Explain this code - Pytorch CNN

These two lines of code are from the testing of a CNN model. I know of alternative ways of getting the predictions and correct predictions
but I have struggled to make sense of the two lines below:

  pred = output.data.max(1, keepdim=True)[1]
  correct += pred.eq(target.data.view_as(pred)).sum()

So at a high level - what your code is doing is first getting the predicted tensor pred, and then element-wise comparing them to the values in tensor target, setting them to True if the elements match and False if not. And then when you take the sum(), you’re simply summing over the True values, and that gives you the number of correct predictions.