The paper is about training implicit models of infinite layers. Instead of employing expensive implicit differentiation and solving the gradient for backward propagation, the paper proposes a novel approach, named Phantom Gradient, that can forgo the heavy computations of the exact gradient, as well as providing an update direction empirically preferable to the implicit model training.