on, TarFlow's sampling process is extremely slow. In this paper, we
demonstrate that through a series of optimization strategies, TarFlow sampling
can be greatly accelerated by using the Gauss-Seidel-Jacobi (abbreviated as
GS-Jacobi) iteration method. Specifically, we find that blocks in the TarFlow
model have varying importance: a small number of blocks play a major role in
image generation tasks, while other blocks contribute relatively little; some
blocks are sensitive to initial values and prone to nume