Non-scalar eta in HSGP

[wd60622]

Similar to #1280, I would like to be able to use non-scalar (including hierarchical) scales in HSGP class.

This might be easier to implement than #1280 depending if pymc.gp.HSGP handles the dims via prior_linearized the ls.

Implementation Location :

pymc-marketing/pymc_marketing/mmm/hsgp.py

Lines 720 to 730 in 181b348

	cov_func = eta**2 * cov_funcs[self.cov_func.lower()](input_dim=1, ls=ls)
	gp = pm.gp.HSGP(
	m=[self.m],
	L=[self.L],
	cov_func=cov_func,
	drop_first=self.drop_first,
	)
	phi, sqrt_psd = gp.prior_linearized(
	self.X[:, None] - self.X_mid,
	)