Marignal_likelyhood and prior

hi, I am not so clear about the difference bew marignal_likelyhood and prior,in module.
take Latent as an example,when shall I use marignal_likelyhood or prior?

Use marginal_likelihood when your observed data is drawn directly from the GP. If you are using the GP as a prior distribution for latent (i.e. unobserved) variables, then use prior. Here’s an example from PyMC v3 which shows how the prior method can be used to create latent RVs. In that example, the observed data are discrete counts (which clearly cannot be drawn from a standard GP) but we use the GP to place a prior over the log-mean value of the Poisson distributed counts.

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thanks, that means the prior is more general than m_likelyhood?