nan grads when running find_MAP() on analytic, ddm

[AlexanderFengler]

Something as simple as:

# Test 1: Basic DDM model
cav_data = hssm.load_data("cavanagh_theta")

mCon=hssm.HSSM(
    data=cav_data,
    model="ddm",
)

mCon.find_MAP()

Produces nan grads (as per report from the optimizer). This may be the key to investigating what is going on with the gradients of that model and therefore corresponding sampler pathologies.