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I really wanted to demonstrate the full power of combining PyTorch Lightning with Weights amp;amp; Biases. So this is sort of a Reeseamp;#39;s situation. Itamp;#39;s two great tastes that taste great together. So Iamp;#39;m going to show you how to do a PyTorch Lightning callback that gives you the ability to do fully flexible media logging with Weights amp;amp; Biases. If you just used PyTorch Lightning, then you would be able to log metrics pretty easily. But if you wanted to log things like the input and output of your model, youamp;#39;re going to have a little bit more trouble with just base PyTorch Lightning. This is a problem because DNNs often fail in these very pernicious kind of silent ways. You know, the loss is going down, but itamp;#39;s actually getting every single example from one class wrong. Maybe you have a bug in your code and the way youamp;#39;re calculating your accuracy is incorrect. These can be very difficult bugs to track down unless you actually look
