TPR and FPR of a model are not independent given the decision threshold, which is what you’re varying to produce the ROC curve. As DigThatData said, you get a step function where each step is the point at which a sample crosses the threshold. If you get multiple threshold values where your FPR is the same but TPR changes, leading to a deep step in the curve, it means you haven’t got enough negative samples near to measure FPR precisely in that curve region.