From db49b6b22fa775ccfa9e5645d1d0fc42f0e5ba1f Mon Sep 17 00:00:00 2001 From: junpenglao Date: Wed, 21 Dec 2022 23:32:00 +0700 Subject: [PATCH] fix example --- examples/howto_other_frameworks.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/howto_other_frameworks.md b/examples/howto_other_frameworks.md index 69b171ff8..5fef941f4 100644 --- a/examples/howto_other_frameworks.md +++ b/examples/howto_other_frameworks.md @@ -52,7 +52,7 @@ print(sampling_fn()) We do not care about the posterior distribution of the indicator variable `I_rv` so we marginalize it out, and subsequently build the logdensity's graph: ```{code-cell} python -from aeppl import joint_logdensity +from aeppl import joint_logprob y_vv = Y_rv.clone() i_vv = I_rv.clone() @@ -60,7 +60,7 @@ i_vv = I_rv.clone() logdensity = [] for i in range(4): i_vv = at.as_tensor(i, dtype="int64") - component_logdensity, _ = joint_logdensity(realized={Y_rv: y_vv, I_rv: i_vv}) + component_logdensity, _ = joint_logprob(realized={Y_rv: y_vv, I_rv: i_vv}) logdensity.append(component_logdensity) logdensity = at.stack(logdensity, axis=0)