Modify docstring for HMC.
@@ -46,14 +46,16 @@ class HMC(Optimizer):
:param model: gpflow model with `build_objective` method implementation.
:param num_samples: number of samples to generate.
- :param epsilon: HMC parameter - stepsize.
- :param lmin: HMC parameters - lowest integer `a` of uniform `[a, b)` distribution
+ :param epsilon: HMC tuning parameter - stepsize.
+ :param lmin: HMC tuning parameter - lowest integer `a` of uniform `[a, b)` distribution
used for drawing number of leapfrog iterations.
- :param lmax: HMC parameters - largest integer `b` from uniform `[a, b)` distribution
+ :param lmax: HMC tuning parameter - largest integer `b` from uniform `[a, b)` distribution
used for drawing number of leapfrog iterations.
:param thin: an integer which specifies the thinning interval.
:param burn: an integer which specifies how many initial samples to discard.
+ :return: data frame with `num_samples` traces, where columns are full names of
+ trainable parameters except last column, which is `logprobs`.
"""
session = model.enquire_session(session)
