through multiple different augmentation strategies so you can see here in policy one there they're making a transformation rotation to the input data the other ones are mostly changing the color of the samples and and so the idea is the the model will automatically select the policy that is adding the most novel signal to to the yeah to the training so for example if and they find that in different in different data sets different policies are optimal so in in one data set you might need to modify the color of your images a lot to get