Update torch requirement from ~=1.13.1 to ~=2.0.1

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[mzweilin]

We should also upgrade to the latest template: ashleve/lightning-hydra-template@v1.4.0...v2.0.2

Notable changes

• pytorch_lightning -> lightning.pytorch
• use lightning.fabric for TPU
• upgrade to hydra 1.3
• upgrade toolkits in pre-commit
• config datamodule -> data
• add a cpu trainer config
• move src.tasks to src
• stop exporting extra log after a task exception.
• add aim as a logger
• split src.utils.utils into several .py files
• update .gitignore for the aim logger

[mzweilin]

Changes in pytorch-lightning ~= 1.6.5 -> lightning ~= 2.0.2.

• import pytorch_lightning as pl -> from lightning import pytorch as pl
• LightningModule: training_epoch_end(self, outputs) -> on_train_epoch_end(self).
• LightningModule: remove training_step_end()
• LightningModule: change arguments configure_gradient_clipping()

[mzweilin]

lightning 2.0.2 depends on torchmetrics<2.0 and >=0.7.0.

However, we want to keep torchmetrics == 0.6.0 because mAP is super slow in later versions.

I hope torchmetrics will change the backend of mAP soon in the upcoming release.

Changes in torchmetrics == 0.6.0 -> torchmetrics == 0.11.4

• Accuracy requires num_classes in arguments.
• torchmetrics.detection.MAP -> torchmetrics.detection.mean_ap.MeanAveragePrecision

[dxoigmn]

The reason we used torchmetrics == 0.6.0 is because MeanAveragePrecision is super slow in newer versions. It looks like they're finally going to revert back to the original implementation that uses the COCOapi: Lightning-AI/torchmetrics#1024.

[dxoigmn]

Should this be closed @mzweilin?