feeding the train data set as shown on the left into an into the neural network comparing this to our test input shown on the bottom two and outputting these similarities and then training it such that the predictions that it gets out which corresponds to weighted nearest neighbors are correct with respect to each of the tasks in our meta training set cool so this is basically embedding nearest neighbors into a neural network the the metric that we're using can be correspond to a convolutional encoder or some other architecture to get the