  The Chambolle--Pock method is a versatile three-parameter algorithm designed
to solve a broad class of composite convex optimization problems, which
encompass two proper, lower semicontinuous, and convex functions, along with a
linear operator $L$. The functions are accessed via their proximal operators,
while the linear operator is evaluated in a forward manner. Among the three
algorithm parameters $\tau $, $\sigma $, and $\theta$; $\tau,\sigma >0$ serve
as step sizes for the proximal operators, and $\theta$ is an extrapolation step
parameter. Previous convergence results have been based on the assumption that
$\theta=1$. We demonstrate that weak convergence is achievable whenever
$\theta> 1/2$ and $\tau \sigma \|L\|^2<4/(1+2\theta)$. Moreover, we establish
tightness of the step size bound by providing an example that is non-convergent
whenever the second bound is violated.
