{"library":"numpyro","type":"library","category":null,"description":"NumPyro is a probabilistic programming library that leverages JAX for automatic differentiation, JIT compilation, and GPU/TPU acceleration. It allows users to build and infer Bayesian models with a flexible and composable API inspired by Pyro. NumPyro is currently at version 0.20.1 and maintains a regular release cadence, often releasing minor versions monthly or bi-monthly with new features, bug fixes, and performance improvements.","language":"python","status":"active","version":"0.20.1","tags":["probabilistic programming","bayesian inference","jax","deep learning","mcmc","variational inference"],"install":[{"cmd":"pip install numpyro[cuda12_pip] -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html","imports":["import numpyro","import numpyro.distributions as dist","from numpyro.infer import MCMC, NUTS","import jax; key = jax.random.PRNGKey(0); key1, key2 = jax.random.split(key)"]},{"cmd":"pip install numpyro[cpu]","imports":[]}],"homepage":"https://num.pyro.ai","github":"https://github.com/pyro-ppl/numpyro","docs":null,"changelog":"https://github.com/pyro-ppl/numpyro/blob/main/CHANGELOG.md","pypi":"https://pypi.org/project/numpyro/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":12.4,"avg_import_s":2.97,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/numpyro/compatibility"},"provenance":{"verified_status":"install_fail","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Sun Jul 05","install_tag":null}}