just worked at an instance level where the the context is just one version of your image target is another version of the same image and negatives are just any other images so in this case it could be like hey you just take a picture for dog you perform one data augmentation to it which is just apply a grayscale perform another data augmentation to it which is you flip it and you take a particular random crop so and any other image would be a negative for this particular anchor positive there so what does this actually learn