can reproduce the pipeline.

I like this idea because it binds the input data to the output model.

🛠 What does this PR implement

Changes in LocusToGeneModel.evaluate to accomplish the suggestion above.

🙈 Missing

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[DSuveges]

It look OK. No obvious issues. Have you tried to run it?

[ireneisdoomed]

It's running right now. It shouldn't have issues because we were logging a very similar table (only the train set). I just changed the input to the logging function and refactored the train function