Save training metadata with the fault tolerance checkpoint

🚀 Feature

See title

Motivation

Since we will only guarantee fault-tolerance restart for the same number of GPUs and workers (among others), we might want to save metadata about those for archival and error checking.

Pitch

Add extra fields to the checkpoint generated in _on_exception

https://github.com/PyTorchLightning/pytorch-lightning/blob/9d62f248476c6358d8707188f7b20fafa79f8a4f/pytorch_lightning/trainer/trainer.py#L1376-L1381

Additional context

This kind of training "metadata" should get saved with the checkpoint. For example, we will also want to know this for fault-tolerance to fail if the trainer configuration has changed between runs and the user is trying to restore mid-batch.

Originally posted by @carmocca in https://github.com/PyTorchLightning/pytorch-lightning/pull/8515#r677317201

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