Shifting a lognormal distribution

If I have a normal distribution which has vanishingly small coefficients, for example mu=e-10 and sd=e-20, using pm.Normal directly results in “bad initial energy” or “derivative of RV is zero” errors. However using the “trick” of shifting and scaling the normal distribution pm.Normal(“example”, mu=0, sd=1) by the above small values gives the desired “small” distribution.

My question is; is there a way to do such a shift and scale for a lognormal distribution instead of normal? I am sure there is a mathematical relation to obtain this, but I have not been able to find that yet.

In scipy lognormal is also defined as a location-scale distribution, so it should be possible: