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name: contrib-and-domain-workflows description: "Navigate Pyro contrib modules, domain examples, optional integrations, and safe skip policies." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Contrib And Domain Workflows

Use this sub-skill when a Pyro task is about pyro.contrib, domain-focused examples/tutorial patterns, pyro.generic or MiniPyro backends, or optional integrations such as Funsor, Horovod, Lightning, Graphviz rendering, torchvision, pandas, scanpy, scikit-learn, or zuko.

This guidance targets the pyro-ppl 1.9.1 package family imported as pyro. It is self-contained: do not require an external repository checkout, examples, tutorial notebooks, or tests at runtime.

Route First

• To choose among contributed modules, understand maturity/stability, identify best-fit tasks, and hand off to core Pyro sub-skills, read references/contrib-module-map.md.
• For domain workflow patterns in forecasting, Gaussian processes, epidemiology, tracking, HMM/RSA/capture-recapture, scANVI, VAEs, CEVAE, AIR, DMM, MuE, and MiniPyro/generic backends, read references/domain-workflows.md.
• For optional extras, install/skip policy, Funsor, Horovod, Lightning, Graphviz rendering, zuko, CUDA flags, and data/plotting dependencies, read references/optional-integrations.md.
• For failures involving optional imports, downloads, plotting, GPU flags, long training, contributed-module stability, or domain data shape issues, read references/troubleshooting.md.

No local script is bundled for this sub-skill. Optional-extra diagnostics are owned by the root Pyro skill's environment check rather than by a contrib-specific script.

Best-Fit Tasks

Use this sub-skill for requests like:

• "Should I use pyro.contrib.forecast, pyro.contrib.timeseries, a core SVI model, or an HMM distribution for this time series?"
• "What does pyro.contrib.gp provide, and what dependencies do the GP examples need?"
• "Can this environment run pyro.contrib.funsor, Horovod, Lightning, Graphviz rendering, scANVI, or zuko flows?"
• "Adapt a domain example pattern safely without downloading data or running a long tutorial."
• "Use MiniPyro or pyro.generic for backend-agnostic didactic code."
• "Decide whether to skip, ask for data, ask for GPU, or ask to install extras."

Mandatory Safety Gates

1. Treat all pyro.contrib APIs as less stable than core Pyro. The package states that contributed code is in various stages of development and does not guarantee backwards compatibility.
2. Do not claim optional extras are available unless the active user environment proves them. Funsor, Graphviz, Horovod, Lightning, torchvision, pandas, scanpy, and similar extras should be treated as optional until probed.
3. Prefer tiny synthetic or mock data when explaining domain examples. Do not require a future agent to run external examples, notebooks, or download public datasets merely to answer a modeling question.
4. Ask before long training, broad extra installation, network downloads, or GPU use. If the task can be answered with distilled module behavior and a tiny mock pattern, do that first.
5. If a question is really about core primitives, shapes, SVI, MCMC, or poutine, reroute to the sibling sub-skill instead of duplicating core mechanics here.

Reroute Boundaries

• Basic pyro.sample, pyro.param, pyro.plate, parameter-store lifecycle, PyroModule, and pyro.render_model basics: route to ../modeling-basics/.
• Distribution choice, HMM distribution shapes, support constraints, .to_event(), GaussianHMM, LinearHMM, and log_prob shape errors: route to ../distributions-and-shapes/.
• SVI loops, ELBO choice, autoguides, Pyro/PyTorch optimizer mechanics, and minibatching: route to ../svi-and-autoguides/.
• HMC/NUTS/MCMC, posterior predictive sampling, and diagnostics: route to ../mcmc-and-prediction/.
• Poutine handler ordering, trace/replay/condition/block, discrete enumeration, TraceEnum_ELBO, infer_discrete, Funsor-backed enumeration mechanics, and reparameterizers: route to ../effect-handlers-and-enumeration/.

Fast Triage

User asks about	Start here	Then hand off when needed
Time-series forecasting with future samples	pyro.contrib.forecast in the module map	SVI/MCMC or distribution-shape siblings for inference mechanics
Gaussian-process regression/classification/GPLVM	pyro.contrib.gp in the module map	SVI/MCMC sibling for training choices; shapes sibling for kernel tensor issues
SIR/SEIR/regional epidemic model	Epidemiology domain notes	MCMC/SVI sibling for fit settings; optional integration notes for CUDA/plotting
Object tracking or EKF	Tracking domain notes	Distribution-shape sibling for likelihood shapes
Discrete HMM, capture-recapture, RSA	HMM/RSA/capture-recapture domain notes	Enumeration/effect-handler sibling
scANVI, VAEs, AIR, DMM, CEVAE	Domain notes plus optional integration policy	SVI/autoguide sibling for training-loop fixes
pyro.contrib.funsor import error	Optional integrations and troubleshooting	Enumeration sibling for non-Funsor fallback
Graphviz/rendering failure	Optional integrations and troubleshooting	Modeling-basics for pyro.render_model usage