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- Help post，shape problem - Pyro Discussion Forum
with pyro plate("data", x size(0)): pyro sample("obs", dist Normal(mu, sigma), obs=y squeeze(-1),infer={"scale": annealing_factor}) #obs，真实数据+噪声
- Pyro Discussion Forum
Forum For Pyro Developers
- Batch processing numpyro models using Ray - forum. pyro. ai
Hello again, Related post: Batch processing Pyro models so cc: @fonnesbeck as I think he’ll be interested in batch processing Bayesian models anyway I want to run lots of numpyro models in parallel I created a new post because: this post uses numpyro instead of pyro I’m doing sampling instead of SVI I’m using Ray instead of Dask that post was 2021 I’m running a simple Neal’s funnel
- numpyro - Pyro Discussion Forum
Forum For Pyro Developers
- Model and guide shapes disagree at site - Pyro Discussion Forum
Model and guide shapes disagree at site ‘z_2’: torch Size ( [2, 2]) vs torch Size ( [2]) Anyone has the clue, why the shapes disagree at some point? Here is the z_t sample site in the model: z_loc here is a torch tensor wi hellip;
- Implementation normalizing flow in matrix normal distribution
Hi, I’m working on a model where the likelihood follows a matrix normal distribution, X ~ MN_{n,p} (M, U, V) I’m using conjugate priors: M ~ MN U ~ Inverse Wishart V ~ Inverse Wishart As a result, I believe the posterior distribution should also follow a matrix normal distribution Is there a way to implement the matrix normal distribution in Pyro? If I replace the conjugate priors with
- Reducing MCMC memory usage - numpyro - Pyro Discussion Forum
I am running NUTS MCMC (on multiple CPU cores) for a quite large dataset (400k samples) for 4 chains x 2000 steps mcmc run actually ran until the end, but then died with an out-of-memory exception; I assume upon trying to gather all results (There might be some unnecessary memory duplication going on in this step?) Are there any “quick fixes” to reduce the memory footprint of MCMC? For
- Use of LogNormal in Numpyro - Pyro Discussion Forum
Hi everyone, I am very new to Numpyro and hierarchical modeling Recently I have been trying to build a hierarchical model where I have a hyper-prior (theta_group) which should be centered around 1 and strictly positive There is another prior (theta_part) which should be centered around theta_group I am trying to use LogNormal as priors for both: theta_group = numpyro sample("theta_group
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