We tried the tutorial on GP https://pyro.ai/examples/gp.html
(thank you for the awesome tutorials!)
and we have a few questions:
1. We could not get these lines to work?
gpr.kernel.lengthscale = pyro.nn.PyroSample(dist.LogNormal(0.0, 1.))
gpr.kernel.variance = pyro.nn.PyroSample(dist.LogNormal(0.0, 1.))
It says: AttributeError: module ‘pyro.nn’ has no attribute ‘PyroSample’.
Could you please give an example on how to fix this?
2. We would like to compute log_p, log_q. It looks like we could do this using poutine.
How does poutine work with GPRegression or SparseGPRegression in the lines below?
What shape of data should we pass in get_trace(data)? is it a tuple data=(X,y)?
model_trace = pyro.poutine.trace(gpr.model).get_trace(data)
guide_trace = pyro.poutine.trace(gpr.guide).get_trace(data)
3. If we pass data=None in the lines above, how does it compute log_prob_sum()?
(ie. how does it do the random sampling?)
log_p = model_trace.log_prob_sum()
log_q = guide_trace.log_prob_sum()