Pyro
Pyro is a universal probabilistic programming language (PPL) written in Python and supported by PyTorch on the backend. Pyro enables flexible and expressive deep probabilistic modeling, unifying …
Getting Started With Pyro: Tutorials, How-to Guides and Examples
Follow the instructions on the front page to install Pyro and look carefully through the series Practical Pyro and PyTorch, especially the first Bayesian regression tutorial.
Pyro Documentation — Pyro documentation
Pyro Distributions Transforms TransformModules Transform Factories Constraints Parameters ParamStore Neural Networks Pyro Modules AutoRegressiveNN DenseNN …
Introduction to Pyro — Pyro Tutorials 1.9.1 documentation
Just like the model, the guide is encoded as a Python program guide() that contains pyro.sample and pyro.param statements. It does not contain observed data, since the guide needs to be a properly …
Bayesian Regression - Introduction (Part 1) - Pyro
Here, we show how we can serve a Pyro model as a torch.jit.ModuleScript, which can be run separately as a C++ program without a Python runtime. To do so, we will rewrite our own simple version of the …
SVI Part I: An Introduction to Stochastic Variational Inference ... - Pyro
Just like the model, the guide is encoded as a stochastic function guide() that contains pyro.sample and pyro.param statements. It does not contain observed data, since the guide needs to be a properly …
Distributions — Pyro documentation
PyTorch Distributions ¶ Most distributions in Pyro are thin wrappers around PyTorch distributions. For details on the PyTorch distribution interface, see torch.distributions.distribution.Distribution. For …
Example: Hidden Markov Models — Pyro Tutorials 1.9.1 documentation
Here we use the# pyro.util.ignore_jit_warnings context manager to silence warnings about# conversion to integer, since we know all three numbers will be the same# across all invocations to the …
Getting Started with NumPyro — NumPyro documentation
Pyro Primitives: NumPyro programs can contain regular Python and NumPy code, in addition to Pyro primitives like sample and param. The model code should look very similar to Pyro except for some …
MCMC — Pyro documentation
Given a Python callable with Pyro primitives, generates the following model-specific properties needed for inference using HMC/NUTS kernels: initial parameters to be sampled using a HMC kernel,