If you don’t want to estimate scalar values, you can just plug them into your model equations as numbers, or wrap them in pm.Deterministic. For example, if you write the following regression:
with pm.Model():
x = pm.MutableData('x', ...)
z = pm.MutableData('z', ...)
y = pm.MutableData('z', ...)
a = pm.Normal('a')
b = pm.Normal('b')
mu = pm.Determinsitic('mu', a + b * x + 4 * z)
sigma = pm.Exponential('sigma', 1)
y_hat = pm.Normal('y_hat', mu=mu, sigma=sigma, observed=y)
The coefficient “4” associated with covariate z will not be “learned”.
Is your situation more complex than that?