Log the ROC or PRC curve of the best model when using EarlyStopping

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Hi everyone, what would be the best way to log the ROC curve (or any list of metrics really) of the best model when training using EarlyStopping? For now, I just use the test method at the end, passing the validation data loader, but I was wondering if there was a more elegant way to do that

trainer.test(test_dataloaders=dm.val_dataloader(), ckpt_path='best')
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trainer.validate() will be available in hopefully next release: https://github.com/PyTorchLightning/pytorch-lightning/pull/4945

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